Human tooth root canal geometry assessment through micro-ct images A. Garay 1, J.H. Legarreta 1, I. Macía 1, R. C. Aza 2 1 Vicomtech-ik4, Mikeletegi Pasealekua, 57 Teknologi Parkea 20009 Donostia, Spain 2 Clínica Dental Roberto Carlos Aza, Sor Ángela de la Cruz, 40 28020 Madrid, Spain Aims Successful tooth root canal preparation constitutes an essential first step in endodontic therapy in order to ensure an appropriate posterior canal irrigation and obturation. Any infected tissue surrounding the tooth needs to be removed prior to sealing the canal with gutta-percha. The preparation consists of shaping, possibly enlarging and disinfecting the root canal system, thus removing the damaged tissue by means of a series of manually or mechanically powered files, a process called instrumentation. The choice of the technique depends on the canal anatomy, and has an impact on the shaping ability and cleaning effectiveness. Root canal reciprocating motion techniques have gained acceptance during recent years 3. Reciprocating motion, a fully automatic technique, is believed to produce less deformation, to cut better and to advance faster, as well as avoiding unexpected file fractures. In addition, instrumentation time decreases with reciprocating techniques. However, further studies on the effect of reciprocating motion on the canal geometry are still needed Error! Reference source not found.. The purpose of the clinical study is to assess the effect of reciprocating motion compared to continuous rotation in root canal instrumentation using micro-ct images. Although not suitable for in-vivo root canal anatomy assessment, micro-ct scanning allows for a detailed and accurate post-exodoncy assessment of the effect of a given instrumentation technique on the root canal geometry 1. 3D reconstruction from obtained data allows for a clear visualization of the root canal system, dentin and enamel. This paper presents the first step of the whole process, the acquisition and reconstruction parameter configuration for root canal geometry assessment in a SkyScan 1172 micro-ct. Method A number of samples were randomly selected out of a population of 40 human teeth for a preliminary micro-ct acquisition set-up study. All 40 teeth had been extracted due to periodontal causes or orthodontic treatment. All had completely formed apexes without visible apical re-absorption signs and without any previous endodontic treatment. Tissue remainders were removed after exodoncy, and they were stored in 10% buffered formaldehyde solution. A high-resolution SkyScan 1172 100 KV Hamamatsu C9300 11Mp (SkyScan, Kontich, Belgium) micro-ct scanner was used for the study. The micro-ct incorporates a Hamamatsu 100/250 20-100 KV; 0-250 µa; (10 W max); <5 µm spot
size source and a Hamamatsu C9300 11Mp 12-bit cooled CCD fiber-optically coupled to scintillator detector. The teeth were vertically positioned with the plastic tube sample holders provided by SkyScan and fixed with radio-transparent foam. The dental piece were scanned using a total number of four configurations: 180º and 360º rotation for each two filters, Al 0.5 mm and Al+Cu. Scanning with no filter is an unfeasible choice given that the beam contains too much energy for tooth scan purpose even at very low voltages. Other authors 2 have used an Al 1 mm filter, which is halfway between the Al 0.5 mm and Al+Cu filters. The oversize scan method was needed in order to fully scan the samples at reasonable resolution. The acquisition parameters for the SkyScan Version 1.5 (build 12) F Control Program shown in Table 1 and Table 2 were found to yield a good contrast and to achieve the transmission requirement of 40 to 60% at reasonable scanning speed (time), even at full 360º rotation (although this has other drawbacks discussed below). Acquisition parameter Value X-Ray source Voltage (kv) 100 Current (µa) 100 Object position and magnification Pixel size (µm) 19.73 Rotation (º) 180/360 Stage/camera parameters Camera position (Binning) 4x4 Exposure time (ms) 90 Acquisition Rotation step (º) 0.7 Averaging (frames) 2 Random movement Off Scan duration (hh:mm:ss) 00:04:53/00:08:28 Generated dataset size (GB) 0.73/1.3 Table 1. Micro-CT acquisition parameters for the study of root canal geometry in human tooth using an Al 0.5 mm filter. Acquisition parameter Value X-Ray source Voltage (kv) 49 Current (µa) 167 Object position and magnification Pixel size (µm) 19.73 Rotation (º) 180/360 Stage/camera parameters Camera position (Binning) 4x4 Exposure time (ms) 420 Acquisition Rotation step (º) 0.7 Averaging (frames) 2 Random movement Off Scan duration (hh:mm:ss) 00:08:27/00:14:53 Generated dataset size (GB) 0.73/1.3 Table 2. Micro-CT acquisition parameters for the study of root canal geometry in human tooth using an Al+Cu filter.
