Automatic analysis method of 3D images in patients with scoliosis by quantifying asymmetry in transverse contours

• Autorzy: Roy Susmita , Grünwald Alexander T.D. , Alves-Pinto Ana , Lampe Renée

Identyfikatory

DOI

10.1016/j.bbe.2020.09.001

• Języki publikacji: EN

Abstrakty

EN

Scoliosis is characterized by a lateral curvature of spine in the coronal plane of at least 10º, showing three-dimensional deformities of the torso. Recently, a 3D body scanner was proposed as an ionizing radiation-free method, supplementary to clinical examinations and X-rays, for assessing scoliosis and its progression. Here we present an automatic method of analysis of the 3D images of the body torso delivered by the scanner, with the objective of capturing and characterizing deformities in the torso due to scoliosis. The method quantifies asymmetries in each of the torso contours, extracted from 2D cross sections of the 3D torso images, transverse to the vertical axis of the body. Three parameters were calculated: (1) circularity, (2) difference between the areas to left and right of the spinous process (LRAsm), and (3) difference between the ratios width/depth to the left and right of the centroid of the contour (ASR). The method was verified by analyzing twenty-six computed tomography images of patients with different types of scoliosis. In patients with thoracic scoliosis both LRAsm and ASR were larger, that is the asymmetry was stronger, in the thoracic than in the lumbar region, whilst in patients with lumbar scoliosis the inverse was obtained. Furthermore, larger values of LRAsm coincided with the apex position of scoliosis. The circularity factor did not capture scoliosis-related asymmetries. It may, however, be useful in localizing the vertebral level during analysis of 3D scanner data. The method can have the potential to use it for follow-up examinations of scoliosis, in addition to clinical examinations. Further validation of the method requires its application to 3D body scanner data, particularly for more cases of severe scoliosis, which have more irregular transverse contours and thus potential for improvement.

Słowa kluczowe

EN

scoliosis; noninvasive method; body scanner

PL

skolioza; metoda nieinwazyjna; skanowanie ciała

• Wydawca: Nałęcz Institute of Biocybernetics and Biomedical Engineering of the Polish Academy of Sciences ; Elsevier
• Czasopismo: Biocybernetics and Biomedical Engineering
• Rocznik: 2020
• Tom: Vol. 40, no. 4
• Strony: 1486--1498
• Opis fizyczny: Bibliogr. 38 poz., rys.

Twórcy

autor

Roy Susmita

• Technical University of Munich, School of Medicine, Klinikum rechts der Isar, Orthopaedic Department, Research Unit of the Buhl-Strohmaier Foundation for Cerebral Palsy and Paediatric Neuroorthopaedics, Munich, Germany

autor

Grünwald Alexander T.D.

• Technical University of Munich, School of Medicine, Klinikum rechts der Isar, Orthopaedic Department, Research Unit of the Buhl-Strohmaier Foundation for Cerebral Palsy and Paediatric Neuroorthopaedics, Munich, Germany

autor

Alves-Pinto Ana

• Technical University of Munich, School of Medicine, Klinikum rechts der Isar, Orthopaedic Department, Research Unit of the Buhl-Strohmaier Foundation for Cerebral Palsy and Paediatric Neuroorthopaedics, Munich, Germany

autor

Lampe Renée

• Technical University of Munich, School of Medicine, Klinikum rechts der Isar, Orthopaedic Department, Research Unit of the Buhl-Strohmaier Foundation for Cerebral Palsy and Paediatric Neuroorthopaedics, Munich, Germany; Markus Würth Professorship, Technical University of Munich, Munich, Germany

