Relationship between caries-affected dentin mineral density and microtensile bond strength

Transcription

1 University of Iowa Iowa Research Online Theses and Dissertations Spring 2011 Relationship between caries-affected dentin mineral density and microtensile bond strength Savitri Vaseenon University of Iowa Copyright 2011 Savitri Vaseenon This thesis is available at Iowa Research Online: Recommended Citation Vaseenon, Savitri. "Relationship between caries-affected dentin mineral density and microtensile bond strength." MS (Master of Science) thesis, University of Iowa, Follow this and additional works at: Part of the Other Dentistry Commons

2 RELATIONSHIP BETWEEN CARIES-AFFECTED DENTIN MINERAL DENSITY AND MICROTENSILE BOND STRENGTH by Savitri Vaseenon A thesis submitted in partial fulfillment of the requirements for the Master of Science degree in Operative Dentistry in the Graduate College of The University of Iowa May 2011 Thesis Supervisor: Associate Professor Steven R. Armstrong

3 Graduate College The University of Iowa Iowa City, Iowa CERTIFICATE OF APPROVAL MASTER'S THESIS This is to certify that the Master's thesis of Savitri Vaseenon has been approved by the Examining Committee for the thesis requirement for the Master of Science degree in Operative Dentistry at the May 2011 graduation. Thesis Committee: Steven R. Armstrong, Thesis Supervisor Deborah S. Cobb Maria M. Hernandez Punam K. Saha Fang Qian James S. Wefel

4 To mom, dad and Todd. ii

5 ACKNOWLEDGMENTS I would like to express my sincerest thanks to my thesis supervisor, Dr. Steve Armstrong for his guidance and dedication. The research project for my thesis was extremely interesting and challenging for me and clinically relevant to my area of research interest. I was totally inspired and encouraged by Dr. Armstrong s intelligence and enthusiasm and I could not have accomplished this thesis project without his kind support, patience and guidance. Thank you Dr. Armstrong. I truly appreciate all that you have done for me. I would also like to acknowledge members of my thesis committee for their helpful advice and effort. Thanks to Dr. Hernandez for her kindness and suggestions on specimen preparation protocol for SEM analysis. Thanks to Associate Professor Saha for his great support in facilitating µct and helpful advice in developing a protocol on specimen preparation for µct scanning and BMD software for mineral density interpretation. Thanks to Dr. Qian for devoting her expertise and time in analyzing my pilot and thesis data. Thanks to Dr. Wefel for his valuable input on the thesis proposal and for providing HA crystal for the project. I could not have made it without Dr. Cobb s support, not only for this project but my life lessons. I am very pleased to express my gratitude to Dr. Denehy, Operative Chairman, for giving me an opportunity to be a part of the Operative Program at Iowa. Thanks to Operative faculty, staff, and graduate students for their support and hospitality. Thanks to Kathy Walters and Jean Ross for SEM training and accessibility. Thanks to Dr. Brogden for his useful tips on SEM protocol. Thanks to Maggie Hogan for providing teeth samples for this project. Special thanks to Professor Hoffman for his worthwhile input on this project regarding µct scanning. Thanks to Tim and Jered for carrying out µct scanning for this research. Special thanks to Guoyuan Liang for putting in a tremendous iii

6 effort with BMD software and for his helpful advice. I am so thankful for his support and laptop availability. I am very grateful to the following people for being a part of my achievement; Dr. Ronald and Sonia Ettinger for their kindness and generosity, thanks to Jib, Ore, Tipapat, and all my Thai friends for their significant support in every way and thanks to my lovely classmates, Karine and Carolina, for being so supportive throughout my entire study. Thanks to my colleagues from the Department of Restorative Dentistry, Chiang Mai University, for giving me an opportunity to pursue my advance study. Last but not least, I truly appreciate the immeasurable love and support from my mom, dad, and my husband. Without them, I would not have been here. Thank you all very much. This project is funded by the Academy of Operative Dentistry s 2009 George C Paffenbarger Student Research Award. iv

7 TABLE OF CONTENTS LIST OF TABLES... viii LIST OF FIGURES... ix CHAPTER 1 INTRODUCTION...1 CHAPTER 2 REVIEW OF LITERATURE...3 Introduction...3 Background and Significant...3 Compositional and structural aspects of the tooth...3 Enamel...3 Dentin...4 Cementum...6 Tooth pathology...6 Etiology of dental caries...6 Histology and pathophysiology of dental caries...7 CAD...8 Caries detector dye...10 Demineralization and remineralization...12 Management of dental caries...13 Noninvasive or preventive management strategies...13 Restorative treatment...13 Resin-based composite (RBC)...14 Terminology...14 Classification...14 Current classification of bonding agents...17 Etch-and-rinse adhesives...17 Self-etch adhesives...17 Glass ionomer adhesives...17 Concepts of adhesion...18 Enamel adhesion...18 Dentin adhesion...18 Adhesion to CAD...20 µtbs test...22 Concept and development...22 Specimens preparation for µtbs testing...23 µtbs mechanical testing method...23 µtbs of current adhesives...23 Tools for measuring dentin's mineral density...24 Microradiography (MR)...24 µct...25 Summary of previous literature...28 Current knowledge...28 Gaps in knowledge...30 CHAPTER 3 METHODOLOGY...38 Introduction...38 Research question...39 v

8 Specific aim...39 Research hypotheses...39 Null hypotheses (H 0 )...39 Alternative hypotheses (H A )...40 Operational Definitions...40 Population & Sample...41 Study design...41 Specimen preparation...41 µtbs testing...43 Mineral density measurement...43 Fracture Mode Analysis by Scanning Electron Microscopy (SEM)...45 Statistical Analysis...45 CHAPTER 4 RESULTS...51 Introduction...51 Part 1: µtbs vs. image intensity...53 Statistical results...53 Part 2: failure mode vs. image intensity...55 Statistical results...55 Part 3: µtbs vs. failure mode...58 Statistical results...58 Part 4: Level of dye staining vs. image intensity...59 Statistical results...60 Failure mode analysis...61 CHAPTER 5 DISCUSSION...83 Research hypotheses...83 Discussion...85 Conclusion...96 Study limitations...97 Clinical significance and future perspective...98 APPENDIX METHOD SHEET FOR PROJECT CAD bonding and µtbs Tooth collection and cleaning Tooth embedding in stone blocks Tooth numbering Tooth preparation Caries staining: 1 st stain Tooth flattening Caries staining: 2 nd stain Recording of staining pattern and location Bonding procedure Sectioning Dumbbell-shape specimen preparation µtbs testing µct, BMD determination, and SEM Fractured specimen management and µct BMD determination SEM analysis vi

9 REFERENCES vii

10 LIST OF TABLES Table 1. List of products used in sample preparation process...47 Table 2. Descriptive statistics of selected variables in the study for all specimens...62 Table 3. Descriptive statistics of selected variables in the study for all specimens, CAD, and normal dentin by including and excluding apparently adhesive and mixed failures...62 Table 4. Correlation between µtbs and image intensity...63 Table 5. Descriptive statistics of image intensity by failure modes for all specimens...64 Table 6. Mean image intensity of slice 1 by failure modes for all teeth...65 Table 7. Mean average image intensity of slices 1 and 2 by failure modes for all teeth...65 Table 8. Mean image intensity of slice 1 by failure modes for CAD...66 Table 9. Mean average image intensity of slices 1 and 2 by failure modes for CAD...66 Table 10. Mean image intensity of slice 1 by failure modes for normal teeth...66 Table 11. Mean average image intensity of slices 1 and 2 by failure modes for normal teeth...67 Table 12. Descriptive statistics of µtbs by failure modes for all specimens...67 Table 13. µtbs by failure modes for all teeth...68 Table 14. µtbs by failure modes for CAD Table 15: µtbs by failure modes for normal teeth...68 Table 16. Descriptive statistics of image intensity by levels of dye staining for all teeth...69 Table 17. Mean image intensity of slice 1 by 3 levels of dye staining for all teeth...70 Table 18. Mean average image intensity of slices 1 and 2 by 3 levels of dye staining for all teeth...70 viii

11 LIST OF FIGURES Figure 1. SEM photomicrograph of enamel, showing enamel rods...31 Figure 2. SEM photomicrograph of dentin, showing peritubular dentin and dentinal tubule...31 Figure 3. SEM photomicrograph of intertubular dentin, showing collagen fibers and hydroxyapatite crystals...32 Figure 4. SEM photomicrograph of dentin near dentin-enamel junction (DEJ), showing dentinal tubules at the level close to DEJ...32 Figure 5. SEM photomicrograph of dentin near pulp, showing greater number of dentinal tubules at the level close to pulp when compared to superficial dentin...33 Figure 6. SEM photomicrograph of CAD, showing turbid zone...33 Figure 7. SEM photomicrograph of CAD, showing mineral occlusion in dentinal tubule in CAD...34 Figure 8. SEM photomicrograph of CAD, showing Whitlockite crystals in transparent zone...34 Figure 9. SEM photomicrograph of CAD, showing Whitlockite crystals in dentinal tubules in transparent zone...35 Figure 10. SEM photomicrograph of CAD, showing plate-like crystals in subtransparent zone...35 Figure 11. RBC development and classification based on filler size particles...36 Figure 12. Classification of contemporary adhesives by type and number of clinical application steps...36 Figure 13. Experimental design of µtbs testing...37 Figure 14. SEM observation of resin-dentin interface...47 Figure 15. Summary of methods...48 Figure 16. Steps in CAD specimen preparation...49 Figure 17. Steps in normal dentin specimen preparation...49 Figure 18. Steps in specimen preparation for µtbs test, µct and SEM...50 Figure 19. Resin-dentin interface from different specimens' fracture pattern and mineral density measurement at the resin-dentin interface...50 Figure 20. Graph plot between image intensity slice 1 vs. µtbs of all teeth...71 ix

12 Figure 21. Graph plot between average image intensity of slices 1&2 vs. µtbs of all teeth...71 Figure 22. Graph plot between image intensity slice 1 vs. µtbs of CAD...72 Figure 23. Graph plot between average image intensity of slices 1&2 vs. µtbs of CAD...72 Figure 24. Graph plot between image intensity slice 1 vs. µtbs of normal dentin...73 Figure 25. Graph plot between average image intensity of slices 1&2 vs. µtbs of normal dentin...73 Figure 26. Graph plot between image intensity slice 1 vs. µtbs of all teeth, series categorized by 2 levels of dye staining...74 Figure 27. Graph plot between average image intensity of slices 1&2 vs. µtbs of all teeth, series categorized by 3 levels of dye staining...74 Figure 28. Graph plot between image intensity slice 1&2 vs. µtbs of all teeth, series categorized by 2 levels of dye staining...75 Figure 29. Graph plot between average image intensity of slices 1&2 vs. µtbs of all teeth, series categorized by 3 levels of dye staining...75 Figure 30. Failure mode analysis of all specimens...76 Figure 31. Failure mode analysis of CAD...76 Figure 32. Failure mode analysis of normal teeth...77 Figure 33. SEM photomicrograph of a fracture specimen cohesively in dentin...77 Figure 34. SEM photomicrograph of a fracture specimen cohesively in dentin, showing peritubular dentin and intertubular dentin in CAD...78 Figure 35. SEM photomicrograph of a fracture specimen cohesively in dentin, showing dentinal tubules in normal dentin...78 Figure 36. SEM photomicrograph of a fracture specimen cohesively in dentin, showing Whitlockite crystal in dentinal tubule in CAD...79 Figure 37. SEM photomicrograph of a fracture specimen cohesively in RBC...79 Figure 38. SEM photomicrograph of a fracture specimen cohesively in RBC, showing resin matrix filled with filler particles in Z Figure 39. SEM photomicrograph of a fracture specimen apparently in adhesive...80 Figure 40. SEM photomicrograph of a fracture specimen apparently in adhesive, showing upper hybrid layer...81 Figure 41. SEM photomicrograph of a fracture specimen apparently in adhesive, showing lower hybrid layer...81 x

13 Figure 42. SEM photomicrograph of a fracture specimen in mixed group...82 Figure 43. SEM photomicrograph of a fracture specimen in mixed group, showing CAD and adhesive...82 Figure 44. Graph plot between image intensity slice 1 vs. µtbs of all teeth, series categorized by type of teeth Figure 45. Illustration of CAD's Knoop hardness in a relation to ultrastructural characteristics including mineral deposition and odontoblastic process Figure 46. Dumbbell specimen showing tested or gauge area of 1 mm (1000 µm) with 0.5 mm-length (500 µm) of dentin in gauge area Figure 47. µct image of fractured specimen showing ideal area of interest (resindentin interface and ideal starting and ending point for µct determination Figure 48. µct image of fractured specimen showing area of interest (resin-dentin interface and starting and ending point for µct determination in specimen where fracture location is close to interface xi

14 1 CHAPTER 1 INTRODUCTION The primary goal of conservative restorative dentistry is to maintain the natural dentition in an optimum state of health, function and esthetics. Therefore, adhesive technology has gained in popularity because it provides the conservative approach with minimally invasive techniques that preserve tooth structure. In addition to the preservation of tooth structure, adhesive-retained resin-based composite (RBC) provides optimal esthetics. Many previous studies have focused on the adhesion between tooth and RBC. These studies have demonstrated that these two different substrates have reliable initial adhesion, but the long-term adhesion of some RBC remains questionable. Moreover, a study by De Munck et al (De Munck et al., 2005) found that the interface between dentin and adhesives tend to degrade over time. Thus, many studies have been conducted to improve dentin bond strength and seal to minimize degradation. Currently, the survival rates of RBC is somewhat lower than amalgam (Garcia, 2009), the conventional filling material; although amalgam is more durable, its unesthetic color has limited its use. Even though it has been demonstrated that current three-step total-etch adhesives give favorable results with initial dentin bond strength studies in vitro, in clinical situations, saliva, occlusal forces, temperature change, acidity of food and drink may impair the performance and thus, affect their long-term durability. Several strategies are currently being investigated to improve dentin-resin bond outcomes to include: (1) increasing the degree of conversion and esterase resistance of hydrophilic adhesives, (2) the addition of inhibitors of collagenolytic enzymes, (3) increasing the cross-linking density of the collagen matrix, (4) ethanol wet-bonding to infiltrate more hydrophobic adhesives, and (5) biomimetic remineralization within the hybrid later (Liu et al., 2011).

15 2 In clinical practice, the most frequent tooth substrate that dentists restore is demineralized dentin or caries-affected dentin (CAD) (Perdigao, 2010). Therefore it is critical that we acquire a better understanding of CAD s physical properties and mechanism of adhesion for the advancement of minimally invasive restorative dentistry. The bond between CAD and adhesive materials is not as strong as that with normal teeth (Erhardt et al., 2008) and hence, the reduced bond strength leads to failure of the restoration over time. This problem remains unresolved and has raised interest in studies comparing the strength of the bond between CAD and RBC using different bonding strategies. To test the bond strength of CAD, understanding its modulus of elasticity and strength properties is very important. An examination of the degree of caries dye staining has shown that pink and light pink stained CAD has lower elastic modulus than nonstained normal dentin (Pugach et al., 2009). Even among CAD group, its mechanical properties and microstructure can vary. One promising method to obtain a better understanding of CAD physical properties is to measure the mineral density of the substrate with micro-computed tomography (µct). This may help to explain the relationship between the degree of mineral density and modulus of elasticity of CAD. Since there have been no studies measuring the mineral density of CAD at the resindentin interface, the purpose of this study was to determine the µtbs of CAD and the degree of mineral density of CAD using wet-bonding technique.

