Development of Application Ontology of Lenke s classification of Scoliosis - OBR-Scolio

Development of Application Ontology of Lenke s classification of Scoliosis - OBR-Scolio Vanja Lukovic, Danijela Milosevic, Sasa Cukovic, and Goran Devedzic Abstract the objective of this paper is to demonstrate creation process of the application ontology of scoliosis OBR- Scolio using the OBR reference ontology, which is spread over anatomy, physiology and pathology domains. Since OBR reference ontology exists only as preliminary classification and does not possess taxonomy of pathological structure, we created the OBR-Scolio ontology by employing analogy with taxonomy of anatomical structure of the FMA reference ontology of anatomy. Also, we obtained the hierarchy of object and data properties of the OBR-Scolio ontology on the basic on FMA reference ontology. The OBR-Scolio ontology is employed in web-based information system for visualization, monitoring and diagnosing of idiopathic scoliosis ScolioMedIS. Considering that the key ontological concepts of the OBR- Scolio ontology are intended to define Lenke s classification of scoliosis, some of the main functionalities of this part of the information system ScolioMedIS include automation of process of determining Lenke s type of scoliosis and statistical demographic analysis of frequency of occurrence of each specific characteristic of scoliosis according Lenke classification. In addition, this part of the system allows continuous monitoring of progression/regression of spinal curvatures for each registered patients with scoliosis, which could help in the process of management of medical treatment of scoliosis. anatomy, physiology and pathology (Fig. 1). The ontology is federation of three independent reference ontologies: Foundational Model of Anatomy (FMA) [8], [9], vertically integrated with top-level Basic Formal Ontology (BFO) [10], Physiology Reference Ontology (PRO) and Pathology Reference Ontology (PathRO) reference ontologies [11]. Although scoliosis domain of our application ontology belongs to pathology domain of spine we used only pathological taxonomy of the OBR reference ontology for the process of vertical integration of our application ontology OBR-Scolio (Fig. 2). I. INTRODUCTION Although most of the published approaches [1] [3] suggest development of application ontology using the process of vertical integration with existing reference ontologies as the best practice, after analyzing many existing biomedical reference ontologies [4] [7] we selected the OBR (Ontology of Biomedical Reality) reference ontology [1] for this purpose. OBR reference ontology ranges over the domains of Manuscript received August 14, 2015. This work was supported - by the Serbian Ministry of Science and Technology under the grant III-41007 Application of Biomedical Engineering in Preclinical and Clinical Practice. V. L. Author is with the University of Kragujevac, Faculty of Technical Sciences, Svetog Save 65, 32000 Cacak, Serbia (phone: (+381 32)302762; fax: (+381 32) 34-21-01; e-mail: vanja.lukovic@ftn.kg.ac.rs). D. M. Author is with the University of Kragujevac, Faculty of Technical Sciences, Svetog Save 65, 32000 Cacak, Serbia (e-mail: danijela.milosevic@ftn.kg.ac.rs). S. C. Author is with the University of Kragujevac, Faculty of Engineering, Sestre Janjic 6, 34000 Kragujevac, Serbia (e-mail: cukovic@kg.ac.rs). G. D. Author is with the University of Kragujevac, Faculty of Engineering, Sestre Janjic 6, 34000 Kragujevac, Serbia (e-mail: devedzic@kg.ac.rs). Fig. 1. Тhе basic classification scheme of the OBR reference ontology. Adopted from [1]. II. DEVELOPMENT OF TAXONOMY OF PATHOLOGICAL- STRUCTURE CLASS OF THE OBR-SCOLIO ONTOLOGY Since OBR reference ontology does not possess taxonomy of pathological_structure class, we employed analogy with hierarchical tree of the main FMA anatomical_structure class in the process of creating the hierarchical tree of the OBR-Scolio pathological_structure class [12]. Namely, we created the hierarchical tree of the OBR-Scolio pathological_structure class by adding the attribute pathological to all FMA anatomical_structure subclasses and by retaining only classes which are relevant to pathology domain of spine such as: pathological_human_body, pathological_organ_system and pathological_organ (Fig. 3). At the other hand, all classes that represent the subdivision of an anatomical structure (e.g. classes whose names begin with subdivision_of) were removed from the hierarchical tree of the OBR patological_structure class. However, all their relevant subclasses were added in the subclass hierarchical tree of the OBR pathological_structure class, using the attribute pathological. This has been done

