Automated SOSORT-recommended Angles Measurement in Patients with Adolescent Idiopathic Scoliosis

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Automated SOSORT-recommended Angles Measurement in Patients with Adolescent Idiopathic Scoliosis Sasa Cukovic, Vanja Lukovic, Karupppasamy Subburaj, Wolfgang Birkfellner, Danijela Milosevic, Branko

1 Automated SOSORT-recommended Angles Measurement in Patients with Adolescent Idiopathic Scoliosis Sasa Cukovic, Vanja Lukovic, Karupppasamy Subburaj, Wolfgang Birkfellner, Danijela Milosevic, Branko Ristic and Goran Devedzic Abstract In this article we describe a 3D methodology to characterize dorsal surface for the diagnosis of idiopathic scoliosis and its implementation. This characterization is based on the set of external and internal parameters recommended by SOSORT consortium. Parameterized 3D model of the spine and 3D optical scans of dorsal surfaces are used to generate patient-specific surface model for the analysis. The methodology is implemented using Visual Basic Application (VBA) macros in a CAD environment to study relationship between dorsal and internal parameters of spinal deformities and 3D visualization. I. INTRODUCTION any studies showed that manually collecting of M anthropometric measurements and visual assessment of the spinal deformities is time-consuming and depends on subjective judgment of the observer. Advances in technical development of modern optical scanning systems offer multiple options to design non-invasive, accurate and faster diagnostic methods. International Society on Scoliosis Orthopedic and Rehabilitation Treatment (SOSORT) consortium recommends various criteria for the implementation of diagnosis and assessment in the treatment of scoliosis. Those criteria are based on morphometric characteristics of anatomical deformity, functionality, and quality of life of the patients suffering from adolescent idiopathic scoliosis (AIS) [1]. In clinical settings, these deformities are examined by a series of visual tests such as: Manuscript received August 14, This work was supported - by the Serbian Ministry of Science and Technology under the grant III Application of Biomedical Engineering in Preclinical and Clinical Practice and Tempus Project, BioEMIS: Studies in Bioengineering and Medical Informatics ( TEMPUS UK - TEMPUS JPCR), funded by European Commission (EACEA). S. C. is with the University of Kragujevac, Faculty of Engineering, Sestre Janjic 6, Kragujevac, Serbia (corresponding author - phone: ( ) ; cukovic@kg.ac.rs). V. L. is with the University of Kragujevac, Faculty of Technical Sciences, Svetog Save 65, Cacak, Serbia ( vanja.lukovic@ftn.kg.ac.rs). K. S. is with the Singapore University of Technology and Design (SUTD), 8 Somapah Road, Singapore , Singapore ( subburaj@sutd.edu.sg). W. B. is with the Center for Medical Physics and Biomedical Engineering, Medical University Vienna, AKH 4L Waehringer Guertel 18-20, A-1090 Vienna, AT ( wolfgang.birkfellner@meduniwien.ac.at). D. M. is with the University of Kragujevac, Faculty of Technical Sciences, Svetog Save 65, Cacak, Serbia ( danijela.milosevic@ftn.kg.ac.rs). B. R. is with the University of Kragujevac, Faculty of Medical Sciences, Svetozara Markovića 69, Kragujevac, Serbia ( branko.ristic@gmail.com). G. D. is with the University of Kragujevac, Faculty of Engineering, Sestre Janjic 6, Kragujevac, Serbia ( devedzic@kg.ac.rs). inspection by scoliometer device, interpretation of radiological images and surface topography scans, analysis of other modalities (CT, MRI, ultrasound, etc.), photographic tests, etc. [2]-[5]. SOSORT s criteria are in line with the key measurements currently used by physicians in clinical settings [6]. We propose a non-invasive 3D methodology to quantify these deformity measures using patient-specific models generated from patient s dorsal surface shape, anatomical landmarks, curve of surface asymmetry, and middle spinal curve generated from optical scan data. The methodology is created using knowledgeware technology and VBA macros implemented in PLM system CATIA to perform these measurements with minimal human intervention and repeatedly. II. MATERIALS AND METHODS The schematic representation of the methodology and implementation scheme is shown in Fig. 1. Fig. 1. Algorithmic scheme to simulate scoliosis, 3D registration and detection of key vertebrae - deformity diagnosis

For this purpose we used Turner-Smith's rule, which localize peaks of spinal processus on the dorsal surface, to generate these reference elements [10].