16 3 CHAPTER 2 REVIEW OF LITERATURE Introduction This chapter will review the basic knowledge of tooth structure, in terms of compositional and structural aspects of enamel, dentin and cementum, along with the formation and apposition of mineral. Tooth pathology will also be reviewed; the main focus will involve dental caries and its etiology, histology of dental caries, caries development and the demineralization and remineralization processes. Management of dental caries will also be reviewed and will focus mainly on restorative aspects and RBC as a material of choice. Current adhesives used to bond RBC with tooth structure will be discussed regarding their performance of bonding with tooth substrates, especially CAD. One possible way to measure the quality of the bond is to test the µtbs of RBC to CAD. To review the bond to CAD, one must understand the mineral density of CAD. The measurement of CAD's mineral density technique will also be included in this chapter. Finally, the current knowledge and gaps in knowledge will be summarized. Background and Significant Compositional and structural aspects of the tooth Enamel The tooth is considered the most important structure involved in the chewing mechanism. Tooth structure consists of enamel, dentin, pulp and cementum. Enamel is a hard dental tissue developed from ameloblast cells. Enamel is composed of 96% inorganic hydroxyapatite crystal by weight or more than 86% hydroxyapatite crystal by volume. It also contains organic matrix and a small amount of water; therefore, it is less hydrophilic compared to dentin which has higher water content. Scanning electron photomicrographs (SEM) reveal enamel rods (Figure 1) as the main structure surrounded

17 4 by interrod enamel. Enamel serves as a protective structure for dentin and pulp. Its color, texture and translucency vary among each individual. Enamel also serves as esthetic function as it maintains the shape of the tooth (Summitt JB, 2006). Dentin Dentin serves as an elastic support for enamel. Unlike enamel, dentin is composed of 70% inorganic hydroxyapatite crystal by weight or 50% hydroxyapatite crystal by volume. Dentin has a higher percentage of organic mineral (18% by weight or 25% by volume) and water (12% by weight or 25% by volume) compared to enamel. It is also considered more hydrophilic when compared to enamel. Odontoblast cells play the major role in dentin formation (Summitt JB, 2006). Dentin structure is composed of four main elements (Figure 2 and 3): (1) dentinal tubules surrounded by (2) highly mineralized peritubular dentin embedded in intertubular dentin (3) cross-linked type I collagen which forms peritubular and intertubular dentin; this collagen is embedded in hydroxyapatite crystal and (4) dentinal fluid (Marshall et al., 1997). Dentin is porous in nature and is considered as a permeable tissue due to the numerous dentinal tubules. Peritubular dentin is a highly mineralized layer lining the dentinal tubule wall (Summitt JB, 2006). Tubule density is greater near the pulp (Figure 4 and 5). The size and number of the tubules gradually decrease from dentin-pulp interface (2.5 μm in diameter or 22 %) to the dentino-enamel junction (DEJ) (0.8 μm in diameter or 1 %) (Marshall et al., 1997). Intertubular dentin lies between the dentinal tubules and has lower mineral content compared to peritubular dentin. The amount of intertubular dentin is inversely related to the number of dentinal tubules. The more tubules per square milliliter area, the closer the tubules and thus, a lesser amount of intertubular dentin. The mineral phases of dentin can be described as calcium hydroxyapatite (HA) with the ideal formula of Ca 10 (PO 4 ) 6 (OH) 2 (Kay et al., 1964). However, the biological HAs are not pure, containing carbonate-containing apatites and some other elements such

18 5 as Magnesium (Mg), Phosphate (PO 4 ), Chloride (Cl), Fluoride (F), Sodium (Na), Carbonate (CO 3 ), to name a few. The biological apatites have a formula of (Ca, Mg, Na, X) 10 (PO 4, HPO 4, CO 3 ) 6 (OH, Cl) 2 and is called carbonate hydroxyapatite (CHA) (LeGeros, 1990). Dentin and bone are more soluble than enamel due to impurities. Carbonate substitution in biological apatites increases apatite solubility (LeGeros & Tung, 1983). Dentin can be classified to three different types according to the formation process: (1) primary dentin, (2) secondary dentin, and (3) tertiary dentin. Primary dentin and secondary dentin are part of the physiologic dentin formation process. The primary dentin is formed during the tooth development, while secondary dentin is formed slowly throughout the life as the pulp is still vital. This results in decreasing the pulp size as the tooth ages. Tertiary dentin is formed in response to the protective mechanism of the dental pulp against noxious stimuli, for example, the invasion of pathogenic bacteria or bacterial products. Tertiary dentin lies between dental pulp and secondary dentin. It is formed in order to compensate for dentin lost at the periphery, dentin lost from bacterial invasion or in response to a slow progressive mechanical trauma or injury (Summitt JB, 2006). Tertiary dentin can be classified to (1) reactionary dentin and, (2) reparative dentin. Reactionary dentin is a tertiary dentin formed by surviving post-mitotic odontoblast cells as a reaction to stimuli, while reparative dentin is formed by odontoblast-like cells (Smith et al., 1995). When bacteria invade dentin, a loss of mineral from dentin, or demineralization, occurs. Physiologic normal dentin will transform into carious or demineralized dentin by bacterial acid attacking. Since the acid molecules are relatively small and can penetrate through enamel causing demineralization in enamel and dentin even before a cavitation in enamel occurs. The demineralization process is caused by exposure of dentin to acidic solutions with ph less than a critical limit (Dawes, 2003), which is approximately 6.4 (Summitt JB, 2006). This carious dentin is full of pathogenic bacteria and bacterial by-

19 6 products. Once the dentin is infected by bacteria, the pulp will response to noxious stimuli by completely blocking the dentinal tubule or decrease the lumen size to prevent bacteria and bacterial toxins invasion (Perdigao, 2010). Carious dentin is described as two different layers, an outer layer is called caries-infected dentin (CID), and an inner layer is called CAD (Marshall et al., 1997; Wang et al., 2007). A full description of each layer and the ultrastructural changes that occur in carious dentin will be discussed later in this chapter. Cementum Cementum is a dental hard tissue covering the root area. It is secreted by the cementoblast. Cementum derived from mesenchymal cells and is formed after Hertwig's epithelial root sheath disintegrates (Diekwisch, 2001). Cementum composition is similar to dentin. It has roughly 50% inorganic and 50% organic matrix by weight. Collagen type I also plays an important role as a main component in organic part (Nanci & Bosshardt, 2006). There are four types of cemento-enamel interrelation: (1) cementum overlapped by enamel, (2) enamel overlapped by cementum, (3) edge-to-edge, and (4) gap patterns. The most frequent pattern observed is enamel overlapped by cementum (Neuvald & Consolaro, 2000). Tooth pathology Etiology of dental caries The carious process has been shown to cause demineralization of dental hard tissue (Angker et al., 2004). According to Keyes & Jordan (Keyes, 1963), caries is a multi-factorial process. The three main factors are tooth substrate, dental plaque and diet. Moreover, the caries process also involves factors such as saliva, the immune system, topical fluoride exposures, time, patient's behavior, education, socioeconomic status,

20 7 income, knowledge and attitude of each individual. These influencing factors are understood to play an important role in the caries process. Histology and pathophysiology of dental caries Fusayama (Fusayama, 1979; Fusayama, 1991) described 3 aspects of the caries process: (1) demineralization by decomposing inorganic substance, (2) degenerating organic substance, and (3) bacterial invasion. The demineralization process of dentin causes a patho-morphological reaction of the dentin pulp complex in response to the carious attack, resulting in peritubular, intratubular and reactive dentin apposition within the dentinal tubules and pulp chamber (Arnold et al., 2000). There are many ways to classify the dentin caries zone. According to Arnold et al (Arnold et al., 2000), carious dentin can be classified into six different zones which are: (1) softened dentin, (2) demineralized dentin, (3) bacterial invasion into the tubules, (4) translucency zone of dead tracts, (5) hypermineralized translucent zone and (6) secondary dentin respectively. However, Marshall et al and Wang et al. (Marshall et al., 1997; Wang et al., 2007), as mentioned previously, have classified carious dentin into two different layers - CID and CAD. CID is a superficial layer where there is a destruction of mineral matrix or crystal. This layer is full of pathogenic bacteria and bacterial by-products. Due to high levels of decalcification or demineralization in CID, it is impossible to return to a normal stage (unremineralizable). This layer is fuchsin-stainable showing degraded collagen fibers with disruption of cross-links. The discontinuation of cross-links indicates an irreversible stage of collagen, or denatured collagen, and thus unremineralizable. The inner zone, CAD, is partly, but highly heterogeneously, demineralized. Usually, CAD is remineralizable due to sound collagen fibers, fuchsin-unstainable, surrounded by hydroxyapatite crystals (Perdigao, 2010). This zone is free of bacteria and should ideally be preserved during tooth preparation.

21 8 CAD Since CAD is one of the most relevant substrates in clinical practice, understanding its nature is of great importance to dentistry and to minimally invasive restorative dentistry. Many studies of CAD have attempted to describe: (1) the carious zones, (2) physical and ultrastructural properties, (3) its ability and process of remineralization, and (4) resin-dentin bonding mechanism and durability, to name a few. There are many studies regarding these aspects mentioned above, unfortunately, scientific disagreement and unknowns remain. According to caries zone classification by Fusayama (Fusayama, 1979; Fusayama, 1993), inner layer of carious lesion or CAD can be classified to 3 zones: (1) turbid, (2) transparent and, (3) subtransparent zone. The turbid zone (Figure 6) is the zone where peritubular dentin is not present due to the process of demineralization; however, the intertubular dentin is identifiable but demineralized (Marshall et al., 1997). The demineralization process is reversible (Fusayama, 1991) due to the presence of crosslinked collagen - a key to remineralization (Marshall et al., 1997; Perdigao, 2010). This zone is bacteria free and a living odontoblastic process is present, which also plays part in remineralization process by supplying calcium phosphate from the pulp. The typical characteristic of CAD is the presence of mineral plug in dentinal tubules. However, turbid zone, the outer part of inner carious layer is free of mineral occlusion due to demineralization process from acid produced by bacteria (Fusayama, 1979; Fusayama, 1991). In the transparent zone, both peritubular and intertubular dentin remain but mineral crystal is present in dentinal tubule. The mineral may be partially or completely occluded in the tubule (Figure 7). Unlike the turbid zone, transparent dentin can be hypomineralized due to caries process or can be hypermineralized (sclerotic). No bacterial invasion found in this zone. In addition, living odontoblastic process is visible in this zone but more pitted on its surface due to mineral deposition. The mineral crystal in

22 9 the transparent zone has a typical character as a rhomboid-shape crystal. It is termed by Frank et al (Frank et al., 1964) as Whitlockite (Figure 8 and 9) which is a β-tricalcium phosphate (Daculsi et al., 1987). This crystal is formed by the caries process dissolution and recrystalization from hydroxyapatite crystal. Once the caries process begins, a fine plate-like crystal starts to deposit in peritubular dentin wall in normal dentin close to the carious lesion (subtransparent zone). The rhomboid-shape crystal is gradually formed in transparent zone and slowly appeared irregularly toward the outer zone of carious lesion. Upon reaching the outer layer (turbid and toward infected dentin), the crystal disappears. Within the transparent zone, the Whitlockite crystal is usually larger toward the center of the dentinal tubule (Ogawa et al., 1983). Remineralization process in transparent zone is possible due to the presence of sound collagen structure and vital odontoblastic process (Fusayama, 1991). The innest zone of CAD is called subtransparent zone. In this zone, the tubule is usually not completely occluded with mineral but the mineral level in intertubular dentin might not be normal (Fusayama, 1993; Marshall et al., 1997). The crystals in dentinal tubules are plate-like structure (Figure 10) or granular shape attached to collagen fibrils. Uniformly with transparent zone, subtransparent zone is uninfected with the presence of pitted odontoblastic process and sound collagen. Therefore, remineralization is achievable. The tubule occlusion from mineral deposition is thought to reduce dentin permeability. Although transparent dentin has extensive acid resistant mineral deposition, a lower hardness of Whitlockite crystals and lower calcium content in this layer causes transparent dentin to be softer than normal dentin (Ogawa et al., 1983; Fusayama, 1991; Marshall et al., 1997). Similarly, Ogawa et al (Ogawa et al., 1983) found that transparent dentin was not sclerotic and was softer than normal dentin. The hardness of carious dentin was highest at the junction between normal dentin and subtransparent dentin and progressively decreases toward subtransparent dentin and transparent dentin. They also

23 10 found that when transparent dentin was etched with 0.1 N HCL for 15 seconds, the peritubular dentin was more soluble than the deposited mineral crystal. This confirmed the acid resistance property of dentinal tubule mineral apposition in the transparent zone. As mentioned earlier, acid produced by pathogenic bacteria not only caused a dissolution of inorganic matrix, it also degenerates organic substance or collagen (Fusayama, 1991). Differences in the collagen structure between CID and CAD have been reported (Ogushi, 1973; Kuboki et al., 1977). They found that crossbanded collagen was present only in the inner CAD and absent in the outer CAD. Wefel (Wefel, 1994) hypothesized that remineralization occurred on collagen with existing mineral not on mineral depleted collagen. The presence of crossbanded collagen fibers is believed to be essential in remineralization process since apatite crystals can attach to these collagen molecules (Marshall et al., 1997; Perdigao, 2010). Moreover, the presence of vital odontoblastic process is also important for remineralization since it supplies the calcium phosphate from the pulp. Therefore, remineralization can occur in vital CAD where crossbanded collagen and odontoblastic processes are present (Fusayama, 1991; Marshall et al., 1997; Perdigao, 2010). Caries detector dye In clinical practice, criteria used as a guide to diagnose dentin carious lesion is based upon color and hardness or tactile consistency. However, color determination by visualization and hardness evaluation by tactile sense may not always be reliable since the nature and presentation of acute and chronic dentin carious lesions are extremely variable. In chronic carious dentin, using color as an indicator to detect carious dentin is more reliable than hardness since discoloration in chronic caries is remarkable, and bacterial penetration is usually close to the staining front. In acute carious lesion, however, discoloration may not be a good indicator for clinical carious removal since discolored dentin is generally slight and usually located far from bacterial penetration

24 11 zone. Moreover, the softened, bacterial-free dentin in acute lesion could be as wide as 2 mm. Therefore, removing the final extent of soft dentin in an acute carious lesion would be considered as destructive and nonconservative (Fusayama et al., 1966). Due to controversies regarding dentin caries determination, many attempts have been made to develop criteria and aids to caries detection. In 1972, a caries detecting dye was introduced by Fusayama and Terashima (Fusayama & Terashima, 1972). An example of this caries detecting dye is Caries Detector (Kuraray Medical Inc., Tokyo, Japan) which contained 1 % acid red in propylene glycol (van de Rijke, 1991; Itoh et al., 2009). The dye distinguishes carious and non-carious dentin by staining the loosened collagen fibers on the outer layer of carious dentin lesion where collagen is irreversibly destroyed (Fusayama, 1988). However, Yip and coworkers (Yip et al., 1994) argued that the specificity of dye staining was to reduced mineral content area rather than differentiating between carious and non-carious dentin. They also found that the dye stained on sound DEJ due to a low inorganic content in this area. Therefore, using caries detecting dye would result in the unnecessary removal of dentin (Yip et al., 1994). Similarly, Kidd and others (Kidd et al., 1993) preferred the use of conventional tactile and optical criteria for caries removal over the use of caries detecting dye. They found that the stained and unstained DEJ had low numbers of residual bacteria and there was no statistically significant difference between these two groups. Thus, they concluded that using caries detecting dye would lead to over preparation. Due to these disadvantages and disagreements over the use of caries detecting dye, a new caries detecting agent, Caries Check (Nippon Shika Yakuhin, Shimonoseki, Japan) has been recently introduced with the specific intent of reducing the unnecessary removal of sound dentin. Caries Check contains 1% acid red in a higher molecular weight polypropylene glycol (MW = 300) as compared to the conventional dye (Caries Detector: 1% acid red in propylene glycol, MW = 76) (Hosoya et al., 2008a). According to a higher molecular weight, solution with higher molecular weight diffused less than the lower

25 12 ones (Trampel et al., 2002). Therefore, Caries Check should diffuse into dentin less than the conventional dye, and thus over staining is avoided. Correspondingly, some studies (Hosoya et al., 2008a; Itoh et al., 2009) have favored the use of Caries Check rather than conventional dye due to less dye penetration into CAD, hence, less excessive cavity preparation was realized. In addition to the correlation of dye staining and level of infection, Sunago and others (Sunago et al., 2009) found that there was a great variation of mineral density in red dye-stained dentin that considered to be removed before restorative procedure. Among the red stained dentin group, some samples had mineral density value comparable to normal dentin. As a consequence, dentin caries detection based on caries detecting dye alone might not be effective enough for clinical practice (Sunago et al., 2009). Although controversies regarding the use of Caries Detector dye remain, many studies still used the dye for research purposes (Pugach et al., 2009; Sunago et al., 2009; Neves et al., 2011a; Neves et al., 2011b). Demineralization and remineralization Caries is a dynamic process in which periods of demineralization and remineralization occur alternatively depending upon conditions in the oral environment. Demineralization occurs in two steps. First, the pathogenic bacteria metabolize the fermentable carbohydrates resulting in the production of organic acids, which can diffuse through the tooth surface. Secondly, the organic acid dissolves the mineral crystals resulting in release of calcium and phosphate ions into the oral environment (Featherstone, 2008). If the demineralization process continues to progress, cavitation may occur, unless the process is delayed by remineralization. Remineralization is a repair process in which there is a mineral re-uptake to the demineralized area. In this process, calcium and phosphate in saliva, with the help of fluoride, diffuse through the tooth surface and reform the crystal from the existing crystal

26 13 remnants (Featherstone, 2008). The replacement of fluoride ions for hydroxyl ions in hydroxyapatite results in a reformed crystal called fluoroapatite (FAp) with the formula of Ca 5 (PO 4 ) 3 F. The fluoride ions (F -, ionic radius = 1.36 Å) fill up the center of calcium triangles where displaced oxygen (0.3 Å) occurred. Consequently, hydroxyl ions (OH -, ionic radius = 1.40 Å) are no longer fit in. The substitution of F - with a slightly smaller ionic radius OH - results in more dense and chemical stability crystal formed (Aoba, 1997). This crystal is more resistant to acid dissolution compared to the original hydroxyapatite crystal and can withstand a lower critical ph (~ 4.5) (Summitt JB, 2006). This is one of major mechanism of fluoride acts to inhibit cavity formation and reverse the caries process (Featherstone, 2008). Management of dental caries Noninvasive or preventive management strategies There are many different treatment approaches for carious lesions depending upon causal factors, lesion stage and activity. The treatment strategies for management of early dental caries lesions can include preventive measures such as plaque removal, professional topical fluoride application, sealant, diet counseling and behavioral modification. The goal of noninvasive or preventive management is to restore the balance between preventive and pathological factors over the long term. Failure to maintain the balance would result in compromising enamel and dentin strength. When integrity of enamel and dentin has been lost, cavitation occurs and restoration is therefore needed. Restorative treatment In more severe cases of carious lesions, more extensive procedures may be required. According to Elderton and Mjör (Elderton, 1988), the indications for restorative treatment are The carious tooth is sensitive to hot, cold, sweetness, etc.