because pathological part classes are associated with pathological whole class with is_a relation [13] and thus, there was no need for these classes to be classified into a class, whose name begins with subdivision_of. Fig. 2. Pathological taxonomy of the OBR reference ontology to which the application ontology OBR-Scolio is integrated the key class of our application domain. In the next section we describe the process of development of taxonomy of the class pathological_vertebral_column. III. DEVELOPMENT OF TAXONOMY OF PATHOLOGICAL_VERTEBRAL_COLUMN CLASS Idiopathic scoliosis is a three-dimensional (3D) deformity of the spine, including one or more curvatures in frontal plane, with a Cobb s angle values of at least 10deg, one or more curvatures in sagittal plane and vertebral bodies rotation and deformation of unknown origin [14]. It should be stressed that scoliosis is detected in the frontal plane, whereas hypo/hyper-kyphosis and lordosis are detected and quantified in the sagittal plane. Curvature of a spine usually occurs in thoracic, thoracolumbar and lumbar region of the spine, whereas the cervical scoliosis is rare (Fig. 4). Thoracic scoliosis is the most common, while the lumbar scoliosis usually is not itself a dominant problem, as it is too short, but more seriously demonstrates its appearance as thoracic-lumbar deformity. Hence, in this paper we focus only on to the classification and description of curvatures in thoracic and lumbar region of a spine. Fig. 3. Taxonomy of the pathological_structure class of the OBR-Scolio ontology From the subclass hierarchy of the class pathological_organ we only retained the class pathological_cavitated_organ, and its subclass pathological_organ_with_cavitated_organ_parts. From the subclass hierarchy of the class pathological_organ_with_cavitated_organ_parts we only kept its subclass pathological_bone_organ. Further, from the subclass hierarchy of the class pathological_bone_organ we retained the class pathological_irregular_bone and its subclasses: pathological_coccyx, pathological_sacrum and pathological_vertebra. We also retained all subclasses of the class pathological_vertebra (Fig. 3). Moreover, from the subclass hierarchy of the class pathological_organ_system we kept class pathological_musculosceletal_system and the class pathological_skeletal_system and its subclass pathological_axial_skeletal_system. From the subclass hierarchy of pathological_axial_skeletal_system class, we retained the class pathological_vertebral_column, which is Fig. 4. Anatomical regions of a spine: cervical region (C1-C7 vertebrae), thoracic region (T1-T12 vertebrae), lumbar region (L1-L5 vertebrae), sacrum (5 fused vertebrae) and coccyx (4 fused vertebrae) In derivation of taxonomy of the class pathological_vertebral_column in scoliosis domain we started from visualization of regional-part hierarchy of vertebral_column class of the FMA ontology (Fig. 5), generated using OntoGraph plug-in of Protégé ontology editor and a knowledge acquisition system [15]. According above mentioned definition of idiopathic scoliosis, we obtained preliminary classification of pathological_vertebral_column class when we applied curvature_of relation to vertebral column s regional-part class hierarchy (Fig. 5). We can conclude that curvature_of relation propagates [13] through regional_part relation only from the part concepts cervical_vertebral_column,

thoracic_vertebral_column and lumbar_vertebral column to the whole concept vertebral_column, resulting that concepts curvature_of_cervical_vertebral_column, curvature_of_thoracic_vertebral_column and curvature_of_lumbar_vertebral_column specialize the concept curvature_of_vertebral_column. This obviously does not hold for the concepts sacrum and coccyx, according previous definition of scoliosis. measurement (Major curvature) is always structural, while other minor curvatures are defined as structural according Table II. Accordingly, based on curvature s flexibility, classes representing basic curvatures of vertebral column are further differentiated into structural and non-structural (Fig. 6). TABLE II STRUCTURAL CRITERIA FOR MINOR CURVATURES. ADOPTED FROM [14] Curvatures types criteria Proximal thoracic Main Thoracic Thoracolumbar/Lumbar Side banding Cobb angle 25 or Kyphosis angle between T2-T5 20 Side banding Cobb angle 25 or Kyphosis angle between T10-L2 20 Side banding Cobb