2 A. Algorithmic scheme and interface of ScoliosisSimulator-3DSpinalRegistration.catvba macro We implemented VBA macro for generating and visualizing reference elements of 3D skeletal model on the spinal curve. For this purpose we used Turner-Smith's rule, which localize peaks of spinal processus on the dorsal surface, to generate these reference elements [10]. The system produces a set of diagnostic parameters that are displayed in the special branch of the CAD elements tree, but also exported in separate *.xls file for downstream analysis. We employed PLM system CATIA V5R20 to automate the methodology with in-built VBA scripts environment [9] and developed a macro ScoliosisSimulator- 3DSpinalRegistration.catvba. This macro takes the patient's optical scan data of dorsal surface. It generates elements of CAD skeletal model based on a generic parameterized CAD 3D model of spine (by rigid registration) and generates key parameters to quantify deformities. B. Measuring the linear and angular anatomical measures on dorsal surface using VBA scripts To measure dorsal surface symmetry we use the locations of markers (primary and secondary) from the optical scan data on the patient s back. The symmetry line follows vertebral extensions - processus and passes through transition points of the lumbar-thoracic and thoracic-cervical segment (Fig.2). On this line, peak of lordosis curve is marked as fix_la, peak of kyphosis curve is marked as fix_ka and peak of cervical lordosis curve is marked as fix_ca. Transitional (inflection) points of the asymmetry line of dorsal surfaces are denoted as fix_itl and fix_ict. Set RefS1 = Prt.CreateReferenceFromObject(HBl.HybridShapes.Item("Normal15- XY")) 'T2 Set RefS2 = Prt.CreateReferenceFromObject(HBl.HybridShapes.Item("Normal12- XY")) 'T5 Set TheMeasurable = MyBench.GetMeasurable(RefS1) CatiaResult.T2T5 = TheMeasurable.GetAngleBetween(RefS2) CreateParam "T2T5", CatiaResult.T2T5, 1 'Result 21 Creating of angle parameter SosortSagittalT4T12_deg: 'Result 25 - get SosortSagittalT4T12 Set RefS1 = Prt.CreateReferenceFromObject(HBl.HybridShapes.Item("iLine13- YZ")) 'T4 Set RefS2 = Prt.CreateReferenceFromObject(HBl.HybridShapes.GetItem("iLine5- YZ")) 'T12 Set TheMeasurable = MyBench.GetMeasurable(RefS1) CatiaResult.SosortSagittalT4T12 = TheMeasurable.GetAngleBetween(RefS2) CreateParam "SosortSagittalT4T12", CatiaResult.SosortSagittalT4T12, 1 'Result 25 C. The external parameters of deformities and dorsal surfaces For characterization of the dorsal surface and deformity we used external anthropometric measures and 15 parameters measured with reference to primary and secondary anatomical landmarks. Some of the linear and angular measurements in the frontal and sagittal plane of dorsal surface that characterize spinal deformity are: TrunkLengthVPDM_mm, TrunkLengthVPSP_mm, DimpleDistanceDLDR_mm, TrunkInclinationVPDM_deg, TrunkInclinationVPDM_mm, PelvicTiltDLDR_mm, PelvicTiltDLDR_deg, TrunkImalanceVPDM_deg, and TrunkImalanceVPDM_mm. In addition, we also evaluated some additional measures based on secondary skin markers. These measures are related to the intensities of kyphosis and lordosis in the sagittal plane as described by Fleche et al. [10]: FlecheCervicale_mm, FlecheLombaire_mm, KyphoticAngleICTITLmax_deg, LordoticAngleITLDM_deg. Fig. 2. Position of anatomical landmarks and basic anatomical measurements of dorsal surface Main anatomical landmarks of the patient s dorsal surface are fix_c7, fix_dm, fix_arpitleft, fix_armpitright, fix_dl, fix_dr, and fix_sp. After generating basic skeletal elements, VBA script calculates diagnostic parameters. As a representation, we specify part of the code that creates SOSORT-these angles. Creating of angle parameter T2T5_deg: 'Result 21 - get T2T5 Fig. 3. The SOSORT angles of the upper thoracic region in the frontal plane: T5T12, deg and T2T5, deg D. Measurement of angles of spinal curves defined based on SOSORT consortium SOSORT consortium recommends selecting the reference vertebrae in the sagittal and frontal planes for measuring

angles as done in clinical settings [11].