27 14 The occlusal and proximal lesions extend into dentin. The pulp is endangered. Previous attempts to stop the lesion have failed, and there is evidence that the lesion is progressing during the observation period. The patient's ability to provide effective home care is impaired. Drifting is likely to occur through loss of proximal contact. The tooth has an unesthetic appearance. The restorative material options can be direct (e.g. gold foil, amalgam, RBC, glass ionomer cement, resin-modified glass ionomer) or indirect restoration (e.g. cast restoration) depending on the individual case. In this chapter, only RBC will be discussed. Resin-based composite (RBC) Terminology RBC is a material that consists of a continuous polymeric or resin matrix within a dispersed phase of organic filler (Roberson, 2006). Classification Types of RBC can be classified in various ways based on the formulation for different application (restorative material, sealants, luting cements, etc.), consistency (universal, flowable, and packable RBC), and reinforcing fillers characteristic (Ferracane, 2011). RBCs are usually divided based on the size, amount, and composition of the inorganic filler. According to Roberson (Roberson, 2006), RBC is classified as (1) conventional composites, (2) microfill composites, and (3) hybrid composites. Subsequent changes in RBC composition have resulted in several hybrid type categories such as (1) Multipurpose or microhybrid composites, (2) Nanocomposites, (3) Microfill composites, (4) Packable composites, (5) Flowable composites, and (6) Laboratory

28 15 composites (Powers, 2008). In this chapter, classification will be based on a recent review article from Ferracane (Ferracane, 2011). Based on characteristic of filler particles, Ferracane (Ferracane, 2011) classified RBC to (1) Conventional or Macrofill composites, (2) Microfill composites, (3) Midifill composites (4) Minifill or Microhybrid composites, and (5) Nanofill composites (Figure 11). Conventional or Macrofill composites have relatively high filler size particles, around 50 µm or higher (Ferracane, 2011). The examples of commercial product are Filtek P60 (3M ESPE), Prodigy Condensable (Kerr), and Alert (Pentron Clinical Technologies) (Powers, 2008). Due to the high volume percentage of inorganic filler which ranges from 59 to 80%, this results in high wear resistance, less shrinkage and packable properties (Powers, 2006). However, they are not currently widely use since they have poor polished surface and difficult to retain surface luster providing lower the esthetic appearance. To overcome such problems, Microfill composites have been developed (Ferracane, 2011). The example of commercial product is Durafill VS (Heraeus) (Powers, 2008). The filler particle size is reduced to about 40 nm (Ferracane, 2011). The reduced filler size improves polishability property and gives the best esthetic result since they contain small filler size particles. However, the volume percentage of filler is relatively low, approximately 32-50%, along with the high percentage of resin matrix, resulting in higher shrinkage and low strength properties compared to conventional composites (Powers, 2006). Such limitations limit the use of the materials in small cavities and non-stress bearing sites, for example, small cavities on anterior teeth and cavities on buccal or lingual surfaces (Powers, 2006; Powers, 2008). To overcome the low strength property of Microfill, Midifill was developed with the average filler particle size of > 1 µm while the 40 nm-size particle still remains. Further improvement resulted in more fine grain filler particles, approximately µm and 40 nm. These RBCs are so-called Minifill or Microhybrid composites (Ferracane,

29 ). The examples of commercial product are Filtek Z250 and Z100 (3M ESPE), Esthet-X (Dentsply Caulk), Tetric EvoCeram (Ivoclar vivadent), and Estelite Sigma (Tokuyama America). The volume percentage of inorganic filler is 60-70%, which is relatively high and results in superior properties in terms of high strength and high modulus (Powers, 2008). These Microhybrid composites are considered as universal composite since they are applicable on both anterior and posterior teeth (Ferracane, 2011). The latest technology that has been developed is Nanocomposite. Besides the high strength and high modulus properties, they have the high capability of polishing since the average filler size particles are very small ( μm). The volume percentage of inorganic filler is 78.5%, which is higher compared to microhybrid composites (Powers, 2006). The examples of commercial product are Filtek Supreme Plus (3M ESPE), Simile (Pentron Clinical Technologies) (Powers, 2008), Premise (Kerr), Artiste (Pentron Clinical Technologies), and Renamel Nano (Cosmedent). Some products have included prepolymerized resin filler (PPRF) in their ingredients and are called Nanohybrids. Their physical properties are similar to Microhybrids with lower filler particle size (Ferracane, 2011). Each composite category has different properties based primarily on its filler size and volume percentage. Most of studies that investigated the adhesives' bond strength were done using Microhybrid composites since they have a good strength and high modulus. They also serve as all-purpose materials which can be used in many different cavity designs (occlusal, proximal, cervical lesion) and sites (anterior, posterior teeth). The use of Microhybrid composites also gives a benefit of comparable results among studies.

30 17 Current classification of bonding agents Based on the literature, there are also many classifications of dental adhesives. In this chapter, classification will be based on Van Meerbeek's classification (Van Meerbeek et al., 2003) since it is simple and has proved to be reliable and consistent (Summitt JB, 2006). Van Meerbeek et al (Van Meerbeek et al., 2003) have suggested a scientifically based classification with three groups of adhesives: etch-and-rinse adhesives, self-etch adhesives and glass-ionomer adhesives as shown in Figure 12 (Van Meerbeek et al., 2003; Summitt JB, 2006). Etch-and-rinse adhesives Etch-and-rinse adhesives can be classified into two types based on the number of steps used for applying adhesives. They are 3-step etch-and-rinse adhesives and 2-step etch-and-rinse adhesives. The 3-step etch-and-rinse adhesives system has separate bottles of material for etching, priming and bonding steps; while 2-step etch-and-rinse adhesives system combine the priming and bonding steps (De Munck et al., 2005). Self-etch adhesives Self-etch adhesives also have two types based on the number of steps of application. They are 2-step self-etch adhesives system and 1-step self-etch adhesives systems. Self-etch adhesives do not require a separate etching step since the prime material contains a water-soluble acidic polymerizable monomer that acts as an etchant to condition the tooth surface before the bonding step (De Munck et al., 2005). The term etching will be described in the next section. Glass ionomer adhesives Glass-ionomer adhesive has two separate pastes that when mixed together, the acid-base reaction hardens the material. This type of material has a different mechanism

31 18 of adhesion since it forms an ionic chemical bond to tooth structure (De Munck et al., 2005). In this chapter, only etch-and-rinse adhesives will be discussed in terms of mechanism of adhesion and supporting studies. Concepts of adhesion The main bonding mechanism of current resin adhesives can be regarded as an exchange process involving substitution of inorganic tooth material by resin monomers. This process involves two phases. The first phase, etching, consists of removal of calcium phosphates from the tooth by the application of acid, most commonly, phosphoric acid. This results in microporosities in enamel and dentin. The second phase or hybridization phase involves infiltration and polymerization of resin that incorporates into microporosities. This results in micromechanical interlocking between tooth and resin adhesives primarily based upon a diffusion mechanism. Enamel adhesion Currently, bonding to enamel is still best accomplished through the use of the etch-and-rinse adhesives. Etching with 30-40% phosphoric acid removes the enamel top layer for a few micrometers and selectively dissolves hydroxyapatite crystals within prismatic and interprismatic enamel. This increases surface roughness and surface energy of enamel and hence, facilitates the adhesive infiltration into the enamel surface by capillary action. The infiltration results in macro- and micro-tags of resin which creates retention of the material. This bond to enamel has been shown to be more reliable and much stronger compared to dentin bonding. Dentin adhesion For dentin bonding, phosphoric acid removes the smear layer and demineralizes the dentin, thus, creating the exposed collagen fibrils nearly depleted of hydroxyapatite.

32 19 The exposed collagen serves as a microretentive network for micromechanical retention of resin monomers that incorporate into the collagen network and form a hybrid layer through inter- and intra-tubular hybridization. A critical review of the durability of adhesion to tooth tissue (De Munck et al., 2005) demonstrated that the 3-step etch-and-rinse adhesives have the best performance in terms of durability of adhesion to dentin and, therefore, these authors consider them the gold standard. The simplified adhesives would compromise the bond and resulted in loss of bonding effectiveness (De Munck et al., 2005). This was due to the fact that most total-etch adhesives contain methacrylate-based monomers (Van Landuyt et al., 2007), for example, BisGMA (2, 2 - bis [4 (2 - hydroxy methacryloyloxy - propyloxy) - phenyl] propane, which has no specific chemical groups to compete with water (Tay et al., 2007) and thus, it was considered a hydrophobic bonding resin in nature (Tay et al., 2004). In contrary, dentin itself is very hydrophilic. It consists of dentinal tubules which contain dentinal fluid. These micropores act as a permeable membrane. Since there is a mismatch of dentin substrate (hydrophilic) and resin adhesives (hydrophobic), a poor adaptation of resin adhesives and the collagen network occurs. This results in a gap formation between these two substrates and leads to bond degradation at the interface over time. This degradation has been demonstrated by many studies. For example, a study (De Munck et al., 2003) concluded that resin bonded to enamel protected the resin-dentin bond against degradation, while direct exposure to water for 4 years affected bonds produced by two-step total-etch adhesives. This study suggested that durable dentin bonding using three-step or two-step total-etch adhesives could be achieved if cavity margins were surrounded by enamel. In case of dentin margins, three-step total-etch adhesives were preferable.

33 20 Although current three-step total-etch adhesives were shown to give a favorable result with a dentin margin in vitro, in clinical situations, saliva, occlusal forces, temperature change, and acidity of food and drink have the capability to impair the performance of current adhesives and thus, affect their long-term durability. That is, these resins tend to degrade over time. Therefore, a new concept of ethanol wet-bonding has been introduced, and several studies have found improved resin-dentin bonds using hydrophobic resin and ethanol. Nishitani et al (Nishitani et al., 2006) found that wetbonding with ethanol facilitates higher bond strengths with the use of relatively hydrophobic resins when compared to wet-bonding technique with hydrophilic resins. In spite of the fact that ethanol wet-bonding with hydrophobic resins has been shown to have higher bond strength and increased thermal stability of demineralized dentin collagen matrices compared to other dentin conditions and solvents (Nishitani et al., 2006), additional factors have to be considered. Residual ethanol solvent content higher than 30% lowers the degree of conversion of the tested resin blends (Cadenaro et al., 2008). Another study (Tay et al., 2007) also indicated that the use of this new concept needed further investigation since the results of the study showed that the ethanol wetbonding technique caused some degree of collagen fibril shrinkage. This phenomenon may permit greater interfibrillar monomer penetration but at the same time may have some adverse effect which cannot be ignored (Tay et al., 2007). Moreover, most of the studies about ethanol wet-bonding were performed in vitro. Further investigations are essential before application in clinical practice. Adhesion to CAD From those studies that found advantages of ethanol wet-bonding over the current wet-bonding concept, all of them were performed with normal dentin. In reality, most of the time dentists have to deal with carious dentin, CAD or sclerotic dentin. It has been reported that CAD has a lower µtbs when compared to that in normal dentin

34 21 (Yoshiyama et al., 2003; Nishitani et al., 2005). The authors concluded that the Ultimate Tensile Strength (UTS) for mineralized CAD is less than half that for normal dentin, but this difference is lost after the substrates were completely demineralized. In clinical situations with CAD present, the degree of mineralization and the width of the CAD layer are not uniform and differ from each individual tooth. This results in lower µtbs of CAD when compared to normal dentin. The lower bond strength may affect the longevity of the restoration (Ceballos et al., 2003). They found that the µtbs tested in CAD was lower than that of normal dentin. They also observed that adhesive failure and cohesive failure in dentin were most often found in the CAD group. Moreover, they investigated the correlation between bond strength and DIAGNOdent laser fluorescence and Knoop microhardness of CAD and found that both laser fluorescence and Knoop microhardness have a strong relation to each other. However, both of them did not have a strong relationship with the bond strength of CAD. Resin-dentin bonds from CAD interfaces are more susceptible to water degradation than sound dentin (Erhardt et al., 2008). In addition, bond strengths to sound dentin were significantly higher than those to CAD, regardless of the adhesive system or storage time. The poor resin tag formation in CAD leads to lower µtbs and susceptibility to degradation. CAD has lower µtbs than that of non-carious or normal dentin (Wang et al., 2007). As the result of chemical and structural alterations of CAD due to the caries process, the resin adhesives' infiltration into the CAD substrate is compromised and thus results in phase separation of resin adhesives which in turn lowers the µtbs of CAD. Hybrid layers in CAD (15-19 µm) are thicker than that in normal dentin (5 µm) but more porous in nature (Yoshiyama et al., 2002). This results in lower µtbs when compared to normal dentin. The reason the hybrid layer in CAD is thicker than normal dentin can be explained by the histological morphology of inner carious lesion in which the intertubular dentin is partially demineralized due to the caries process (Ogushi & Fusayama, 1975).

35 22 This results in a deeper etching pattern when CAD is treated with acid etching. The fact that dentinal tubules of CAD are filled with mineral crystal or Whitlockite crystal does interfere with the resin infiltration into dentinal tubules and with the depth of demineralization from acid etching. Even though peritubular dentin is acid-etchable, the blockage is present due to acid resistance properties of these crystal, thus, it results in a non-uniform and porous pattern of the hybrid layer (Wang et al., 2007). Yoshiyama et al (Yoshiyama et al., 2002) stated that many caries-affected specimens failed cohesively in the dentin due to their weaker substrate nature than bonding resin. Likewise, caries-affected primary dentin has a lower hardness and Young s modulus when compared to the sound primary dentin below (Hosoya et al., 2008b). Correspondingly, a dramatic decrease in volume% mineral from normal to pink stained dentin has been reported (Pugach et al., 2009). However, even in the pink stained dentin group, the residual mineral is found to be 25% of normal dentin which may have an important role in remineralization. Consideration in preserving the remaining mineralized dentin may be critical in conservative dentistry. In summary, the decrease in bond strength of CAD is likely a result from the poor resin tag formation (Erhardt et al., 2008) due to the blockage of resin infiltration from mineral crystals inside dentinal tubules (Wang et al., 2007), the decrease in hardness (Hosoya et al., 2008b) and volume% of mineral (Pugach et al., 2009), and the lower UTS of CAD (Nishitani et al., 2005). µtbs test Concept and development Bond strength tests are the most frequently used tests to screen adhesives. The rationale behind this testing method is that the stronger the adhesion between tooth and biomaterial, the better it will resist stress imposed by resin polymerization and oral

36 23 function. Currently, the shear and µtbs test methods are the most used (De Munck et al., 2005). Specimens preparation for µtbs testing Based on De Munck et al (De Munck et al., 2005), the experimental design of µtbs testing is as shown in figure 13. Steps in specimen preparation (De Munck et al., 2005) Remove enamel to minimally expose superficial dentin. The remaining dentin should be surrounded by enamel. The trimmed surface should be perpendicular to long axis of tooth. Apply resin adhesives following manufacturer's protocol. Resin composite build-up incrementally and light cure each increment for 40 seconds. Build-up until reaches the height of 4-5 mm. Store the tooth in distilled water for 24 hours. Vertically section the tooth into four, 2 x 2 x 10 mm sticks. Prepare the dumbbell shape specimen (0.8 mm in diameter) using MicroSpecimen former. Proceed to µtbs testing. µtbs mechanical testing method (Armstrong et al., 2003) Tensile testing at 1 mm/min is then performed with a material testing machine (Zwick 1445) with the cylindrical dumbbell test specimen passively gripped in a glueless gripping device (Dircks device) to failure. The µtbs value is recorded from the machine and the test repeated with a new specimen. µtbs of current adhesives A critical review of the durability of adhesion to tooth tissue (De Munck et al., 2005) found that the pooled µtbs of etch-and-rinse adhesives tested when bonded to