angle 25 or Kyphosis angle between T10-L2 20 Fig. 5. Regional-part hierarchy of the class vertebral_column, which includes only vertebral column regions IV. OBR-SCOLIO ONTOLOGY In the previous sections we revealed that as a result of selective propagation of curvature_of relation through the regional-part hierarchy of the class vertebral_column we obtained preliminary classification of the class curvatures_of_vertebral_column. In order to obtain expanded taxonomy of the class curvatures_of_vertebral_column we grouped all these classes into the class basic_curvatures_of_vertebral_column and employed definition of curvatures localization and flexibility [14]. Depending on curvatures localization (Table I) the class basic_curvatures_of_vertebral_column is precisely classified into following classes: curvature_of_cervical_vertebral_column, curvature_of_lumbar_vertebral_column, curvature_of_thoracic_vertebral_column and curvature_of_thoracolumbar_vertebral_column. The class curvature_of_thoracic_vertebral_column is further classified into following classes: proximal_thoracic_curvature and main_thoracic_curvature. TABLE I CURVATURES TYPES BASED ON APEX LOCATION - ADOPTED FROM [14] Curvatures types Proximal thoracic Main Thoracic Thoracolumbar Lumbar Apex location T2 - T6 T6 - T11-12 disc T12 or L1 L1-2disc L4 Another very important characteristic of curvatures is theirs flexibility, which is assessed either against the residual curvature in the bending radiograph or the extent of kyphosis. Curvature with largest Cobb angle [17] Fig. 6. Taxonomy of the pathological_vertebral_column class of the OBR- Scolio ontology Another subclass of the class Curvatures_of_vertebral_column is the class Lenke_type_curvatures_of_vertebral_column, which represents curvatures classification according to Lenke et al. [18]. Beside Lenke classification scheme there are also other classification systems for idiopathic scoliosis such as King [19], PMUC [20], Schwab ASD [21], Rigo [22], SRS [23], Lehnert-Schroth classification [24], etc. However in creating the taxonomy of the Curvatures_of_vertebral_column class we only employed Lenke s classification system as the most reliable and used system, which takes into account deformities of spine in both frontal and sagittal plane, as scoliosis is three dimensional deformity of the spine [18]. According Table III Lenke_type_curvatures_of_vertebral_column class has six

subclasses (Fig. 6). TABLE III CURVATURE TYPES ACCORDING TO LENKE CLASSIFICATION SYSTEM OF SCOLIOSIS. ADOPTED FROM. ADOPTED FROM [14] TYPE Proximal Thoracic 5 Main Thoracic Thoracolu mbar/ Lumbar 3 4 1 2 Curvature Type Main Thoracic (MT) Double Thoracic (DT) Double Major (DM) Triple Major (TM) Thoracolumbar /Lumbar (TL/L) In order to incorporate the degree of lumbar spinal deformity in the frontal plane and thoracic deformity in the sagittal plane, in crating taxonomy of Lenke_type_curvatures_of_vertebral_column class we also took into account lumbar frontal spine modifier (A, B or C) and thoracic sagittal spine modifier (+, - or N) (Fig. 7), as is depictured in Fig. 6. Nevertheless, combinations of six curvatures types, three lumbar spine modifiers and three thoracic modifiers (e.g. 1AN ) result in 42 different classifications and not the 54 as would be expected, because all surgically relevant Lenke type 5 and Lenke type 6 curvatures carry the C lumbar modifier [25]. Fig. 8. Taxonomy of the OBR-Scolio ontology Fig. 9. Object properties hierarchy of the OBR-Scolio ontology part 1 Fig. 7. Lumbar spine modifier and thoracic sagittal modifier, according Lenke s classification system of scoliosis. Adopted from [14] For modeling OBR-Scolio ontology we used open source ontology editor and a knowledge acquisition system Protégé [26], [27]. The Fig. 8 illustrates the final taxonomy of the OBR-Scolio ontology, whereas Fig. 9 and Fig. 10 illustrate object properties hierarchy. Data properties hierarchy of the OBR-Scolio ontology is depictured in Fig. 11. We created object properties hierarchy of the OBR-Scolio ontology on the basic of object property hierarchy of the FMA reference ontology, by retaining only object properties, whose domain and range belongs to classes, which exist in the OBR-Scolio taxonomy. Also we added some new object properties, which were relevant to application domain of the OBR-Scolio ontology, such as: appex, curvature_of, has_curves, major_curvature, has_lumbar_modifier, etc. (Fig. 9 and Fig. 10). In the similar way we created datatype properties hierarchy by retaining only datatype properties of the FMA reference ontology, whose domains belong to classes, which exist in the OBR-Scolio taxonomy. Also we added properties, which were specific to application domain of the ontology, like: Cobb_angle,