N.B.: The tables and figures in this paper refer to the values for one of the selected samples. Increasing the resolution (decreasing the pixel size) increases the dataset size accordingly and results in a rather unmanageable dataset for processing and visualization purposes with a medium-range workstation. NRecon version 1.6.3.1 was used for reconstruction purposes. A Volume Of Interest (VOI) encompassing the whole volume was set in each case in order to reduce the generated reconstruction dataset size (and thus, the computational load). The reconstruction parameters used are shown in Table 3, Table 5, Table 5 and Table 6. Smoothing 7 Misalignment compensation -2.0 Ring artifact reduction 20 Beam hardening (%) 30 Generated dataset size(gb) 0.8 Table 3. Reconstruction parameters for micro-ct scanned human tooth using an Al 0.5 mm filter and 180 acquisition. Smoothing 5 Misalignment compensation -2.5 Ring artifact reduction 20 Beam hardening (%) 54 Generated dataset size(gb) 0.8 Table 4.Reconstruction parameters for micro-ct scanned human tooth using an Al 0.5 mm filter and 360 acquisition. Smoothing 5 Misalignment compensation -2.5 Ring artifact reduction 4 Beam hardening (%) 30 Generated dataset size(gb) 0.7 Table 5. Reconstruction parameters for micro-ct scanned human tooth using an Al+Cu filter and 180 acquisition. Smoothing 5 Misalignment compensation -2.5 Ring artifact reduction 4 Beam hardening (%) 30 Generated dataset size(gb) 0.7 Table 6. Reconstruction parameters for micro-ct scanned human tooth using an Al+Cu filter and 360 acquisition. N.B.: The generated reconstruction dataset size depends on the dimensions of the VOI selected for reconstruction.
The same parameters were applied to all sub-scans (part) belonging to the same scan (segment). The acquisition and visualization process were carried out in a workstation with a Dell Precision T5500 workstation, Windows 7 Professional SP1 32-bit, Intel Xeon E5670 2.93 GHz, 4 GB RAM (2.93 GB usable), 2.72 TB hard disk and an NVIDIA Quadro FX580 graphic card. The reconstruction process was performed in a cluster of eight Intel 2xSixCore 2,93GHz, 24 GB RAM processors. Results The reconstruction process shows that, for our purposes, using the Al 0.5 mm filter implies heavier post-processing compared to that required by the Al+Cu filter. There are two main reasons for this: the increased beam hardening and ring artifacts. The choice of the filter has an impact on the beam hardening. Using the Al 0.5 mm filter results in a higher the beam hardening effect since the lower beam energies are still present and penetrate less than the high energy part of the spectrum. Thus, a higher figure is necessary to correct it. Although performing a 360 scan should minimize the beam hardening, we found that the combination of the Al 0.5 mm filter and 360 results in an even poorer performance. Finally, it was verified that increasing the smoothing parameter for the Al 0.5 mm filter at 360 in order to reduce the beam hardening figure did not yield improved results. Furthermore, increasing the smoothing figure results in a loss of detail. Ring artifact increase for the Al 0.5 mm filter may be due to the increase in the beam hardening. See Figure 42. Figure 42. Ring artifacts in a reconstructed slice for the Al 0.5 mm filter and 360 acquisition. Figure 43, Figure 44, Figure 45, Figure 46, Figure 47 and Figure 48 show the result of the reconstruction process. Figure 43. Al 0.5 mm filter acquisition preview. Figure 44. Axial reconstruction for Al 0.5 mm filter and 180 acquisition. Figure 45. Axial reconstruction for Al 0.5 mm filter and 360 acquisition
Figure 46. Al+Cu filter acquisition preview. Figure 47. Axial reconstruction for Al+Cu filter and 180 acquisition. Figure 48.Axial reconstruction for Al+Cu filter and 360 acquisition. Once the reconstructions done, CTAn version 1.10.1.3 was used to analyze the datasets. Our interest was on segmenting the root canal volume and having its statistics computed. For canal geometry assessment purposes, the region comprised between the isthmus and the apex was considered. A CTAn custom processing pipeline was built in order to do so. The Al 0.5 mm dataset posed further segmentation problems than those posed by the Al+Cu filter. Since the contrast between the regions was worse for the Al05 filter and given the increased post-processing activity during reconstruction, the segmentation parameter compromise was harder to achieve. In order to analyze the geometry of the root canal, the 3D analysis performed by CTAn were recorded. Table 7, Table 8, Table 9 and Table 10 show the differences across the acquisitions. Parameter Value Root canal volume (mm 3 ) 14.69839 Tooth volume (mm 3 ) 895.79961 Root canal volume/tooth volume (%) 1.64 Root canal surface(mm 2 ) 106.28693 Root canal surface/volume (%) 7.23120 Table 7. Morphometry parameters for micro-ct scanned human tooth using an Al 0.5 mm filter and 180 acquisition. Parameter Value Root canal volume (mm 3 ) 12.44012 Tooth volume (mm 3 ) 891.82463 Root canal volume/tooth volume (%) 1.39 Root canal surface(mm 2 ) 98.91206 Root canal surface/volume (%) 7.95105 Table 8. Morphometry parameters for micro-ct scanned human tooth using an Al 0.5 mm filter and 360 acquisition. Parameter Value Root canal volume (mm 3 ) 12.55067 Tooth volume (mm 3 ) 909.80999 Root canal volume/tooth volume (%) 1.38 Root canal surface(mm 2 ) 101.95957 Root canal surface/volume (%) 8.12383 Table 9. Morphometry parameters for micro-ct scanned human tooth using an Al+Cu filter and 180 acquisition.