37 24 dentin showed that 3-step etch-and-rinse adhesives bonded significantly more strongly to dentin than did 2-step etch-and-rinse adhesives and 2-step self-etch adhesives. The latter two systems did not perform significantly different from each other. The significantly least favorable results were recorded for 1-step self-etch adhesives. These findings were consistent with a systematic review of restorations placed in non-carious cervical lesions (Peumans et al., 2005). They found that 3-step etch-and-rinse adhesives and 2-step etchand-rinse adhesives showed a clinically reliable and predictably good clinical performance. The clinical effectiveness of 2-step etch-and-rinse adhesives was less favorable, while an inefficient clinical performance was noted for the 1-step self-etch adhesives. In addition, an in vitro study found that the 2-step etch-and-rinse adhesives was significantly weaker than 3-step etch-and-rinse adhesives and 2-step self-etch adhesives after 1 and 6 months of water storage, but all three systems were equivalent after 15 months of water storage (Armstrong et al., 2003). The 1-step self-etch adhesives could not be tested due to failure of nearly all specimens (~89%) during preparation. In summary, 3-step etch-and-rinse adhesives provide the best clinical and in vitro performance while 1-step self-etch adhesives have the least favorable result. The performance of 2-step etch-and-rinse adhesives and 2-step self-etch adhesives vary among studies depending on study design. Mostly, their performance is in an acceptable range. Tools for measuring dentin's mineral density Microradiography (MR) Using conventional radiographs, the mineral density of teeth cannot be measured. The only aspect presented in the conventional radiograph image is the image contrast. Thus, this method is not practical for measuring mineral density of dentin. However, transverse microradiography (TMR) has been validated as a method of mineral volume measurement by its high correlation with microhardness (Pugach et al., 2009). MR

38 25 provides a high resolution but its destructive specimen preparation and two-dimensional assessment of a three-dimensional specimen has limited its use (Zou et al., 2011). µct µct is a miniature version of computerized axial tomography that has a resolution of a few micrometers (Wong et al., 2000). The clinical application of µct was introduced in early 1970s (Ritman, 2004). Elliott et al (1989) are believed to be the first who reported using µct in dentistry (Davis & Wong, 1996). Currently, µct has been used widely in dentistry, for example, it is used to construct the root canal configuration, evaluate the quality of bone regeneration in implant placement, measure the enamel mineral density in rat incisors (Wong et al., 2000) and measure the leakage of the resindentin interface (Mollica et al., 2004). Besides the use of microradiography (MR), µct is an alternative method in determining dentin mineral density by constructing a three-dimensional image with less destructive specimen preparation (Zou et al., 2011). µct provides volumetric x-ray attenuation measurements by revealing the spatial distribution of attenuation coefficients (µ) within the materials (Davis & Wong, 1996). µct has advantages over conventional radiograph since it can construct a three-dimensional image (Ritman, 2004), which is very useful in clinical dental research. It is a non-destructive method (Davis & Wong, 1996; Wong et al., 2000), which can project the soft tissue image without inputting any radiopaque medium in the soft tissue. The image can be cut into slices along three different axes. However, the image has relatively poor contrast (Ritman, 2004). Interpretation of such images with poor contrast may not be accurate. µct can be classified as two different types: synchrotron radiation microcomputed tomography (SRµCT), and conventional polychromatic micro-computed tomography (CµCT) (Zou et al., 2011). SRµCT produces parallel monochromatic x-ray beams (Lewis, 1997) which facilitates the accurate quantitation of linear attenuation

39 26 coefficients (µ), and thus density calibration and beam hardening corrections can be avoided (Dowker et al., 2004). While CµCT produces polychromatic x-ray beams from cone beam geometry (Wong et al., 2000) which creates a beam hardening problem (Clementino-Luedemann & Kunzelmann, 2006). Beam hardening is likely to cause artifacts in the scanned image due to underestimation of µ toward the center of scanned material (Zou et al., 2011). The fact that CµCT has other physical limitations, besides beam hardening, such as geometrical blur, beam divergence, and limited intensity flux impacts CµCT performance (Chappard et al., 2006). Ideally, mineral density should be measured with SRµCT to reduce the risk of artifacts as described above. A study (Dowker et al., 2004) showed that enamel mineral densities obtained from SRµCT were consistent with previous studies using MR. Unfortunately, there is a limited access to SRµCT (Elliott et al., 1998) and therefore, CµCT is widely used (Zou et al., 2011). Three methods to correct beam hardening have been discussed: (1) beam infiltration during the scan, (2) beam hardening correction during image reconstruction, and (3) mineral density calibration (Zou et al., 2011). Filtering can convert polychromatic x-ray beams from CµCT to monochromatic x-ray beams; however, increased exposure time may be required due to decreased x-rays from filtration. Furthermore, to correct beam hardening during reconstruction, a step-wedge calibration or reconstruction software can be used. Another method to correct beam hardening is the use of phantoms with known densities for calibration (Zou et al., 2011). Several phantoms have been used in bone research, such as: Hydroxyapatite (HA)-resin phantom (Burghardt et al., 2008), HA-Li 2 B 4 O 7 solid phantom (Zou et al., 2011), and K 2 HPO 4 liquid phantom (Nazarian et al., 2008). Limitations with HA-epoxy resin composites in calibration due to inhomogeneity of the phantom have been described. Moreover, the range of HA concentration in HA-resin phantom (0-800 mg HA/cm 3 ) did not cover the biological range of bone which is usually greater than 1000 mg HA/cm 3. Extrapolation of the calibration curve was required in order to obtain an

40 27 actual density relatively to HA-resin phantom density. Therefore, extrapolating the calibration curve is likely to cause errors in actual density value (Schweizer et al., 2007). To overcome the problem regarding range of densities, HA-Li 2 B 4 O 7 solid phantom was introduced (Zou et al., 2011). Its ability for custom fabrication (Zou et al., 2011) provides a density range up to 3050 mg/ cm 3 (Schweizer et al., 2007). However, concerns in application remain since the need for extrapolated calibration curve are still require (Zou et al., 2009). Another alternative of HA-resin phantom is K 2 HPO 4 liquid phantom which be used to obtain bone mineral density. It is cost-effective and easily prepared (Nazarian et al., 2008). Nevertheless, problems of air bubble formation and water evaporation may impair its performance (Zou et al., 2011). A recent study (Zou et al., 2009) has proposed the use of two-phase calibration. Two different phantoms, K 2 HPO 4 solution phantoms (0 0.9 g/ cm 3 ) and porous solid HA phantoms ( g/ cm 3 ) were used to construct a calibration curve which gave a wider range of mineral density, and thus extrapolation of calibration curve was not necessary. According to Zou et al (Zou et al., 2011), commonly used phantoms in dental research are Aluminum (Al) and pure HA solid phantom. Using Al for calibration, one can standardize the mean µ for each scanned image using the ratio of the published µ value for Al to the measured value based on the assumption that HA is the only content in scanned tissue. Additionally, Al facilitates the calibration only when the attenuation vs. energy characteristics of scanned specimens matches those of Al. Using Al to measure mineral density of enamel is practical since enamel mainly consists of inorganic phase. However, dentin is a heterogeneous tissue, measuring normal and carious dentin s density might be misinterpreted by assuming that HA is the only content in those substrates. Moreover, measuring normal and carious dentin s density, the value obtained depends on the ratio of normal and carious dentin s µ to Al, which may be different and unreliable since the caries process may have an impact on µ due to structural alterations (Zou et al., 2011).

41 28 Using pure HA solid phantom to measure mineral density of enamel would be beneficial since HA is considered the closest in composition to enamel (Huang et al., 2007). However, this might not be valid in dentin due to its heterogeneous nature mentioned above. Therefore, Willmott et al (Willmott et al., 2007) proposed a study to determine mineral concentrations of carious dentin in deciduous molars by assuming that mineral phase of dentin was based purely on HA and the organic phase on collagen. In this study, however, they used Al as a calibrating reference and a symmetrical 7-step wedge made of 99.98% Al was used during calibration to compensate for artifacts from beam hardening. They found that the mineral densities of normal and carious deciduous dentin observed were comparable to data obtained by SRµCT (Kinney et al., 1994). Although CµCT has its disadvantages compared to SRµCT, these limitations did not compromise its performance in trabecular bone evaluation and was consider as effective as SRµCT in certain experimental groups (Chappard et al., 2006). The use of step-wedge calibration to convert polychromatic x-ray beams to a monochromatic x-ray source has been found to be as effective as using SRµCT (Willmott et al., 2007). Summary of previous literature Current knowledge Enamel is known to have reliable bond strength when bonded to RBC since its main components are inorganic, while dentin has different composition and structure. Dentin is more hydrophilic in nature compared to enamel and thus, it is more difficult to deal with in terms of bonding to adhesive resin. From studies mentioned previously, it was demonstrated that µtbs of current adhesives, especially 3-step etch-and-rinse adhesives have a good performance both in vitro (Armstrong et al., 2003; De Munck et al., 2003; De Munck et al., 2005) and in clinical studies (Peumans et al., 2005). Most studies agreed that 1-step self-etch adhesives have unsatisfactory performance (Armstrong et al., 2003; De Munck et al., 2005; Peumans et al., 2005). Overall, 3-step

42 29 etch-and-rinse adhesives proved to have satisfactory µtbs, but in long term, the dentin bond interface degrades over time (De Munck et al., 2003). As explained by a 15 month water storage study that found no difference in µtbs between 3-step etch-and-rinse adhesives, 2-step etch-and-rinse adhesives, and 2-step self-etch adhesives after long term water storage (Armstrong et al., 2003). This resin-dentin interface degradation was partially explained by phase separation of adhesive resin and collagen degradation (De Munck et al., 2003). Several studies have shown that the ethanol wet-bonding technique, with the use of hydrophobic resins may have an advantage over the current 3-step etch-and-rinse adhesives using a water wet-bonding technique (Nishitani et al., 2006; Hosaka et al., 2009). Those hydrophobic resins provide favorable results in vitro in terms of the µtbs and SEM ultrastructural evaluation, and they have the ability to better resist water degradation, or hydrolysis, over time. However, as this is a relatively new concept, further investigation is needed. In clinical practice, dental caries is the most common tooth pathology that leads to restoration. Resin composite is among the most common used direct filling materials since it provides an excellent esthetic result and preserves existing tooth structure. Moreover, it can be bonded to tooth structure with resin adhesives, which are believed to provide a better seal between tooth and restoration. After carious dentin has removed, the demineralized dentin or CAD underneath the caries remains and as such this substrate is what dentists work with most of the time. Therefore, understanding the nature and mechanism of adhesion of CAD is very important. It has been shown that µtbs of CAD is lower than that of normal dentin (Ceballos et al., 2003; Erhardt et al., 2008). Moreover, Wang et al (Wang et al., 2007) concluded that there was evidence of distinct differences in the depth of dentin demineralization and degree of adhesive infiltration in non-carious and CAD. It was shown that the interface between the adhesive and CAD was wider and more complicated than that of the adhesive and non-carious dentin. Because of the

43 30 structural alteration and porosities in CAD, deeper demineralized layers occurred. The deeper the demineralized collagen, the poorer resin can incorporate into the deepest part of the layer. This resulted in phase separation of resin adhesives and lowered the bond strength. Gaps in knowledge Many studies investigated bond strength of CAD and compared it with that of normal dentin. Studies have explained how CAD results in the low bond strength in terms of dentin's chemistry and microstructure. The Knoop microhardness of CAD was also described as being related to the bond strength, as the low Knoop microhardness, compared to that of normal dentin, results in low µtbs. Although many attempts were made to investigate the bond strength of CAD compared to normal dentin, no studies have ever related the degree of mineral density of CAD to the µtbs of CAD. To overcome the problem of weak bonding of CAD, understanding the basic knowledge of nature of the substrate is very important. Knowing the relationship between the degree of mineral density of CAD and its µtbs will help improve the further studies and relate the basic knowledge to clinical practice. It may serve as a guideline to the dentist for adequate caries removal before adhesive restoration and might eventually lead to a consensus of effective caries removal for the advancement of minimally invasive restorative dentistry.

44 31 Figure 1. SEM photomicrograph of enamel (original magnification 60000x), showing enamel rods Figure 2. SEM photomicrograph of dentin (original magnification 11000x), showing peritubular dentin and dentinal tubule

45 32 Figure 3. SEM photomicrograph of intertubular dentin (original magnification 30000x), showing collagen fibers and hydroxyapatite crystals Figure 4. SEM photomicrograph of dentin near dentin-enamel junction (DEJ) (original magnification 1100x), showing dentinal tubules at the level close to DEJ

46 33 Figure 5. SEM photomicrograph of dentin near pulp (original magnification 1100x), showing greater number of dentinal tubules at the level close to pulp when compared to superficial dentin Figure 6. SEM photomicrograph of CAD (original magnification 12000x), showing turbid zone

47 34 Figure 7. SEM photomicrograph of CAD (original magnification 35000x), showing mineral occlusion in dentinal tubule in CAD Figure 8. SEM photomicrograph of CAD (original magnification 50000x), showing Whitlockite crystals in transparent zone

48 35 Figure 9. SEM photomicrograph of CAD (original magnification 30000x), showing Whitlockite crystals in dentinal tubules in transparent zone Figure 10. SEM photomicrograph of CAD (original magnification 35000x), showing plate-like crystals in subtransparent zone

49 36 Figure 11. RBC development and classification based on filler size particles (Ferracane, 2011) Figure 12. Classification of contemporary adhesives by type and number of clinical application steps (GI = glass ionomer; PAA = polyalkenoic acid) (Van Meerbeek et al., 2003)

50 Figure 13. Experimental design of µtbs testing (De Munck et al., 2005) 37

51 38 CHAPTER 3 METHODOLOGY Introduction This chapter will describe the methodology of the research design which includes research question, hypotheses, operational definitions used in this study, population and samples in terms of how the samples were obtained, detailed protocol in specimen preparation and µtbs testing. The data management and analysis will also be included in this chapter. Since there is a gap in the published literature as to whether there is an association between CAD s physical and mechanical properties (mineral density) and its bond strength (µtbs). The purpose of this study was to determine the relationship between µtbs of CAD and the degree of mineral density of CAD. The experimental group consisted of specimens with CAD bonded with RBC using the wet-bonding technique. The control group consisted of specimens with normal dentin bonded to RBC using the same wet-bonding technique. All the teeth were bonded to the same RBC (Z100, shade A1, 3M ESPE, Germany). The adhesive used in this study was Optibond FL (Kerr, Orange, CA, USA), a commercial 3-step etch-and-rinse adhesive. After the bonding procedure, the µtbs of these two groups was then compared. Each specimen was processed for mineral density measurement after µtbs test. The mean mineral density of specimens was calculated using Bone Mineral Density (BMD) software (P. Saha & G. Liang, Iowa City, IA, USA). Since the µtbs is difficult to determine in clinical situations with human subjects and for ethical reasons, an in vitro design was used for this study.

52 39 Research question Is the bond strength of CAD related to its degree of mineralization? Specific aim Test the hypothesis that there is a direct relationship between CAD s degree of mineralization (image intensity) and µtbs. Research hypotheses Null hypotheses (H 0 ) H 0 1: µtbs is unrelated to image intensity at slice 1. H 0 2: µtbs is unrelated to image intensity at the average of slices 1&2. H 0 3: µtbs is unrelated to image intensity (slice 1) of CAD (type 2). H 0 4: µtbs is unrelated to image intensity (slices 1&2) of CAD (type 2). H 0 5: µtbs is unrelated to image intensity (slice 1) of normal dentin (type 1). H 0 6: µtbs is unrelated to image intensity (slices 1&2) of normal dentin (type 1). H 0 7: Failure mode is unrelated to image intensity at slice 1. H 0 8: Failure mode is unrelated to image intensity at the average of slices 1& 2. H 0 9: Failure mode is unrelated to image intensity (slice 1) of CAD (type 2). H 0 10: Failure mode is unrelated to image intensity (slices 1&2) of CAD (type 2). H 0 11: Failure mode is unrelated to image intensity (slice1) of normal dentin (type 1). H 0 12: Failure mode is unrelated to image intensity (slices 1&2) of normal dentin (type 1). H 0 13: Failure mode is unrelated to µtbs of all specimens (types 1&2). H 0 14: Failure mode is unrelated to µtbs of CAD (type 2). H 0 15: Failure mode is unrelated to µtbs of normal dentin (type 1).