Cobb_banding_angle_left, Cobb_banding_angle_right, kyphosis_angle_between_t10_l2, kyphosis_angle_between_t2_t5 and kyphosis_angle_between_t5_t12 (Fig. 11). implemented for the needs of the Clinical Center Kragujevac (Serbia), but can be also used for regional analysis and monitoring adolescent spinal deformity in other health centers. However, details about implementation of this part of information system ScolioMedIS for ontology integration go beyond the scope of this paper. Fig. 10. Object properties hierarchy of the OBR-Scolio ontology part 2 Fig. 11. Data properties hierarchy of the OBR-Scolio ontology The OBR-Scolio ontology is integrated in ScolioMedIS system [28] for complete monitoring, visualization and diagnosing of scoliosis, which is based on optical methods. For integrating purpose we used Protégé-OWL API [29], which enables creating, deleting, and editing basic elements of the OBR-Scolio ontology, as well as querying the ontology for obtaining all necessary information. Considering that the key ontological concepts of the OBR- Scolio ontology are intended to define Lenke s classification of scoliosis, some of the main functionalities of this part of the information system ScolioMedIS include automation of process of determining Lenke s type of scoliosis and statistical demographic analysis of frequency of occurrence of each specific characteristic of scoliosis according Lenke classification: regional location of curvature(s), structural property of curvature(s), value of thoracic sagittal modifier and lumbar spine modifier and Lenke s type of scoliosis. In addition, this part of the system allows continuous monitoring of progression/regression of spinal curvatures for each registered patients with scoliosis. Developed system is V. CONCLUSION We developed the OBR-Scolio application ontology to enhance the process of diagnosing and monitoring of idiopathic scoliosis in the ScolioMedIS system, thereby providing tracking of disease with greater comfort and accuracy for a broad range of scoliosis patients. After analyses of many biomedical reference ontologies, which rely on anatomical and pathological domains of spine, our approach was to create the OBR-Scolio ontology in scoliosis domain using the method of extracting from the OBR reference ontology which is spread over anatomy, physiology and pathology domain. We created the taxonomy of the application ontology, using the process of vertical integration in pathology domain of the OBR reference ontology. Although OBR reference ontology does not possess taxonomy of pathological structures, we employed the anatomical domain of the FMA reference ontology for obtaining taxonomy of OBR-Scolio application ontology. The resulting application ontology is based on Lenke s classification system and represents unique scoliosis ontology, which takes into account curvatures location, flexibility and sizes, measured using Cobb method. By integrating the ontology in ScolioMedIS system we obtain a broader perspective on statistical demographic analyses about scoliosis, according to Lenke s classification scheme and also other characteristicsh of the progression/regression of scoliosis, which could help in the process of management of medical treatment of scoliosis. ACKNOWLEDGMENT This research work is supported by the Serbian Ministry of Science and Technology under the grant III-41007: Application of Biomedical Engineering in Preclinical and Clinical Practice and Tempus Project, BioEMIS: Studies in Bioengineering and Medical Informatics (530423 - TEMPUS - 1-2012 - 1 - UK - TEMPUS JPCR), funded by European Commission (EACEA). REFERENCES [1] C. Rosse, A. Kumar, J. L. V Mejino, D. L. Cook, L. T. Detwiler, and B. Smith, A strategy for improving and integrating biomedical ontologies., AMIA Annu. Symp. Proc., pp. 639 43, Jan. 2005. [2] L. Temal, A. Rosier, O. Dameron, and A. Burgun, Mapping BFO and DOLCE., Stud. Health Technol. Inform., vol. 160, pp. 1065 1069, 2010. [3] R. Hoehndorf, F. Loebe, R. Poli, J. Kelso, and H. Herre, GFO-Bio: A biomedical core ontology, Appl. Ontol., vol. 3, no. 4, pp. 219 227, 2008. [4] N. H. Shah and M. A. Muse, UMLS-Query: a perl module for querying the UMLS., AMIA Annu. Symp. Proc., pp. 652 656, 2008. [5] J. Rogers and A. Rector, GALEN s model of parts and wholes: experience and comparisons., Proc. AMIA Symp., pp. 714 718, 2000.