T2T5, deg; T5T12, deg; T10L2, deg; L1L5, deg and SosortSagittalT4T12, deg; SosortSagittalL1L5, deg.

This procedure performs automatically using VBA in YZ and XY planes (Fig.3, Fig.4, and Fig.5). III.

1.CATPart) that enables a strong multi-modular associations and built-in knowledge to create the 3D model of the spinal assembly (Master Product.

3 angles as done in clinical settings [11]. Thus, we measured angles between vertebrae T2-T5, T5-T12, T10-L2, and L1- L5 in the frontal plane and angle between vertebrae L1-L5 and T4-T12 in the sagittal plane, which are denoted as follows: T2T5, deg; T5T12, deg; T10L2, deg; L1L5, deg and SosortSagittalT4T12, deg; SosortSagittalL1L5, deg. These angles are measured based on the projected central spine line that passes through the centroid points of vertebral bodies of patient in a standing position [12], [13], [14]. This procedure performs automatically using VBA in YZ and XY planes (Fig.3, Fig.4, and Fig.5). III. PATIENT-SPECIFIC 3D MODEL OF DEFORMITY VBA script creates all elements of the skeletal CAD model of dorsal surface (Part1.1.CATPart) that enables a strong multi-modular associations and built-in knowledge to create the 3D model of the spinal assembly (Master Product.CATProduct) and does registration of 3D generic model of the spine. Once the patient-specific model is generated, the initial generic model (Part1.1.CATPart) will be replaced with the patient-specific model in the data flow. 3D CAD model of deformity and ScoliosisSimulator- 3DSpinalRegistration.catvba macro are integral part of the system ScolioMedIS, the information system for monitoring and diagnosing scoliosis [13]. Fig. 6. Initialization of registration and regenerating the 3D model of the spine to the skeletal CAD model of dorsal surface of the specific patient As the names of models form the CAD skeletal model are associated and published in the model tree, the registration process is initiated by scaling factor parameter (Ln\ ExternalParameters\ScalingFactor.1). Further transformation of each generic vertebra are subject to rigid registration (scaling, translation and rotation) (Fig.6, Fig.7). Fig. 4. The SOSORT angles of the thoracolumbar and lumbar region in the frontal plane: T10L2, deg and L1L5, deg Fig. 7. Assembled (registered) model of the spinal model to the skeletal model of the dorsal surface Fig. 5. The SOSORT angles in the sagittal plane: SosortSagittalT4T12, deg, and SosortSagittalL1L5, deg Master (generic) 3D CAD model of the spine is adaptable to all models of CAD surfaces obtained from the patients datasets [13], [14]. This is achieved through the common names of reference skeletal elements with CAD assembly,

published in the model tree and used to establish the geometric dependence in VBA processing. IV.

deformity are also included in the statistics that system offers [13].

SPSS Inc., Chicago, IL, USA), to determine the correlation coefficient (r) and linear relationship between the anatomical measures [15], [16], [17]. Fig.

Extreme values of these measures are SosortSagittalT4T12 and SosortSagittalL1L5 in 2 samples from 372 adolescents dataset. Male patient M.U., 16. years old., SosortSagittalT4T12=54.10 Male patient D.