53 40 H 0 16: Level of dye staining is unrelated to image intensity (slice 1) and therefore unrelated to µtbs, failure mode and SEM morphology. H 0 17: Level of dye staining is unrelated to image intensity (slices 1&2) and therefore unrelated to µtbs, failure mode and SEM morphology. Alternative hypotheses (H A ) H A 1: There is a direct relationship (linear or nonlinear) between μtbs of CAD and the degree of mineralization (image intensity) of CAD. H A 2: CAD with lower degree of mineralization (image intensity) is related with apparently adhesive and mixed failure mode. H A 3: CAD with lower μtbs is associated with apparently adhesive and mixed failure mode. H A 4: CAD with more intense stain is associated with its low image intensity and therefore associated with low μtbs, failure mode in apparently adhesive or mixed group, and ultrastructure showing demineralized dentin from SEM analysis. Operational Definitions Caries: a multifactorial, transmissable, infectious oral bacterial disease characterized by demineralized tooth tissue typically exhibiting yellowish to brownish discoloration. CAD: the remaining light pink to brown stained dentin obtained after infected caries was removed with spoon excavator and round bur at slow speed and then stained for 10 seconds with Caries Detector (Kuraray Medical, Tokyo, Japan). Specimen: resin - dentin dumbbell shape, 0.8 mm in diameter at the junction between dentin and resin, ~ 8-10 mm in height Resin adhesive: bonding material that binds the dentin and RBC by mechanical interlocking. (In this research, it implies to Optibond FL, Kerr, Orange, CA, USA)

54 41 Resin - dentin interface: the junction which RBC meets normal or CAD. Wet-bonding: the technique of dentin bonding that leaves the dentin surface moist (after acid etching step and rinse with water) before the primer application. µct (Micro-CAT II, Siemens Preclinical solutions, Knoxville, TN): the smallscale computed tomography scanner which can indirectly read the degree of mineral deposition in dentin. Degree of mineral density of resin-dentin interface: the mean dentin mineral apposition at the junction between dentin and RBC as measured by µct. Population & Sample Population: A total of sixty-three extracted human molars were randomly selected and were obtained from the Oral Surgery department, College of Dentistry, The University of Iowa. Fifty-four out of sixty-three teeth were extracted human molars with carious lesions extending into dentin, the remaining nine human molars were sound. Samples: Two hundred and six samples were obtained from sixty-three extracted teeth (180 samples from carious teeth and 26 samples from sound teeth). After the teeth were cut to remove occlusal enamel and dentin, they were then bonded to RBC using resin adhesive as a bonding agent. In CAD group, the infected carious dentin was removed before the bonding process. Each bonded tooth was sectioned up to 4 sticks (2 x 2 x ~ 6 mm) and dumbbell-shaped specimens were then prepared for µtbs testing. Study design Specimen preparation Sixty-three extracted human molars with and without carious lesions, that cannot be identified to any individual (IRB exempt), are collected and stored in PBS with 0.5% chloramine T at 4 C and used within 6 months of extraction. These teeth are flattened with a 600-grit wheel model trimmer (3/4HP Wet Model Trimmer, Whip Mix

55 42 Corporation, Louisville, KY, USA) to partially remove occlusal enamel and expose the dentin. Caries is removed in CAD teeth with the aid of Caries Detector (Kuraray Medical, Tokyo, Japan). After staining CID with Caries Detector for 10 seconds (as manufacturer s instruction), the heavy pink stained CAD is removed with spoon excavator and round burs at slow speed leaving a light pink stained dentin that is firm to explorer, spoon excavator and low speed round bur application using conventional subjective clinical procedures. The teeth were then flattened by CNC Specimen forming machine (University of Iowa, Iowa City, IA, USA) to create a flat dentin surface which was perpendicular to the vertical axis leaving the remaining dye-stained CAD. After flattening with CNC former, they were then bonded with RBC (Z100, shade A1, 3M ESPE, Germany) using an etch-and-rinse 3-step adhesive system (Optibond FL, Kerr, Orange, CA). Acid-etching is accomplished with 35% phosphoric acid (Ultra-Etch, Ultradent, South Jordan, UT, USA) applied to the dentin surface for no longer than 15 s to remove mineral and expose collagen fiber before rinsing for s. Lint-free absorbent paper (Kimwipe) is used to remove excess water leaving a moist dentin surface. Primer is then applied on dentin surface with a microbrush and left for 20 s before drying with an oil- and water-free air syringe at 20 psi. The adhesive is then applied with a microbrush in an even non-excessive layer before light curing (Optilux 500, Demetron/Kerr, Danbury, CT, USA) for 20 s from within 1 mm of the surface. The RBC buildup procedure is accomplished using an incremental technique with each increment no greater than 2 mm-thick and individually light cured for 40 seconds with the same curing unit. Radiant emmittance of the curing unit is no less than 500 mw/cm 2 as measured with a radiometer in the wavelength range of nm (Curing Radiometer model 100, Demetron Research Corp., Danbury, CT, USA). The curing unit spectral exitance emission (mw/nm), exitance radiance (mw/cm 2 ), an indication of how the power is distributed across the light guide tip (top hat factor), and verification of power levels using proposed curing sequences was predetermined to ensure that

56 43 manufacturer s recommendations for curing time can be followed without compromising adhesive and RBC polymerization (Rueggeberg lab, Medical College of Georgia). The bonded teeth are then stored overnight at 37ºC in 100% humidity before further specimen fabrication. The following day each bonded tooth is vertically sectioned into up to 4 sticks (2 x 2 x ~ 6 mm), depending upon the available CAD bonding area. Sectioning is accomplished with water-lubricated low-speed diamond saw blades (IsoMet 1000, Buehler Ltd., Lake Bluff, IL, USA) separated by 2 mm spacers using a cutting speed of 125 rpm and the application of a 150 g weight with two sections at right angles to one another. The sticks are then trimmed with a 0.8 micron, ultrafine cylindrical diamond bur (#012, Brasseler, Savannah, Georgia, USA) in the CNC Specimen Former (University of Iowa, Iowa City, IA) into dumbbell-shaped tensile test specimens with a round crosssectional area of 0.5 mm 2, a gauge length of 1 mm, and a radius of curvature or neck of 0.6 mm. These are examined under a stereomicroscope at 50X magnification (Stemi 2000, Zeiss, NY, USA) to verify proper fabrication. The diameter of each specimen is measured with a digital caliper (Digimatic caliper, Mitutoyo Corporation, Japan) to ± 0.01 mm. (See appendix for detailed protocol for specimen preparation.) µtbs testing Tensile testing is performed at a crosshead speed of 1 mm/min with a calibrated material testing machine (Zwick Materials Testing Machine Z2.5/TN1S, Zwick, Ulm, Germany) and testxpert software. The specimen is gripped centrally with respect to the test axis with a non-gluing passive gripping device (Dircks Device, The University of Iowa, Iowa city, IA, USA). Only those specimens that fractured within the test region (gauge area) are included for analysis. Mineral density measurement The fractured specimens are placed within a custom polystyrene (density = 1.05) specimen holders and sealed within a glass jar with anhydrous calcium sulfate (Drierite,

57 44 Fisher Scientific, Chicago, IL) until fully desiccated. Gravimetric pilot studies were used to confirm desiccation protocol. Desiccation is required to minimize signal attenuation during µct mineral density measurements (Micro-CAT II, Siemens Preclinical Solutions, Knoxville, TN). A Styrofoam holder was created for mounting the specimens for mineral density measurement. The Styrofoam was a 1.0 cm-tall cylinder 3 cm in diameter designed to fit in 4 x 4 cm beam field of µct scanner. The specimens were placed in 1 cm area located at the center of the cylinder Styrofoam to achieve the best scanning resolution. Each holder contained 10 holes for placing specimens, 5 holes per side (top and bottom side). These 5 holes were placed symmetrically in the center to evenly distribute the beam attenuation. The fractured specimens are placed between the x-ray source (35-80 kvp) and the detector (2048 x 3096 pixels). Scanning is performed at maximum resolution (pixel size) of 27 microns. The mean mineral densities are calculated from the serial scanned images at the resin-dentin interface of the bonded specimens and proceeding away from the interface using custom BMD analyzer software. Image intensity (unitless) will be plotted against µtbs (MPa) to determine correlation between these two properties. The custom BMD analyzer software is the program that has been developed in Radiology laboratory, University of Iowa (P. Saha & G. Liang), which generates the BMD profile along the central axis of tooth specimens along the interface. The software is developed using QT user interface tools and ITK Library under LINUX operating system. The software directly leads µct images of an assembly of specimens and allows users to select each individual specimen separately for BMD analysis. The software automatically corrects the orientation misalignment of the specimens and identifies the central line along the long axis of the specimens. Finally, it outputs the BMD values

58 45 along the central line; special cases are taken to reduce the effect of noise within the relative limited resolution regime. Fracture Mode Analysis by Scanning Electron Microscopy (SEM) After tensile testing and µct scanning were performed, the fractured specimens were mounted on stubs and viewed with SEM (Hitachi S4800, Central Microscopy Research Facility, EMRB, University of Iowa) for fracture mode verification. According to ultrastructure of resin-dentin interface, specimens which failed cohesively in resin composite or in dentin would be classified as cohesive in resin composite and cohesive in dentin respectively. For those where fracture located at the joint or adhesive layer, they would be classified as apparently adhesive. Any combination of at least two substrates would be classified as mixed group. (Figure 14) Statistical Analysis A total of 206 specimens were included in statistical analysis to determine whether there was a direct relationship between µtbs, degree of mineralization (image intensity), and mode of failure. In this study, each of the total 206 samples was considered independent sample. Spearman s rank correlation test was used to determine if there was a statistically significant relationship between µtbs and image intensity under difference conditions (all teeth, CAD, and normal teeth). The strength of the relationship between µtbs and image intensity was evaluated based on the absolute value of the Spearman s rank correlation coefficient. To assess the impact of modes of failure on the image intensity and on the µtbs, one-way ANOVA was conducted. Shapiro-Wilk test was used to verify the assumption of normality before analyzing the data with one-way ANOVA. Given that the assumption of normality was violated, the rank transformation would be conducted. Subsequently, oneway ANOVA based on ranked data, an equivalent to non-parametric Kruskal-Wallis test,

59 46 followed by post-hoc Bonferroni test was then performed. In case if the assumption of normality was valid, one-way ANOVA followed by post-hoc Tukey-Kramer test would be conducted. In addition, to describe the relationship between levels of dye staining and image intensity, the nonparametric Wilcoxon rank-sum test was used to determine whether there was a statistically significant difference in the mean image intensity between the 2 levels of dye staining. To evaluate the effect of 3 levels of dye staining on image intensity, data were analyzed using the Shapiro-Wilk test to verify the assumption of normality. If the assumption of normality was violated, the rank transformation was conducted. One-way ANOVA based on ranked data was then performed. In case if the assumption of normality was valid, one-way ANOVA followed by post-hoc Tukey-Kramer test would be conducted. To assess the measurement reliability, intraclass correlation was computed as a measure of agreement between the first and second or first and third or second and third measurements which were made by a single-observer. The same procedure was also used for evaluation of an agreement between two observers. The following is an approximate guide for interpreting an agreement between two measurements that corresponds to an intraclass correlation coefficient. 1 = perfect agreement 0.8 = strong agreement 0.5 = moderate agreement 0.2 = weak agreement 0 = no agreement Image intensity will be plotted against µtbs (MPa) to describe correlation based on Spearman rank correlation test. All tests employed at 0.05 level of statistical significance. Statistical analyses were carried out with the statistical package SAS System version 9.2 (SAS Institute Inc, Cary, NC, USA).

60 47 Table 1. List of products used in sample preparation process Product Component Batch Number Caries Detector Optibond FL: Primer Adhesive Manufacturer >90% propane-1,2-diol, dyes 0721C Kuraray Medical 25-30% Hydroxyethyl methacrylate (HEMA), 20-25% Ethyl alcohol 15-20% Hydroxyethyl methacrylate (HEMA), 1-2% Disodium hexafluorosilicate, Uncured methacrylate ester monomers and inert fillers Kerr Corporation Kerr Corporation Ultra-Etch 35% Phosphoric acid solution B3M8M Ultradent Products, Inc. Z100, shade A % by Wt silane treated ceramic, 1-10% bisphenol A diglycidyl ether dimethacrylate (BISGMA), 1-10% Triethylene glycol dimethacrylate (TEGDMA), <1% 2- Benzotriazolyl-4-methylphenol Usage purpose Caries removal Bonding Bonding Dentin conditioning 5905A1 3M ESPE Composite Built-up Figure 14. SEM observation of resin-dentin interface

61 48 Mount teeth in stone block Caries removal using round tungstein carbide bur with the aid of Caries Detector dye (This step was skipped in normal dentin) flatten and 2nd stain (all samples) with Caries Detector then proceeded to RBC build-ups Stored over night (24 hours) Sectioned up to 4 sticks per tooth Trimmed to dumbbells µtbs testing µct scanning for image intensity determination Failure mode analysis by SEM Figure 15. Summary of methods (details described in Figure 16-18)

62 49 Figure 16. Steps in CAD specimen preparation Figure 17. Steps in normal dentin specimen preparation

63 50 Figure 18. Steps in specimen preparation for µtbs test, µct and SEM Figure 19. Resin-dentin interface from different specimens' fracture pattern and mineral density measurement at the resin-dentin interface. Blue arrow indicates direction of image intensity measurements starting from adhesive interface, that is, slice 1, slice 2, etc.

64 51 CHAPTER 4 RESULTS Introduction A total of 206 specimens were included in the statistical analysis to determine whether there was a significant relationship between µtbs and image intensity, and to assess whether there was a significant effect of mode of failure on µtbs and image intensity. Statistical results are presented based on the 4 major parts according to Null hypotheses tested. The first part reports a relationship between µtbs and the image intensity as stated in Null hypotheses 1-6 (H 0 1-H 0 6). The second part describes a relationship between mode of failure and image intensity (H 0 7-H 0 12). The relationship between µtbs and failure mode will be described in the third part (H 0 13-H 0 15). Lastly, the relationship between level of dye staining and image intensity will be reviewed (H 0 16-H 0 17). First, measurement reliability was evaluated. A paired sample t-test was first performed to determine whether there was a significant difference in image intensity measurements made on the same specimens between two persons (SV, SA) for all 9 variables, which were; (1) slice -1, (2) slice 0, (3) slice 1, (4) slice 2, (5) slice 3, (6) average of slices 1-2, (7) average of slices 1-3, (8) average of slices 1-4, and (9) average of slices 1-5, using BMD software. In addition, intraclass correlation was calculated as a measure of agreement between the first and second observer on image intensity determination for all nine variables and for each variable. An intrareliability was also evaluated to determine if there was consistent image intensity measurement from a single-observer using the same statistical procedures. The following is an approximate guide for interpreting an agreement between two measurements that corresponds to an intraclass correlation coefficient. 1 = perfect agreement

65 = strong agreement 0.5 = moderate agreement 0.2 = weak agreement 0 = no agreement Based on the paired-sample t-test, the data revealed that there was no statistically significant difference in measurements between two persons for all of 9 variables (p>0.05). Moreover, data showed that intraclass coefficient was significantly different from zero (p<0.0001), and intraclass coefficient of 0.93 indicated a very strong agreement between two persons for all 9 variables. When considering each variable separately, the intraclass coefficients ranged from 0.88 to 0.98 indicated strong agreement between the two observers for each variable. Intraclass coefficients are as follows: Slice -1 = 0.98 (strong agreement), p < Slice 0 = 0.95 (strong agreement), p = Slice 1 = 0.92 (strong agreement), p = Slice 2 = 0.89 (strong agreement), p = Slice 3 = 0.88 (strong agreement), p = Average of Slices 1-2 = 0.91 (strong agreement), p = Average of Slices 1-3 = 0.92 (strong agreement), p = Average of Slices 1-4 = 0.90 (strong agreement), p = Average of Slices 1-5 = 0.92 (strong agreement), p = Considering intrareliability, there was very strong evidence that the intraclass correlations differed from zero in each instance (p < ), and intraclass correlation coefficients indicated nearly perfect agreement between the three measurements of image intensity slice 1 with a single-observer. The intraclass correlation coefficients were 0.98 between first and second measurements, 0.99 between first and third measurements, and 0.99 between second and third measurements.