[6] I. Release, T. International, H. Terminology, and S. Development, SNOMED Clinical Terms Technical Reference Guide, Development, no. July, p. 164, 2008. [7] N. F. Noy, N. H. Shah, P. L. Whetzel, B. Dai, M. Dorf, N. Griffith, C. Jonquet, D. L. Rubin, M.-A. Storey, C. G. Chute, and M. A. Musen, BioPortal: ontologies and integrated data resources at the click of a mouse., Nucleic Acids Res., vol. 37, pp. W170 W173, 2009. [8] C. Rosse and J. L. V Mejino, A reference ontology for biomedical informatics: the Foundational Model of Anatomy., J. Biomed. Inform., vol. 36, no. 6, pp. 478 500, Dec. 2003. [9] C. Rosse and L. V. M. Jr., The Foundational Model of Anatomy Ontology, Esophagus, vol. 2007, pp. 59 117, 2007. [10] P. Grenon, B. Smith, and L. Goldberg, Biodynamic ontology: applying BFO in the biomedical domain., Stud. Health Technol. Inform., vol. 102, no. ii, pp. 20 38, 2004. [11] D. L. Cook, J. L. V Mejino, and C. Rosse, Evolution of a Foundational Model of Physiology: Symbolic Representation for Functional Bioinformatics Challenges of Functional Bioinformatics, Med. Educ., vol. 2004, no. Pt 1, pp. 336 340, 2004. [12] V. Luković, D. Milošević, and G. Devedžić, Integrating biomedical ontologies OBR-Scolio ontology, Spec. Issue ICIT 2009 Conf. - Bioinforma. Image, UbiCC J., vol. 4, no. 3, pp. 664 669, 2009. [13] J. Bernauer, Analysis of part-whole relation and subsumption in the medical domain, Data Knowl. Eng., vol. 20, no. 3, pp. 405 415, Nov. 1996. [14] M. Haefei and K. Min, Spinal Deformities and Malformations: Idiopathic scoliosis, in Spinal Disorders: Fundamentals of Diagnosis and Treatment, N. Boos and M. Aebi, Eds. Springer Verlag, 2008, pp. 623 654. [15] OntoGraf - Protege Wiki. [Online]. Available: http://protegewiki.stanford.edu/wiki/ontograf. [Accessed: 18-Jun- 2013]. [16] A. Rector, S. Bechhofer, and C. Goble, The GRAIL concept modelling language for medical terminology, Intell. Med., 1997. [17] R. T. Morrissy, G. S. Goldsmith, E. C. Hall, D. Kehl, and G. H. Cowie, Measurement of the Cobb angle on radiographs of patients who have scoliosis. Evaluation of intrinsic error., J. Bone Jt. Surg., vol. 72, no. 3, pp. 320 327, 1990. [18] L. G. Lenke, R. R. Betz, J. Harms, K. H. Bridwell, D. H. Clements, T. G. Lowe, and K. Blanke, Adolescent idiopathic scoliosis: a new classification to determine extent of spinal arthrodesis., J. Bone Jt. Surg., vol. 83-A, no. 8, pp. 1169 1181, 2001. [19] H. Hosseinpour-Feizi, J. Soleimanpour, J. G. Sales, and A. Arzroumchilar, Lenke and King classification systems for adolescent idiopathic scoliosis: interobserver agreement and postoperative results., Int. J. Gen. Med., vol. 4, pp. 821 5, 2011. [20] G. Qiu, J. Zhang, Y. Wang, H. Xu, J. Zhang, X. Weng, J. Lin, Y. Zhao, J. Shen, X. Yang, K. D. K. Luk, D. Lu, and W. W. Lu, A new operative classification of idiopathic scoliosis: a peking union medical college method., Spine (Phila. Pa. 1976)., vol. 30, no. 12, pp. 1419 1426, 2005. [21] S. Bess, F. Schwab, V. Lafage, C. I. Shaffrey, and C. P. Ames, Classifications for Adult Spinal Deformity and Use of the Scoliosis Research Society-Schwab Adult Spinal Deformity Classification, Neurosurgery Clinics of North America, vol. 24, no. 2. pp. 185 193, 2013. [22] M. D. Rigo, M. Villagrasa, and D. Gallo, A specific scoliosis classification correlating with brace treatment: description and reliability., Scoliosis, vol. 5, no. 1, p. 1, 2010. [23] T. Lowe, S. H. Berven, F. J. Schwab, and K. H. Bridwell, The SRS classification for adult spinal deformity: building on the King/Moe and Lenke classification systems., Spine (Phila. Pa. 1976)., vol. 31, no. 19 Suppl, pp. S119 S125, 2006. [24] H.-R. Weiss, The method of Katharina Schroth - history, principles and current development., Scoliosis, vol. 6, no. 1, p. 17, 2011. [25] L. G. Lenke, Lenke classification system of adolescent idiopathic scoliosis: treatment recommendations., Instr. Course Lect., vol. 54, pp. 537 42, Jan. 2005. [26] S. M. Informatics, The Protégé Ontology Editor and Knowledge Acquisition System welcome to protég, Knowl. Acquis., pp. 2010 2010, 2010. [27] Protégé, The Protégé Ontology Editor, vol. 19, no. 1. Stanforn, 2011. [28] G. Devedzic, S. Cukovic, V. Lukovic, D. Milosevic, K. Subburaj, and T. Lukovic, ScolioMedIS: Web-oriented information system for idiopathic scoliosis visualization and monitoring, Comput. Methods Programs Biomed., vol. 108, no. 2, pp. 736 749, 2012. [29] M. Horridge, protégé-owl api, Research, Stanford Center for Biomedical Informatics, 2012. [Online]. Available: http://protege.stanford.edu/plugins/owl/api/.