4 published in the model tree and used to establish the geometric dependence in VBA processing. IV. RESULTS AND DISCUSSION In addition to general demographic data, gender and age presented in the patient s record included in the ScolioMedIS system, generated external and internal parameters of deformity are also included in the statistics that system offers [13]. Length measures (mm) and angles (degrees) are processed in the program Excel 2013 (Microsoft, USA) and are statistically analyzed by the program SPSS v20 (Statistical Package for Social Sciences - SPSS Inc., Chicago, IL, USA), to determine the correlation coefficient (r) and linear relationship between the anatomical measures [15], [16], [17]. Fig. 8 shows the maximum angles of kyphosis and lordosis that were defined based on SOSORT recommendations. Extreme values of these measures are SosortSagittalT4T12 and SosortSagittalL1L5 in 2 samples from 372 adolescents dataset. Male patient M.U., 16. years old., SosortSagittalT4T12=54.10 Male patient D.F., 11 years old., SosortSagittalL1L5=66.46 Fig. 8. Illustration of maximum values of the parameters SosortSagittalT4T12 and SosortSagittalL1L5 in 2 adolescents A. Statistics on SOSORT angles According to SOSORT recommendations VBA macro generated angles in the frontal plane (L1L5, T10L2, T2T5, T5T12) and sagittal plane (SosortSagittalL1L5, SosortSagittalT4T12). Descriptive statistics are presented in the following tables (Table I, Table II). TABLE I STATISTICS OF SOSORT ANGLES MALE PATIENTS DESRIPTIVE STATISTICS OF SOSORT ANGLES MALE PATIENTS N Min. Max. Mean values Standard deviation L1L T10L T2T T5T SosortSagittalL1L SosortSagittalT4T Valid N 141 TABLE II STATISTICS OF SOSORT ANGLES FEMALE PATIENTS DESRIPTIVE STATISTICS OF SOSORT ANGLES FEMALE PATIENTS N Min. Max. Mean values Standard deviation L1L T10L T2T T5T SosortSagittalL1L SosortSagittalT4T Valid N 231 B. Correlation of SOSORT-these and Cobb's angles It is stated in literature that Cobb's angles in diagnostic procedures is "gold standard" for quantifying deformities on x-rays. One of the key issues is the estimate the degree of correlation of these angles with topographical angular measures. Some studies discuss relations of internal Cobb's angles to profile of dorsal surface and torso [18]. In [19] it is stated that there is a significant correlation ( r 2 = 0.66 ) of Cobb angle of middle spinal line with the so-called "Quasi Cobb's angle", that is the angle of the external lines of surface asymmetry. The equation which describes this correlation is Cobb, and r 2 = 0.66 is an indication that 66% of topographical curves can be described through the Cobb's angles of middle spinal lines [20]. In [21] authors present the analysis of idiopathic scoliosis in the case of 91 patients with Cobb's angles between 20-82º. They have compared rasterstereography measures of captured dorsal surface with the measures obtained in the bended patient position, measured using scoliometer and 2 found a small correlation ( r = 0.35 ). Calculation of Pearson's correlation coefficients between frontal SOSORT's angles and primary Cobb's angles generated on the middle spinal line using VBA script are shown in the following table (Table III).