66 53 A p-value of less than 0.05 was used as a criterion for statistical significance. Statistical analyses were carried out with the statistical package SAS System version 9.2 (SAS Institute Inc, Cary, NC, USA). Part 1: µtbs vs. image intensity A total of 206 specimens were included in the study. Spearman s rank correlation test was used to determine if there was a statistically significant relationship between µtbs and image intensity under difference conditions (all teeth, CAD, and normal teeth). Descriptive statistics of µtbs and image intensity for all specimens are summarized in Table 2. The following is an approximate guide for interpreting the strength of the relationship between two variables (µtbs and image intensity), based on the absolute value of the Spearman s rank correlation coefficient: ± 1 = perfect correlation ± 0.8 = strong correlation ± 0.5 = moderate correlation ± 0.2 = weak correlation ± 0.00 = no correlation Statistical results H 0 1: Assessment of the relationship between μtbs and image intensity of slice1 for all teeth (n = 206) Base on the Spearman correlation test, there was an apparently significant increasing relationship between µtbs and image intensity of slice1 for all teeth (p < ). The Spearman s rank correlation coefficient of 0.31 indicated a weak positive correlation between the two variables (Table 4). H 0 2: Assessment of the relationship between μtbs and average image intensity of slices 1 and 2 for all teeth (n = 206)

67 54 Base on the Spearman correlation test, there was an apparently significant increasing relationship between µtbs and the average image intensity of slices 1 and 2 for all teeth (p < ). The Spearman s rank correlation coefficient of 0.29 indicated a weak positive correlation between the two variables (Table 4). H 0 3: Assessment of the relationship between μtbs and image intensity of slice1 for CAD (n = 180) Base on the Spearman correlation test, there was an apparently significant increasing relationship between μtbs and image intensity of slice1 for CAD (p < ). The Spearman s rank correlation coefficient of 0.42 indicated a weak positive correlation between the two variables (Table 4). H 0 4: Assessment of the relationship between μtbs and average image intensity of slices 1 and 2 for CAD (n = 180) Base on the Spearman correlation test, there was an apparently significant increasing relationship between μtbs and the average image intensity of slices 1 and 2 for CAD teeth (p < ). The Spearman s rank correlation coefficient of 0.40 indicated a weak positive correlation between the two variables (Table 4). H 0 5: Assessment of the relationship between μtbs and image intensity of slice1 for normal teeth (n = 26) Base on the Spearman correlation test, there was no significant relationship between μtbs and image intensity of slice1for normal teeth, p = (Table 3). H 0 6: Assessment of the relationship between μtbs and average image intensity of slices 1 and 2 for normal teeth (n = 26) Base on the Spearman correlation test, there was no significant relationship between μtbs and the average image intensity of slices 1 and 2 for normal teeth, p = (Table 4).

68 55 Part 2: failure mode vs. image intensity A total of 206 specimens were included in the study. The data were analyzed using the Shapiro Wilk test to verify the assumption of normality. Given that the assumption of normality was violated, the rank transformation would be conducted. Oneway ANOVA based on ranked data (equivalent to non-parametric Kruskal-Wallis test) followed by post-hoc Bonferroni test was then performed to determine if there was a significant effect of failure mode on the image intensity. Descriptive statistics of image intensity by failure modes are summarized in Table 5. Statistical results H 0 7: Detecting a difference in image intensity of slice 1 among the failure modes for all teeth (n = 206) Since the assumption of normality was violated, the rank transformation was conducted. One-way ANOVA based on ranked data was performed to analyze the data. Results revealed that there was a significant effect of the failure modes on the image intensity of slice 1 for all teeth (p < ). The post-hoc Bonferroni test indicated that the mean rank scores of image intensity of slice 1 observed in cohesive in dentin and cohesive in RBC were significantly greater than those observed in mixed and apparently adhesive locations, while no significant differences were found between cohesive in dentin and cohesive in RBC, and between mixed and apparently adhesive groups (Table 6). H 0 8: Detecting a difference in the average image intensity of slices 1 and 2 among the failure modes for all teeth (n = 206) Since the assumption of normality was violated, the rank transformation was conducted. One-way ANOVA based on ranked data was performed to analyze the data. Results revealed that there was a significant effect of the failure modes on the average image intensity of slices 1 and 2 for all teeth (p < ). The post-

69 56 hoc Bonferroni test indicated that the mean rank scores of average image intensity of slices 1 and 2 observed in cohesive in dentin and cohesive in RBC were significantly greater than those observed in mixed and apparently adhesive groups, while no significant differences were found between cohesive in dentin and cohesive in RBC, and between mixed and apparently adhesive groups (Table 7). H 0 9: Detecting a difference in image intensity of slice 1 among the failure modes for CAD (n = 180) Since the assumption of normality was violated, the rank transformation was conducted. One-way ANOVA based on ranked data was performed to analyze the data. Results revealed that there was a significant effect of the failure modes on the image intensity of slice 1 for CAD (p < ). The post-hoc Bonferroni test indicated that the mean rank scores of image intensity of slice 1 observed in cohesive in dentin and cohesive in RBC were significantly greater than those observed in mixed and apparently adhesive groups, while no significant differences were found between cohesive in dentin and cohesive in RBC, and between mixed and apparently adhesive groups (Table 8). H 0 10: Detecting a difference in the average image intensity of slices 1 and 2 among the failure modes for CAD (n = 180) Since the assumption of normality was violated, the rank transformation was conducted. One-way ANOVA based on ranked data was performed to analyze the data. Results revealed that there was a significant effect of the failure modes on the average image intensity of slices 1 and 2 for CAD (p < ). The post-hoc Bonferroni test indicated that the mean rank scores of average image intensity of slices 1 and 2 observed in cohesive in dentin and cohesive in RBC were significantly greater than those observed in mixed and apparently adhesive groups, while no significant differences were found between cohesive in dentin

70 57 and cohesive in RBC, and between mixed and apparently adhesive groups (Table 9). H 0 11: Detecting a difference in image intensity of slice 1 among the failure modes for normal teeth (n = 26) Since the assumption of normality was violated, the rank transformation was conducted. One-way ANOVA based on ranked data was performed to analyze the data. Results revealed that there was a significant effect of the failure modes on the image intensity of slice 1 for normal teeth (p < ). The post-hoc Bonferroni test indicated that the mean rank score of image intensity of slice 1 observed in cohesive in dentin was significantly greater than those observed in apparently adhesive and mixed groups, while no significant difference was found between apparently adhesive and mixed groups (Table 10). No cohesive in RBC was observed in normal dentin. H 0 12: Detecting a difference in the average image intensity of slices 1 and 2 among the failure modes for normal teeth (n = 26) Since the assumption of normality was violated, the rank transformation was conducted. One-way ANOVA based on ranked data was performed to analyze the data. Results revealed that there was a significant effect of the failure modes on the average image intensity of slices 1 and 2 for normal teeth (p < ). The post-hoc Bonferroni test indicated that the mean rank score of average image intensity of slices 1 and 2 observed in cohesive in dentin was significantly greater than those observed in apparently adhesive and mixed groups, while no significant difference was found between apparently adhesive and mixed groups (Table 11). No cohesive in RBC was observed in normal dentin.

71 58 Part 3: µtbs vs. failure mode A total of 206 specimens were included in the study. The data were analyzed using the Shapiro-Wilk test to verify the assumption of normality. Given that the assumption of normality was valid, one-way ANOVA followed by post-hoc Tukey- Kramer test would be conducted to determine if there was a statistically significant relationship between failure mode and µtbs under difference conditions (all teeth, CAD, and normal teeth). Descriptive statistics of image intensity by failure modes are summarized in Table 12. Statistical results H 0 13: Detecting a difference in the µtbs among the failure modes for all teeth (n = 206) Data were analyzed using the Shapiro-Wilk test to verify the assumption of normality. Since the assumption of normality was valid, one-way ANOVA followed by post-hoc Tukey-Kramer test was conducted to analyze the data. Results revealed that there was a significant effect of the failure modes on the µtbs for all teeth (p < ). The post-hoc Tukey-Kramer test indicated that the mean µtbs observed in cohesive in dentin was significantly greater than those observed in mixed and apparently adhesive groups, while no significant differences were found between cohesive in dentin and cohesive in RBC, between cohesive in RBC and mixed, and between mixed and apparently adhesive groups (Table 13). H 0 14: Detecting a difference in the µtbs among the failure modes for CAD (n = 180) Data were analyzed using the Shapiro-Wilk test to verify the assumption of normality. Since the assumption of normality was valid, one-way ANOVA followed by post-hoc Tukey-Kramer test was conducted to analyze the data. Results revealed that there was a significant effect of the failure modes on the µtbs for CAD (p < ). The post-hoc Tukey-Kramer test indicated that the

72 59 mean µtbs observed in cohesive in dentin was significantly greater than those observed in mixed and apparently adhesive groups, while no significant differences were found between cohesive in dentin and cohesive in RBC, between cohesive in RBC and mixed, and between mixed and apparently adhesive groups (Table 14). H 0 15: Detecting a difference in the µtbs among the failure modes for normal teeth (n=26) Data were analyzed using the Shapiro Wilk test to verify the assumption of normality. Since the assumption of normality was valid, one-way ANOVA followed by post-hoc Tukey-Kramer test was conducted to analyze the data. Results revealed that there was no significant effect of the failure modes on the µtbs for normal teeth (p = ). That is, no significant difference among failure modes in the µtbs for normal teeth was found (Table 15). Part 4: Level of dye staining vs. image intensity A total of 206 specimens were included in the study. The data were analyzed using the Shapiro-Wilk test to verify the assumption of normality. Given that the assumption of normality was violated, the rank transformation was conducted. One-way ANOVA based on ranked data, an equivalent to non-parametric Kruskal-Wallis test, followed by post-hoc Bonferroni test was then performed to determine if there was a significant effect of the 3 levels of dye staining on the image intensity. Nonparametric Wilcoxon rank-sum test was used to assess whether there was a significant effect of the 2 levels of dye staining on the image intensity. Descriptive statistics of image intensity by two (level 5 & 6 & 7 vs. 8) and three levels (level 5 & 6 vs. 7 vs. 8) of dye staining are summarized in Table 16. Description of levels of dye staining is as follows. These codes were classified into 8 different levels according to the observer s ability to distinguish

73 60 between codes ten times without an error. In our findings, only level 5 8 were observed in stained specimens. Level 1: 100% dye (n = 0) Level 2: 50% dye (n = 0) Level 3: 10% dye (n = 0) Level 4: 9% dye (n = 0) Level 5: 8% dye (n = 16) Level 6: 1% dye (n = 17) Level 7: 0.2% dye (n = 17) Level 8: 0% dye (n = 156) Since samples observed in code 5, 6, and 7 were relatively small, some codes were combined for a more power to discriminate between codes as follows. Two levels Code 5-7 = stain (n = 50) Code 8 = no stain (n = 156) Three levels Code 5-6 = pink-stained (n = 33) Code 7 = light pink-stained (n = 17) Code 8 = no stain (n = 50) Statistical results H 0 16: Detecting a difference in image intensity of slice 1 among the levels of dye staining for all teeth (n = 206) Two levels of dye staining (level 5-7 vs. 8) Based on the nonparametric Wilcoxon rank-sum test, no significant difference in the mean image intensity of slice 1 was found between the 2 levels of dye staining (p = ) (Figure 26).

74 61 Three levels of dye staining (level 5-6 vs. 7 vs. 8) Data were analyzed using the Shapiro-Wilk test to verify the assumption of normality. Since the assumption of normality was violated, the rank transformation was conducted. One-way ANOVA based on ranked data was then performed. Results revealed that there was no significant effect for the level of dye staining on the image intensity of slice 1 (p = ). No significant difference in the image intensity of slice 1 was found among three levels of dye staining (Table 17 and Figure 27). H 0 17: Detecting a difference in average image intensity of slices 1 and 2 among the levels of dye staining for all teeth (n = 206) Two levels of dye staining (level 5-7 vs. 8) Based on the nonparametric Wilcoxon rank-sum test, no significant difference in the mean image intensity of slices 1 and 2 was found between the 2 levels of dye staining (p = ) (Figure 28). Three levels of dye staining (level 5-6 vs. 7 vs. 8) Data were analyzed using the Shapiro-Wilk test to verify the assumption of normality. Since the assumption of normality was violated, the rank transformation was conducted. One-way ANOVA based on ranked data was then performed. Results revealed that there was no significant effect for the level of dye staining on the image intensity of slices 1 and 2 (p = ). No significant difference in the average image intensity of slices 1 and 2 was found among three levels of dye staining (Table 18 and Figure 29). Failure mode analysis Of all 206 specimens, the majority of specimens (58%) failed cohesively in dentin, followed by mixed (27%), apparently adhesive (10%), and cohesive in RBC (5%) (Figure 30). Likewise, failure mode analysis in CAD revealed a similar manner. Failure

75 62 occurred most cohesively in dentin (58%), mixed (27%), apparently adhesive (9%), and cohesive in RBC respectively (6%) (Figure 31). In normal teeth, failure locations were most located cohesively in dentin (62%), followed by mixed (27%), and apparently adhesive (11%). No failure found cohesively in RBC (Figure 32). Table 2. Descriptive statistics of selected variables in the study for all specimens (n = 206) Variables N Mean Median Standard Deviation Minimum Maximum µtbs Image intensity slice Average image intensity of slices 1 and Table 3. Descriptive statistics of selected variables in the study for all specimens (n = 206), CAD (n = 180), and normal dentin (n = 26) by including and excluding apparently adhesive and mixed failures Overall Variables N µtbs (MPa) Image intensity slice 1 Average image intensity of slices 1 and 2 Mean of all failure modes Mean of apparently adhesive group Mean of mixed group CAD Mean of all failure modes Mean of apparently adhesive group Mean of mixed group and Normal dentin Mean of all failure modes Mean of apparently adhesive group Mean of mixed group

76 63 Table 4. Correlation between µtbs and image intensity Variables Correlation Coefficients p-value* µtbs vs. image intensity of slice1 (all teeth) 0.31 < ** µtbs vs. average image intensity of slices 1 and 2 (all teeth) 0.29 < ** µtbs vs. image intensity of slice1 (CAD) 0.42 < ** µtbs vs. average image intensity of slices 1 and 2 (CAD) 0.40 < ** µtbs vs. image intensity of slice1 (normal teeth) µtbs vs. average image intensity of slices 1 and 2 (normal teeth) *Significance probability is associated with correlation between two variables. ** A significant correlation existed between two variables.

77 Normal teeth (n = 26) CAD (n = 180) All teeth (n = 206) 64 Table 5. Descriptive statistics of image intensity by failure modes for all specimens (n = 206) Failure mode N Image intensity slice 1 Average image intensity of slices 1 and 2 Cohesive in dentin Cohesive in RBC Apparently adhesive Mean Median Standard deviation Minimum Maximum Mean Median Standard deviation Minimum Maximum Mixed Cohesive in dentin Cohesive in RBC Apparently adhesive Mixed Cohesive in dentin Apparently adhesive Mixed

78 65 Table 6. Mean image intensity of slice 1 by failure modes for all teeth (n = 206) Failure modes Mean image intensity of slice 1 (mean rank scores) Multiple - group comparison* Cohesive in dentin (140.58) A Cohesive in RBC (139.40) A Apparently Adhesive (35.65) B Mixed (41.86) B * means with the same letter are not significantly different using the post -hoc Bonferroni test (p > 0.05) Table 7. Mean average image intensity of slices 1 and 2 by failure modes for all teeth (n = 206) Failure modes Mean average image intensity of slices 1 and 2 (mean rank scores) Multiple - group comparison* Cohesive in dentin (139.59) A Cohesive in RBC (140.10) A Apparently Adhesive (35.95) B Mixed (43.75) B * means with the same letter are not significantly different using the post -hoc Bonferroni test (p > 0.05)

79 66 Table 8. Mean image intensity of slice 1 by failure modes for CAD (n = 180) Failure modes Mean image intensity of slice 1 (mean rank scores) Multiple - group comparison* Cohesive in dentin (123.01) A Cohesive in RBC (117.90) A Apparently Adhesive (29.82) B Mixed (36.96) B * means with the same letter are not significantly different using the post -hoc Bonferroni test (p > 0.05) Table 9. Mean average image intensity of slices 1 and 2 by failure modes for CAD (n = 180) Failure modes Mean average image intensity of slices 1 and 2 (mean rank scores) Multiple - group comparison* Cohesive in dentin (122.28) A Cohesive in RBC (119.20) A Apparently Adhesive (29.82) B Mixed (38.25) B * means with the same letter are not significantly different using the post -hoc Bonferroni test (p > 0.05) Table 10. Mean image intensity of slice 1 by failure modes for normal teeth (n = 26) Failure modes Mean image intensity of slice 1 (mean rank scores) Multiple - group comparison* Cohesive in dentin (18.50) A Apparently Adhesive (6.33) B Mixed (5.14) B * means with the same letter are not significantly different using the post -hoc Bonferroni test (p > 0.05)

80 67 Table 11. Mean average image intensity of slices 1 and 2 by failure modes for normal teeth (n = 26) Failure modes Mean average image intensity of slices 1 and 2 (mean rank scores) Multiple - group comparison* Cohesive in dentin (18.00) A Apparently Adhesive (7.33) B Mixed (5.86) B * means with the same letter are not significantly different using the post -hoc Bonferroni test (p > 0.05) Table 12. Descriptive statistics of µtbs by failure modes for all specimens (n = 206) CAD (n = 180) Normal teeth (n = 26) All teeth (n = 206) Failure mode N Mean Median µtbs Standard Deviation Minimum Maximum Cohesive in dentin Cohesive in RBC Apparently adhesive Mixed Cohesive in dentin Apparently adhesive Mixed Cohesive in dentin Cohesive in RBC Apparently adhesive Mixed