Parameter Value Root canal volume (mm 3 ) 12.83628 Tooth volume (mm 3 ) 887.32546 Root canal volume/tooth volume (%) 1.45 Root canal surface(mm 2 ) 102.10591 Root canal surface/volume (%) 7.95448 Table 10. Morphometry parameters for micro-ct scanned human tooth using an Al+Cu filter and 360 acquisition. It can be drawn from the results that the segmentation process has an impact on the morphometry figures. CTVol version 2.2.0.0 was then used to load and visualize the generated 3D models. The results are shown in Figure 49Figure 49 Figure 50, Figure 52 and Figure 51. Figure 49. 3D model view in CTVol for Al 0.5 mm filter 180 acquisition. Figure 50. 3D model view in CTVol for Al 0.5 mm filter and 360 acquisition. Figure 51. 3D model view in CTVol for Al+Cu filter and 180 acquisition. Figure 52. 3D model view in CTVol for Al+Cu filter and 360 acquisition. As the above images show, the canal volume is extracted with higher accuracy at the apical region from the Al+Cu filter datasets. The discontinuity in one of the root canals found in the Al+Cu 180 acquisition, as it was verified through a slice-wise examination, was probably a result of the compromise between the segmentation parameters. The 3D models confirm the variability seen in the morphometry analysis. Furthermore, since the exact location of the reference plane in the lowest point of the pulp chamber may vary across the different segmentations, another uncertainty element is introduced in the system. Conclusion
According to this initial set-up study for root canal geometry assessment through micro-ct images, the SkyScan 1172 micro-ct has proven to be a valid tool to know the root canal geometry. It has been shown that the Al 0.5 mm presents disadvantages compared to the Al+Cu filter. It requires a higher scanning voltage, up to the limits of the X-Ray source, resulting in a restricted parameter adjustment range. Although it offers a good contrast, its signal-to-noise ratio is worse due to the lower current compared to the Al+Cu filter. Furthermore, it also requires further post-processing to eliminate the generated ring-artifacts and beam hardening. Although the influence of the filter type is unclear when looking the discrepancies in morphometry, the segmentation process proves to be more difficult, and probably less accurate, for the Al 0.5 mm filter. The variability of the segmentation process itself may account for the variations in the morphometry analysis. On the other hand, although the 360º scan doubles both the acquisition time and the initial dataset size, the reconstructed dataset size is comparable to the one produced by a 180º rotation scan. Moreover, the scan time is still reasonable at 360º rotation. Because through the 360º rotation the whole revolution angles are scanned, more information is obtained on the structures contained in the volume. This produces a more accurate reconstruction, which, in turn, may enable an easier segmentation and better root canal geometry assessment. Although there may exist slight variations from one dental piece to another, the Al+Cu filter at 360º rotation seems a reasonable standard configuration for routine scan of dental pieces. It is now our aim to compare the effect of different instrumentation techniques on the root canal geometry. Thus, we expect the comparison to yield information on reparation errors, such as straightening, elbows, clipping or ledging. It should be noticed that for instrumentation technique effect comparison purposes, morphometry features (including volume and surface) will need to be computed separately for each root canal. This is due to the fact that each root canal s geometry is different, and since it is instrumented separately, its geometry varies in a specific way. Furthermore, parameters such as the SMI lack of any significance if not referred to a single canal. Also, a registration framework will need to be developed to compare the changes in a root s canal shape before and after instrumentation. References 1. Peter O.A. Current challenges and concepts in the preparation of root canal systems: a review. J Endod, 30(8):559-567, 2004 2. Sousa-Neto, M. D. et al., Flat-oval root canal preparation with Self-Adjusting File instrument: a micro-ct study, Proceedings SkyScan User Meeting 2011, 140-144, Leuven, Belgium, 2011 3. Yared G. Canal preparation using one only Ni-Ti rotary instrument; preliminary observations. Int Endond J, 41:339-344, 2008 4. You S.Y. et al., Shaping Ability of Reciprocation Motion in Curved Root Canals: A Comparative Study with Micro-Computed Tomography, J Endod, 37(9):1296-13