5 TABLE III CORRELATION OF INTERNAL DEFORMITY PARAMETERS IN FRONTAL PLANE CORRELATION OF FRONTAL DEFORMITY ANGLES Scaling Factor Primary FrontalCobb L1L5 T10L2 T2T5 T5T12 ScalingFactor ** ** PrimaryFrontal Cobb **.572 **.419 **.742 ** L1L ** **.108 *.617 ** T10L **.572 **.219 ** **.302 ** T2T **.108 *.245 ** ** T5T **.742 **.617 **.302 **.260 ** 1 **. Correlation is significant at the 0.01 level (2-tailed). *. Correlation is significant at the 0.05 level (2-tailed). Pearson Correlation A particularly interesting is that among the high correlation parameters in the frontal plane is the correlation between PrimaryFrontalCobb and T5T12 that reaches ( r 2 = 0.55 ). Calculation of Pearson's correlation coefficients between parameters generated on the middle spinal line and dorsal surface using VBA script are shown in the Table IV. TABLE IV CORRELATION OF SAGITTAL DEFORMITY PARAMETERS CORRELATION OF SAGITTAL DEFORMITY ANGLES Scaling Factor Fleche Cervicale Fleche Lombaire vertebrae curves, central spinal line, and anatomical reference points. Relying on mathematical capabilities and minimal human intervention in quantifying these measures and removing visual assessment from the characterization makes the system less vulnerable to errors of subjective assessment or parallax. The results need to be verified with a larger dataset. Since, many causes of errors in measuring the Cobb angle, a caution should be exercised in interpreting the results. We are working towards integrating the methodology to our web-based scoliosis visualization and information system (ScolioMedIS) for online deployment to make it available in remote rural places. 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 ( TEMPUS UK - TEMPUS JPCR), funded by European Commission (EACEA). Kyphotic Angle VPITL Lordotic Angle ITLILSmax Primary Sagittal Cobb SosortSagittal L1L5 SosortSagittal T4T12 ScalingFactor **.145 ** * **.047 FlecheCervicale.290 ** **.702 ** ** ** FlecheLombaire.145 **.232 ** **.517 **.426 **.431 **.570 ** KyphoticAngleVPITL **.650 ** **.498 **.300 **.692 ** LordoticAngleITLILSmax * **.446 ** **.542 **.308 ** PrimarySagittalCobb **.426 **.498 **.559 ** **.341 ** SosortSagittalL1L ** **.300 **.542 **.425 ** ** Pearson Correlation SosortSagittalT4T **.570 **.692 **.308 **.341 **.318 ** 1 **. Correlation is significant at the 0.01 level (2-tailed). *. Correlation is significant at the 0.05 level (2-tailed). In the sagittal plane, attention draws high correlation between FlecheCervicale and KyphoticAngleVPITL that reaches ( r 2 = 0.49 ). After geometric analysis of curvature deviations, asymmetry and surfaces, VBA generates 3D visualization of the spine and key parameters of deformity and prepares model for internet visualization. In addition to the parameters that are evaluated with radiographic images, a large number of parameters are determined based on the positions of anatomical features detected on the surface of the patient (lengths, angles, etc.) [22]. V. CONCLUSION In summary, we have presented an automated methodology to quantify SOSORT recommended measures to characterize spine deformity in patients with idiopathic scoliosis and its implementation. Results from the preliminary study show that these measures correlate well with the deformity measurements performed by the physicians. These measures are quantified based on REFERENCES [1] H. Shakil, Z.A. Iqbal, A.H. Al-Ghadir, "Scoliosis: review of types of curves, etiological theories and conservative treatment," Journal of Back and Musculoskeletal Rehabilitation, vol. 27, no. 2, pp , [2] R. Manuel, "Patient evaluation in idiopathic scoliosis: Radiographic assessment, trunk deformity and back asymmetry," Physiotherapy Theory and Practice, vol. 27, no. 1, pp. 7-25, [3] T. Kotwicki, "Evaluation of scoliosis today: Examination, X-rays and beyond," Journal of Disability and Rehabilitation, vol. 30, no. 10, pp , [4] S. Kadoury, F. Cheriet, C. Laporte, H. Labelle, "A versatile 3D reconstruction system of the spine and pelvis for clinical assessment of spinal deformities," Journal of Medical and Biological Engineering and Computing, vol. 45, pp , [5] B. Ilharreborde, J. Dubousset, W. Skalli, K. Mazda, "Spinal penetration index assessment in adolescent idiopathic scoliosis using EOS low-dose biplanar stereoradiography," European Spine Journal, vol. 22, no. 11, pp , [6] G. H. Bendels, R. Klein, M. Samimi and A. Schmitz, "Statistical Shape Analysis for Computer Aided Spine Deformity Detection," The Journal of WSCG, vol. 13, Plzen, Czech Republic ISSN , [7] J. Hansen, Kochbuch CATIA v5 Automatisieren. Vom Powercopy bis zur C#-Programmierung, Munich: HANSER Verlag, 2009.

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From Generic to the Patient Specific 3D Model of the Spine in Case of Adolescent Idiopathic Scoliosis (AIS)

From Generic to the Patient Specific 3D Model of the Spine in Case of Adolescent Idiopathic Scoliosis (AIS) Sasa Cukovic 1, Goran Devedzic 1, Tanja Lukovic 2,3, Vanja Lukovic 4 1. University of Kragujevac,