81 68 Table 13. µtbs by failure modes for all teeth (n = 206) Failure modes Mean µtbs (SD) Multiple - group comparison* Cohesive in dentin (14.43) A Cohesive in RBC (23.73) A B Mixed (22.61) B C Apparently Adhesive (24.89) C * means with the same letter are not significantly different using the post -hoc Tukey- Kramer test (p > 0.05) Table 14. µtbs by failure modes for CAD (n = 180). Failure modes Mean µtbs (SD) Multiple - group comparison* Cohesive in dentin (14.13) A Cohesive in RBC (23.73) A B Mixed (21.59) B C Apparently Adhesive (21.26) C * means with the same letter are not significantly different using the post -hoc Tukey- Kramer test (p > 0.05) Table 15: µtbs by failure modes for normal teeth (n = 26). Failure modes Mean µtbs (SD) Multiple - group comparison* Cohesive in dentin (9.35) A Apparently Adhesive (12.68) A Mixed (15.91) A * means with the same letter are not significantly different using the post -hoc Tukey- Kramer test (p > 0.05)

82 Level 8 3 levels of dye staining (Level 5-6 vs. 7 vs. 8), n = 206 Level 7 Level levels of dye staining (Level 5-7 vs. 8), n = 206 Level 8 Level Table 16. Descriptive statistics of image intensity by levels of dye staining for all teeth (n = 206) Level of dye staining N Image intensity slice 1 Average image intensity of slices 1 and 2 Mean Median Standard deviation Minimum Maximum Mean Median Standard deviation Minimum Maximum

83 70 Table 17. Mean image intensity of slice 1 by 3 levels of dye staining for all teeth (n = 206) Level of dye staining Mean image intensity of slice 1 (mean rank scores) Multiple - group comparison* Level (90.52) A Level (118.94) A Level (104.56) A * means with the same letter are not significantly different using the post -hoc Bonferroni test (p > 0.05) Table 18. Mean average image intensity of slices 1 and 2 by 3 levels of dye staining for all teeth (n = 206) Level of dye staining Mean average image intensity of slices 1 and 2 (mean rank scores) Multiple - group comparison* Level (91.61) A Level (118.82) A Level (104.35) A * means with the same letter are not significantly different using the post -hoc Bonferroni test (p > 0.05)

84 71 Figure 20. Graph plot between image intensity slice 1 vs. µtbs of all teeth (n = 206) Figure 21. Graph plot between average image intensity of slices 1&2 vs. µtbs of all teeth (n = 206)

85 72 Figure 22. Graph plot between image intensity slice 1 vs. µtbs of CAD (n = 180) Figure 23. Graph plot between average image intensity of slices 1&2 vs. µtbs of CAD (n = 180)

86 73 Figure 24. Graph plot between image intensity slice 1 vs. µtbs of normal dentin (n = 26) Figure 25. Graph plot between average image intensity of slices 1&2 vs. µtbs of normal dentin (n = 26)

87 74 Figure 26. Graph plot between image intensity slice 1 vs. µtbs of all teeth (n = 206), series categorized by 2 levels of dye staining Figure 27. Graph plot between average image intensity of slices 1&2 vs. µtbs of all teeth (n = 206), series categorized by 3 levels of dye staining

88 75 Figure 28. Graph plot between image intensity slice 1&2 vs. µtbs of all teeth (n = 206), series categorized by 2 levels of dye staining Figure 29. Graph plot between average image intensity of slices 1&2 vs. µtbs of all teeth (n = 206), series categorized by 3 levels of dye staining

89 76 Failure mode analysis: all teeth (n = 206) 10% 5% 27% 58% Cohesive in dentin (n = 120) Cohesive in RBC (n = 10) Apparently adhesive (n = 20) Mixed (n = 56) Figure 30. Failure mode analysis of all specimens (all teeth) Failure mode analysis: CAD (n = 180) 9% 6% 27% 58% Cohesive in dentin (n = 104) Cohesive in RBC (n = 10) Apparently adhesive (n = 17) Mixed (n = 49) Figure 31. Failure mode analysis of CAD

90 77 Failure mode analysis: normal teeth (n = 26) 11% 0% 27% 62% Cohesive in dentin (n = 16) Cohesive in RBC ( n = 0) Apparently adhesive (n = 3) Mixed (n = 7) Figure 32. Failure mode analysis of normal teeth Figure 33. SEM photomicrograph of a fracture specimen cohesively in dentin (original magnification 110x)

91 78 Figure 34. SEM photomicrograph of a fracture specimen cohesively in dentin (original magnification 4500x), showing peritubular dentin and intertubular dentin in CAD Figure 35. SEM photomicrograph of a fracture specimen cohesively in dentin (original magnification 4500x), showing dentinal tubules in normal dentin

92 79 Figure 36. SEM photomicrograph of a fracture specimen cohesively in dentin (original magnification 22000x), showing Whitlockite crystal in dentinal tubule in CAD Figure 37. SEM photomicrograph of a fracture specimen cohesively in RBC (original magnification 100x)

93 80 Figure 38. SEM photomicrograph of a fracture specimen cohesively in RBC (original magnification 30000x), showing resin matrix filled with filler particles in Z100 Figure 39. SEM photomicrograph of a fracture specimen apparently in adhesive (original magnification 110x)

94 81 Figure 40. SEM photomicrograph of a fracture specimen apparently in adhesive (original magnification 6000x), showing upper hybrid layer Figure 41. SEM photomicrograph of a fracture specimen apparently in adhesive (original magnification 2000x), showing lower hybrid layer

95 82 Figure 42. SEM photomicrograph of a fracture specimen in mixed group (original magnification 120x) Figure 43. SEM photomicrograph of a fracture specimen in mixed group (original magnification 10000x), showing CAD and adhesive

96 83 CHAPTER 5 DISCUSSION Research hypotheses The purpose of this study was to compare the µtbs of CAD and its degree of mineralization in vitro. The research hypotheses are as follows: H A 1: There is a direct relationship (linear or nonlinear) between μtbs of CAD and the degree of mineralization (image intensity) of CAD. H 0 1: µtbs is unrelated to image intensity at slice 1. [Rejected] H 0 2: µtbs is unrelated to image intensity at the average of slices 1&2. [Rejected] H 0 3: µtbs is unrelated to image intensity (slice 1) of CAD (type 2). [Rejected] H 0 4: µtbs is unrelated to image intensity (slices 1&2) of CAD (type 2). [Rejected] H 0 5: µtbs is unrelated to image intensity (slice 1) of normal dentin (type 1). [Accepted] H 0 6: µtbs is unrelated to image intensity (slices 1&2) of normal dentin (type 1). [Accepted] H A 2: CAD with lower degree of mineralization (image intensity) is related with apparently adhesive and mixed failure mode. H 0 7: Failure mode is unrelated to image intensity at slice 1. [Rejected] H 0 8: Failure mode is unrelated to image intensity at the average of slices 1& 2. [Rejected] H 0 9: Failure mode is unrelated to image intensity (slice 1) of CAD (type 2).

97 84 [Rejected] H 0 10: Failure mode is unrelated to image intensity (slices 1&2) of CAD (type 2). [Rejected] H 0 11: Failure mode is unrelated to image intensity (slice1) of normal dentin (type 1). [Rejected] H 0 12: Failure mode is unrelated to image intensity (slices 1&2) of normal dentin (type 1). [Rejected] H A 3: CAD with lower μtbs is associated with apparently adhesive and mixed failure mode. H 0 13: Failure mode is unrelated to µtbs of all specimens (types 1&2). [Rejected] H 0 14: Failure mode is unrelated to µtbs of CAD (type 2). [Rejected] H 0 15: Failure mode is unrelated to µtbs of normal dentin (type 1). [Accepted] H A 4: CAD with more intense stain is associated with its low image intensity and therefore associated with low μtbs, failure mode in apparently adhesive or mixed group, and ultrastructure showing demineralized dentin from SEM analysis. H 0 16: Level of dye staining is unrelated to image intensity (slice 1) and therefore unrelated to µtbs, failure mode and SEM morphology. [Accepted] H 0 17: Level of dye staining is unrelated to image intensity (slices 1&2) and therefore unrelated to µtbs, failure mode and SEM morphology. [Accepted]

98 85 Our findings showed that there was a significant direct relationship between µtbs and image intensity of all specimens and CAD; however, the correlation coefficient showed weak correlation between the two variables. No significant relationship was found between µtbs and image intensity of normal dentin. Therefore, we rejected the null hypotheses H 0 1 to H 0 4, and accepted H 0 5 and H 0 6. Our results also showed that there was a significant relationship between failure mode and image intensity for all tested teeth, both CAD and normal dentin. Thus, H 0 7 to H 0 12 were rejected. Moreover, H 0 13 and H 0 14 were rejected since there was a relationship between µtbs and failure mode analysis for overall and CAD. However, in normal dentin, no significant relationship between µtbs and failure mode was found. We therefore accepted H In addition, No statistically significant difference in mean average image intensity in 2 and 3 levels of dye staining were observed. Hence, H 0 16 and H 0 17 were accepted. Discussion Our findings showed that there was a significant direct relationship between µtbs and image intensity of all specimens; however, the correlation was weak. This was observed for CAD but not in normal dentin. The results indicate that CAD with high image intensity tends to have higher µtbs. Since the correlation between µtbs and image intensity was weak there may be other variables, besides the simple surrogate measurement of mineral density, that affected the measured µtbs of CAD. CAD is a complex substrate with quite variable degrees of mineralization (Pugach et al., 2009) and mineral deposition (Fusayama, 1991) which potentially compromises adhesion between CAD and adhesive resin by blockage of resin adhesive infiltration (Yoshiyama et al., 2002). Due to a variation within CAD substrate, its different degree of surface wetness may also compromise resin-dentin adhesion and cause phase separation of adhesive resin in hybrid layer. Moreover, even among CADs with equivalent measured image intensities, this does not imply that those substrates have the same property or strength.

99 86 Therefore, considering image intensity alone as a predictor for µtbs might be too simplistic. Attempts (Ceballos et al., 2003) have been made to find an association between other laboratory measurements and µtbs. Ceballos et al (Ceballos et al., 2003) found no association between Knoop s harness and fluorescence values and µtbs of CAD. Therefore, they concluded that hardness and fluorescence of CAD were not good indicators in predicting CAD s µtbs. In normal dentin, µtbs can vary according to: dentin s structural components (Marshall et al., 1997), superficial versus deep dentin (Tagami et al., 1990), hardness (Pashley et al., 1985), coronal versus root dentin (De Goes et al., 2007), to name a few. From our study, however, image intensity of normal dentin did not show any correlation with its µtbs. We speculated that this was probably due to a low number of tested samples, a more consistent interaction zone formed between resin adhesive and normal dentin, and a normal dentin s more homogeneous wetness which resemble interdiffusion zones across different specimens. Although a variety of image intensity in normal dentin across bonded surface was observed, the difference is probably minimal and is unlikely to affect its µtbs. It has been extensively debated whether µtbs was a good predictor of clinical outcomes (Van Meerbeek et al., 2010). Many researchers have attempted to relate µtbs to clinical success parameters. A study from Heintze et al (Heintze et al., 2011) was conducted to relate µtbs with clinical predictors; retention loss, marginal discoloration, marginal integrity, and a clinical index combining these clinical parameters. They found a correlation only between µtbs and marginal discoloration, suggesting that further evaluation should be made to determine if marginal discoloration was associated with future retention loss of restorations. In a similar manner, we found that high image intensity is more likely to achieve a higher µtbs; however, more studies should be made to validate this finding before clinical applicability can be confirmed. Additionally, Van Meerbeek et al (Van Meerbeek et al., 2010) found that only µtbs specimens that had

100 87 been exposed to some form of environmental aging were significantly correlated with Class V restoration retention in non-carious cervical lesions. The ultimate tensile strength (UTS) of CAD is roughly half that of normal dentin (Nishitani et al., 2005), with the majority of total strength (71.3%) contributed by the mineral phase while the remaining (28.7%) was due to the collagen matrix. In CAD, the mineral phase also played important in total strength (59%) while the remaining (41%) relied on collagen matrix. The percentage of total strength relying on collagen matrix in CAD is higher than in normal dentin. This is probably due to mineral depletion in CAD, thus resulting in a shift of total strength dependence toward collagen matrix. This partially explains why CAD is weaker than normal dentin. In general, most mineral is found on the surface of collagen fibril or extrafibrillar compartment (Balooch et al., 2008). However, mineral found within collagen fibrils or intrafibrillar compartment is the main contributor to dentin strength (Kinney et al., 2003; Balooch et al., 2008). This implies that demineralization process from cariogenic bacteria affect mineral phase especially the intrafibrillar compartment, results in lower CAD s bond strength (Yoshiyama et al., 2002; Yoshiyama et al., 2003; Erhardt et al., 2008) compared to normal dentin. Similar to Nishitani et al s finding (Nishitani et al., 2005), we found that CAD overall had lower µtbs than normal dentin (Figure 44), in accordance with findings from Erhardt et al (Erhardt et al., 2008). Nevertheless, some CAD specimens had µtbs comparable to that of normal dentin. Furthermore, the image intensity observed in CAD was scattered. Since CAD s image intensity is somewhat related to µtbs, the variety in CAD s image intensity affects its µtbs and unreliable µtbs obtained. Our results also show that there is a significant effect of image intensity on failure modes for all tested teeth, both CAD and normal. Specimens with higher image intensities tend to fail cohesively in dentin and RBC, whereas specimens with lower image intensity failed adhesively or mixed. This indicates that stronger substrates (higher

101 88 image intensity) immediately adjacent to the adhesive joint promote a better and more reliable bond when compared to weaker substrates (lower image intensity). According to Fusayama (Fusayama, 1991) the CAD zone, from turbid to subtransparent layer, is roughly 1500 µm in thickness (Figure 45). In our study, the tested specimens included approximately 500 µm in thickness of CAD in gauge region or tested volume (Figure 46). Unfortunately, the zone of bonded CAD area right below the interface was unknown. Since CAD is a highly heterogeneous 3-dimensional substrate with various degrees of mineralization and ultrastructural appearance, ideally, µct measurements should be performed across the entire CAD substrate in the gauge area (Figure 47) in order to determine the mean average image intensity of the whole single-dumbbell specimen. During bond strength testing not only strength within a small region below the resindentin interface is being tested, but the entire specimen, including both substrates, and how they are gripped for testing affect the µtbs outcome (Armstrong et al., 2010). Scanning CAD throughout the 500 µm gauge area would better represent the substrate s property and should provide more reliable density value. However, only slice 1 (27 µm) and the average of slices 1&2 (54 µm) of CAD were included in our study. We measured image intensity of fractured specimens side where the resin-dentin interface was located. Unfortunately, it was impossible to obtain image intensity beyond slice 2 (> 54 µm) from specimens where fracture locations were very close to the bonded interface (Figure 48). We therefore included image intensity only 54 µm immediately below the resin-dentin interface. Since the scanned slices were relatively small when compared to the whole tested substrate in gauge area, the image intensity obtained from our study may not represent the true density of the specimens. To obtain a mean range of image intensity of CAD in gauge area, both fractured halves from a specimen could be mounted for µct scanning. Nevertheless, determining image intensity on both fracture sides is labor and time intensive.

102 89 As previously mentioned, we speculated that the stronger substrates promote a better and more reliable bond when compared to weaker substrates. However, It is also possible that this does not indicate a better bond but rather an altered stress distribution within the tensile dumbbell, which lowers the stress concentration within the adhesive joint and forces failure in the dentin substrate. As described in a review from Armstrong et al (Armstrong et al., 2010) Finite elemental analysis (FEA) showed that in µtbs testing, substrate with high elastic modulus and low toughness cannot transfer the stress from the neck region to the test region or gauge area without cohesive failure. This supports our study where cohesive failures in dentin were found in CAD with high mineral density. Since CAD with high density may have some degree of sclerotic dentin due to remineralization process which is usually found in chronic lesion, its low toughness resulted in specimen s embrittleness. Additionally, as described elsewhere that CAD is heterogeneous, there is a possibility that below the high density resin-cad interface, some degree of demineralization may be present. This could affect overall cohesive strength of CAD specimen and is considered a defect site where initiation of fracture occurred. According to our study, the location for image intensity scanning was CAD or normal dentin immediately below the bonded interface, regardless of fracture location. We assumed that stress distribution across dumbbell specimen s gauge area was uniformly distributed. Hence, the measured image intensity was performed beyond interface into CAD/ dentin side. In reality, true µtbs cannot be obtained since the bonded interface composes of different substrate properties (tooth/ adhesive/ RBC), this promote a complex stress distribution, even when a uniform load is applied (Armstrong et al., 2010). This has led to a question according to our study whether measuring image intensity beyond the interface was appropriate, regardless of fracture location. Since µtbs might be related to substrate s cohesive strength, further study is needed to confirm the validity of our study and to investigate if measuring dentin s image intensity

103 90 where fracture locations occur or scanning the entire CAD/ dentin substrate in the tested volume is more practical. Studies (Yoshiyama et al., 2002; Komori et al., 2009) have shown that CAD was associated with low µtbs and cohesive failure in dentin due to the weak substrate in nature. Our findings, however, revealed the opposite if µct image intensity is a valid measurement of mineral density volume and indirectly the strength and toughness of the tooth substrate. Our findings may represent both a heterogeneous substrate combined with stress concentrations that force failure in the dentin deeper within the tooth tissue, keeping in mind that the µct image intensity is only the 27 µm-slice immediately below the adhesive joint. We speculate that CAD with high image intensity might have some degree of sclerotic dentin which may have low toughness. This inherent CAD brittleness may contribute to the cohesive dentin fractures observed. According to the significant effect of µtbs on failure modes, CAD specimens with significantly higher µtbs tend to fail cohesively in dentin or RBC substrates, while those that failed adhesively or mixed tend to have significantly lower µtbs. No significant difference was found in normal dentin group. This implies that substrate with superior physical properties has either: (1) a better load transference across the adhesive resin bond, (2) a stronger substrate, (3) an overall stress distribution that forces failure outside of the adhesive joint, or (4) all three. Nevertheless, contradictory findings were observed between our study and a study from Ceballos et al, who reported adhesive and cohesive failures in CAD with low µtbs and cohesive failures in RBC when high µtbs specimens (Ceballos et al., 2003). Komori et al (Komori et al., 2009), reported lower cohesive strength of CAD was related to higher incidence of cohesive failure in dentin. Study results may vary due to non-standardized specimen preparation and testing methods (Armstrong et al., 2010; Scherrer et al., 2010), as well as the large variety of adhesives used and experimental designs. Many have speculated that low µtbs and cohesive dentin failure is due to the weak CAD substrate. The higher image intensity

104 91 measured in CAD specimens does not directly imply that CAD has mechanical properties similar to that of normal dentin. Therefore, failures occurred cohesively in dentin where weak links were present. Scherrer et al (Scherrer et al., 2010) recommend that all specimens that fail cohesively in dentin or RBC should be excluded from the statistical analyses since those specimens with cohesive failure did not represent the true interfacial bond strength but the mechanical properties of the substrates themselves. They also suggested that only adhesive and mixed failure with less than 10% of RBC or dentin presented should be included in the data analysis. However, according to our study as mentioned earlier, we observed a distinct pattern of failure mode in high and low image intensity substrates. Those with high image intensity presented cohesive failure in dentin and RBC while those with low image intensity failed whether apparently adhesive or mixed. It must also be kept in mind that strength testing does not measure the strength within one small region of the testing volume or area but measures a nominal or average strength of the test specimen, gripping device and load train couplers. Therefore, we conclude that substrate properties have a significant effect, and possibly a dominant effect, on resultant bond strength and thus, cohesive failures should not be excluded. A review (Armstrong et al., 2010) confirmed that bond strength tests and failure mode analysis depended not solely on substrate property but flaws within materials, specimen design and preparation, properties of materials subjected to bond strength test, and testing method. Therefore, one should take into consideration substrates property as one of factors involving bond strength tests. And again, a higher measured mineral density immediately below the adhesion joint does not guarantee a higher mineral density deeper in the tissue or that mechanical properties are uniform throughout the substrate. An alternative approach to excluding specimens that fail cohesively is to report findings both including and excluding cohesive failures, followed with a careful fractographic and ultrastructural appraisal of all failures.

105 92 According to Neves et al (Neves et al., 2009), finite analysis of µtbs specimens showed that specimens with more adhesive thickness tend to have more stress concentration at the bond edge. This leaded to bond failure started at adhesive edge where stress occurred. This observation may have played a role in the fracture phenomena observed in our study; considering the relationship between the three factors: image intensity, µtbs, and failure mode. CAD specimens would have low mineral content below the bonded interface when scanned with µct. Due to partial demineralized collagen, dentin pretreatment with acid etching would result in even wider zone of demineralized collagen. This results in thicker but porous adhesive layer. When these specimens were subjected to µtbs testing, stress concentration occurred at the thick adhesive layer. And with porosity within adhesive layer, this even increases a risk of prefailure in adhesive layer. That is why CAD with low density has lower µtbs and failure usually observed in apparently adhesive and mixed group. Although the bonded CAD zones were unknown, this explanation might relate to those CAD specimens obtained from acute lesions where broader demineralized dentin was observed (Fusayama et al., 1966). In contrary, CAD with higher mineral density, assuming that there is a less degree of demineralization immediately below the bonded interface or due to remineralization process or sclerotic dentin found in chronic lesions, hybrid layer formed would be more uniform and lesser in thickness. Stress concentration will still occur but probably less than in those with thicker hybrid layers. In addition, the non-uniform nature of CADs themselves impairs their cohesive strength and increases the risk of cohesive failure. This partially explains the situation where CAD with high density is usually provided a higher µtbs and cohesive failure in dentin or RBC is usually occurs. The SEM analysis in our study showed that CAD and normal dentin have similar failure modes. The majority failed cohesively in dentin followed by mixed and apparently adhesive. No cohesive failure in RBC observed in normal dentin. The reason why failure pattern in CAD did not differ from those in normal dentin is probably due to the use of a

106 93 gold standard 3-step etch-and-rinse adhesive (De Munck et al., 2005). Therefore, a good and reliable bond obtained, even among CAD group. Moreover, CAD with high image intensity was speculated to have some degree of sclerosis. The sclerotic dentin is likely to have relatively high toughness which embrittle the specimens, the failure mode therefore appeared to occur cohesively in dentin, similarly to those observe in high strength normal dentin. There was no statistically significant difference in mean average image intensity in 2 (level 5-7 vs. 8) and 3 (level 5-6 vs. 7 vs. 8) levels of dye staining. This indicates that the image intensity of CAD was not associated with degree of dye staining. Some redstained (level 5-6) specimens had relatively high mineral density while those with pinkstained (level 7) and no stain (level 8) could be found at a lower level of mineral density. In our study, a relatively small number of stained CAD was observed. This might probably due to over excavation of CAD. However, Caries Detector dye was proved to unselectively stain carious lesion (Yip et al., 1994). The absence of staining does not imply that the dentin is sound; it can be CAD or sclerotic. In addition, the presence of staining does not always imply that dentin was demineralized because Caries Detector does stain normal dentin, especially the one that is close to the pulp. As mentioned earlier, image intensity of CAD observed in our study is highly variable across different levels of dye staining. However, some CAD specimens densities, as identified by caries staining dye and clinical detection, were comparable to normal dentin. A study from Pugach et al (Pugach et al., 2009) found that mineral content (vol%) of CAD was roughly 60% of normal dentin but our measured mineral vol% may not have been this low due to intratubular crystal deposition. We speculate that sclerotic dentin resulting from intratubular mineral deposition affects the overall image intensity of transparent layer of CAD. However, Ogawa et al (Ogawa et al., 1983) debated that the transparent layer which mineral deposition is usually found was not sclerotic since this layer has lower in hardness when compared to normal dentin. In

107 94 accordance with finding from Fusayama (Fusayama, 1991), the Whitlockite crystal found in transparent zone has lower hardness and calcium content, thus, should not be called sclerotic. Likewise, Sunago et al (Sunago et al., 2009) found that black-pigmented and redstained CAD had significantly lower mineral density than pink-stained CAD. However, some specimens in black-pigmented and red-stained CAD group had relatively high mineral density when compared to pink-stained and normal group. Additionally, they found that red-stained CAD was capable of being remineralized, contradictory to findings from Kuboki et al (Kuboki et al., 1983) in which red-stained dentin was unremineralizable. A study from Neves et al (Neves et al., 2011a) also confirmed that CAD s mineral density, measured by µct, was inversely correlated with its dye staining pattern, contradicts to our study where no staining pattern was observed in relation to different image intensities. However, their results and our results may not be comparable due to a different system used in determining staining intensity of CAD (CIE-L*a*b color system vs. a custom shade guide) and different way of reporting density values (mineral density vs. image intensity). Neves et al (Neves et al., 2011a) also reported a higher mineral density in darker lesions (determined by L* value in CIE-L*a*b color system) indicating that dark stained and hard CAD should be preserved for minimally invasive approach. Interestingly, their results showed that using DIAGNOdent as a clinical tool in detecting carious lesions was probably insufficient since the induced fluorescence signal was associated with dark stain but shallow cavities. Using DIAGNOdent to aid in caries diagnosis might result in excessive CAD removal (Neves et al., 2011a). Again, since there was no relationship on the staining pattern associated with image intensity found in our study, along with controversies among studies regarding the use of dye, Caries Detector alone is probably insufficient to diagnose and manage carious lesions. Using Caries Detector dye in conjunction with DIAGNOdent will increase the

108 95 reading value (Neves et al., 2011a) and can lead to misinterpretation of the carious lesion. Therefore, the use of dye and DIAGNOdent together is not recommended. In addition to the study regarding the clinical effectiveness of DIAGNOdent, Neves et al (Neves et al., 2011b) also conducted an in vitro study comparing the clinical effectiveness of 9 different caries removal methods in terms of caries-removal effectiveness and minimal-invasiveness potential using µct. The 9 caries excavation methods were: (1) Tungsten-carbide bur (Komet-Brasseler, Lemgo, Germany), (2) Tungsten-carbide bur aided by Caries Detector (Kuraray, Osaka, Japan), (3) CeraBur (K1SM, Komet-Brasseler, Lemgo, Germany), (4) Cariex (Kavo, Biberach, Germany), (5) Carisolv (MediTeam, Göteborg, Sweden), (6) SFC-V (3M-ESPE, Seefeld, Germany) aided by metal excavator, (7) SFC-VIII (3M-ESPE, Seefeld, Germany) aided by metal excavator, (8) SFC-VIII (3M-ESPE, Seefeld, Germany) aided by plastic excavator, and (9) Er:YAG laser; LIF (Kavo). They found that when considering the caries-removal effectiveness and minimal-invasiveness together, chemo-mechanical methods were the best methods when balancing between the amount of residual caries and over excavation. The use of Tungsten-carbide bur with the aid of Caries Detector dye resulted in overexcavation. However, the use of Tungsten-carbide bur alone would reduce the risk of over preparation. In contrary, Cariex and CeraBur tend to promote an under-preparation cavity where a decent amount of residual caries remained. The use of SFC-VIII with plastic excavator also shifted toward under-preparation. The most unreliable method was Er:YAG laser since it tend to leave more residual caries and sometimes over-preparation. The authors therefore did not recommend using Er:YAG laser due to its non-selective caries removal property (Neves et al., 2011b). In our study, the only method used for caries removal was the use of Tungsten-carbide bur with the aid of Caries Detector dye, which according to Neves et al (Neves et al., 2011b) considered to be too aggressive for caries removal. The fact that we intended to include the varying of degree of mineralization in our study, the technique sensitivity in caries removal was not an issue.

109 96 And since we aimed to determine the levels of dye staining in relation to image intensity, specimens were intentionally prepared with varying degree of CAD hardness by blunt explorer and level of dye staining. Therefore, the caries removal technique used in our study was not intended to include only CAD with the additional purpose of obtaining a varying caries stained dentin shade for image intensity investigation. Regarding image intensity determination using µct, in our study we used CµCT (Micro-CAT II) which produced polychromatic beam. Step-wedge calibration was also performed to correct beam hardening during reconstruction. Micro-CAT II has monochromatization system to maintain monochromatic x-ray beams from polychromatic x-ray source (Zou et al., 2011) to prevent beam hardening. Studies have shown that the used of CµCT with beam hardening correction was as effective as the result from SRµCT (Chappard et al., 2006). The use of step-wedge calibration to convert polychromatic x- ray beams to monochromatic x-ray source was also considered as effective as using SRµCT (Willmott et al., 2007). However, the image intensity value obtained from our study was a relative to gray scale level and thus unitless. We did not scan HA phantoms with known different density (g/cm 3 ) to calculate a calibration curve and therefore cannot compare actual mineral density to published articles. This should be taken into account that for further studies, calibration curve should be perform in order to obtain mineral density and volume percent values. Conclusion Within the limits imposed in the experimental design, we concluded that: The degree of mineralization of CAD has an influence on its failure mode and µtbs. Significant direct correlation was found between CAD s degree of mineralization and µtbs, however, it was weakly correlated. Significant effect was found between CAD s failure mode and its µtbs.

110 97 In normal dentin µtbs did not associate with either its degree of mineralization or mode of failure. No significant relationship was found between levels of dye staining and the degree of mineralization. Study limitations Since we were the first to report a relationship between µtbs and degree of mineralization of CAD, not much data is available using the µct technique and application on a micro-scale tested specimens. The image intensity value obtained from our study was only a gray scale of scanned imaged, not the actual density since a calibration curve in relation to known density (g/cm 3 ) apatite crystal, such as HA was not constructed. We unfortunately cannot quantitatively compare study s result to published articles. Moreover, the BMD software used to determine mean image intensity was a custom program assembled for a specific purpose in this study, no published data regarding BMD software validity is available. In this study, we did not confirm the validity of the program with other mineral density measurement methods such as TMR. Even though the program was reproducible with nearly perfect inter and intrareliability, accuracy was still an issue and need to be validated in future study. Question remains whether the data obtained from this program is valid and whether the gray scale image represent the true density of CAD or normal dentin beyond the resin-dentin interface and does not incorporate the image intensity of adhesive or RBC. It would be of great benefit if we standardized the BMD software before we performed the study. In our study, results regarding CAD vs. normal dentin and certain variables: µtbs, image intensity, and failure modes, were not evaluated statistically, therefore comparisons should be made with caution.

111 98 Clinical significance and future perspective Studies have shown that CAD has lower µtbs than that of normal dentin; however, excessive surgical removal of CAD may lead to weakening of the tooth or pulpal encroachment, both of which could lead to additional or premature treatment needs. To date, there is no agreed upon guideline on how to surgically manage CAD but the trend is toward a conservative approach. Many studies believe that CAD is worth preserving and can be remineralized (Pugach et al., 2009; Sunago et al., 2009). This conservative approach supports the stepwise excavation procedure where deep carious dentin is sealed to prevent further caries progression and to eliminate the risk of pulpal exposure during cavity preparation. A systematic review of stepwise excavation from papers published from 1970 through 2008 (Hayashi et al., 2011) found that many studies had an agreement on the complete excavation of carious dentin periphery with a favorable clinical outcome. Our finding supports the concept of obtaining sound peripheral dentin surrounding the inner carious lesion in stepwise excavation since sound dentin has higher µtbs and therefore should probably provide a better sealing ability of the tooth to be restored. Based on published literature (Kidd et al., 1993; Yip et al., 1994; Neves et al., 2011b) and from our findings, the use of Caries Detector dye is unfortunately not a good clinical tool to manage dental caries since it has been shown to not selectively stained CID. Conventional tactile diagnosis with a blunt probe remains one of the best approaches in managing dental caries (Kidd et al., 1993). Nevertheless, some studies (Neves et al., 2011b) have demonstrated the advantages of using chemo-mechanical methods to achieve an efficient caries removal while preserving tooth structure. Suggestions for further studies included a validation of results from our study and technique used in image intensity determination, along with determining level of uncertainty of each specimen preparation step before proceeding to µct scanning. Calibration curves should be constructed in order to obtain an actual density compared to

112 99 known density crystal such as HA. The actual mineral density then should be compared to other CAD s properties measurement such as elastic modulus, hardness, to name a few. Deeper knowledge regarding different substrates properties (CID, CAD, and normal dentin) should be understood. The ultrastructural changes of acute and chronic carious lesions versus lesions activities are still in need. The results from suggested findings may eventually lead to a development in effective caries diagnostic tool or a guideline in managing dental caries in the most conservative manner while obtaining a favorable clinical outcome. Moreover, µct may be applied in determining the efficacy of new technology aids in detecting caries, such as the photo-thermal radiographluminescence (PTR-LUM) that incorporates the use of laser photothermal radiometry (PTR) and luminescence (LUM) (Jeon et al., 2004). Additionally, attempts should be made to relate µtbs results to clinical trials and therefore validate this in vitro property measurement as a clinical performance measure. Moreover, studies regarding the determination or end point of caries removal would benefit future development in caries management in minimally invasive restorative dentistry in terms of preserving CAD without compromising a longevity clinical outcome.

113 100 Figure 44. Graph plot between image intensity slice 1 vs. µtbs of all teeth (n = 206), series categorized by type of teeth Figure 45. Illustration of CAD's Knoop hardness in a relation to ultrastructural characteristics including mineral deposition and odontoblastic process (Fusayama, 1991)

114 101 Figure 46. Dumbbell specimen showing tested or gauge area of 1 mm (1000 µm) with 0.5 mm-length (500 µm) of dentin in gauge area Figure 47. µct image of fractured specimen showing ideal area of interest (resin-dentin interface and ideal starting and ending point for µct determination

115 102 Figure 48. µct image of fractured specimen showing area of interest (resin-dentin interface and starting and ending point for µct determination in specimen where fracture location is close to interface