Bibliografia

• [1] Staheli LT. Practice of pediatric orthopedics. Lippincott Williams & Wilkins; 2001.
• [2] Fadzan M, Bettany-Saltikov J. Etiological theories of adolescent idiopathic scoliosis: past and present. Open Orthop J 2017;11(9):1466–89.
• [3] Janicki JA, Alman B. Scoliosis: review of diagnosis and treatment. Paediatr Child Health 2007;12(9):771–6.
• [4] Rigo M. Patient evaluation in idiopathic scoliosis: radiographic assessment, trunk deformity and back asymmetry. Physiother Theory Pract 2011;27(1):7–25.
• [5] Willner S. Moiré topography – a method for school screening of scoliosis. Arch Orthop Trauma Surg 1979;95 (3):181–5.
• [6] Diagnostic moiré image evaluation in spinal deformities. Opt Appl 2016;(3):375–84. XLVI.
• [7] Turner-Smith A. A television/computer three-dimensional surface shape measurement system. J Biomech 1988;21 (6):515–29.
• [8] Adrian G, Fiona B, Paul P. The effects of scoliosis and subsequent surgery on the shape of the torso. Scoliosis Spinal Disord 2017;12(1):31.
• [9] Thometz JG, Lamdan R, Liu X, Lyon R. Relationship between quantec measurement and cobb angle in patients with idiopathic scoliosis. J Pediatr Orthop 2000;20(4):512–6.
• [10] Oxborrow NJ. Assessing the child with scoliosis: the role of surface topography. Arch Dis Child 2000;83(5):453–5.
• [11] Poredoš P, C?elan D, Možina J, Jezeršek M. Determination of the human spine curve based on laser triangulation. BMC Med Imaging 2015;15(2):1–11.
• [12] Zheng R, Hill D, Hedden D, Mahood J, Moreau M, Southon S, et al. Factors influencing spinal curvature measurements on ultrasound images for children with adolescent idiopathic scoliosis. PLOS ONE 2018;13. 6:e0198792.
• [13] Drerup B. Rasterstereographic measurement of scoliotic deformity. Scoliosis 2014;9(22):1–14.
• [14] Melvin M, Samuel S, Adrian S. The validity of rasterstereography: a systematic review. Orthop Rev 2015;7 (3):68–73.
• [15] Grant CA, Johnston M, Adam CJ, Little JP. Accuracy of 3D surface scanners for clinical torso and spinal deformity assessment. Med Eng Phys 2019;63:63–71.
• [16] Jaremko JL, Poncet P, Ronsky J, Harder J, Dansereau J, Labelle H, et al. Indices of torso asymmetry related to spinal deformity in scoliosis. Clin Biomech 2002;17:559–68.
• [17] Jaremko J, Delorme S, Dansereau J, Labelle H, Ronsky J, Poncet P, et al. Use of neural networks to correlate spine and rib deformity in scoliosis. Comput Methods Biomech Biomed Eng 2000;3:203–13.
• [18] Gorton GE, Young ML, Masso PD. Accuracy, reliability, and validity of a 3-dimensional scanner for assessing torso shape in idiopathic scoliosis. Spine 2012;37(11):957–65.
• [19] Kokabu T, Kawakami N, Uno K, Kotani T, Suzuki T, Abe Y, et al. Three-dimensional depth sensor imaging to identify adolescent idiopathic scoliosis: a prospective multicenter cohort study. Sci Rep 2019;9(9678):1.
• [20] Roy S, Grünwald ATD, Alves-Pinto A, Maier R, Cremers D, Pfeiffer D, et al. A non-invasive 3D body scanner and software tool towards analysis of scoliosis. Hindawi Biomed Res Int 2019;2019:1–15.
• [21] Al-Zaghal A, Yellanki D, Kothekar E, Werner T, Høilund- Carlsen P, Alavi A. Sacroiliac joint asymmetry regarding inflammation and bone turnover: assessment by FDG and NaF PET/CT. Asia Ocean J Nucl Med Biol 2019;7(2):108–14.
• [22] Keenan BE, Izatt MT, Askin GN, Labrom RD, Pettet GJ, Pearcy MJ, et al. Segmental torso masses in adolescent idiopathic scoliosis. Clin Biomech 2014;29:773–9.
• [23] SlicerWiki. Documentation – slicer wiki; 2016, https://www.slicer.org/.
• [24] 3D slicer: a platform for subject-specific image analysis, visualization, and clinical support. Intraoperative imaging image-guided therapy, vol. 3(19. 2014;p. 277–89.
• [25] Pope M, Stokes I, Moreland M. The biomechanics of scoliosis. Crit Rev Biomed Eng 1984;11(3):157–88.
• [26] Lenke A, Betz R, Harms J, Bridwell K, Clements D, Lowe T, et al. Adolescent idiopathic scoliosis: a new classification to determine extent of spinal arthrodesis. J Bone Joint Surg- Am 2001;83(8):1169–81.
• [27] Little JP, Rayward L, Pearcy MJ, Izatt MT, Green D, Labrom RD, et al. Predicting spinal profile using 3D non-contact surface scanning: changes in surface topography as a predictor of internal spinal alignment. PLOS ONE 2019;14 (9):1–15.
• [28] Hierholzer E, Lüxmann G. Three- dimensional shape analysis of the scoliotic spine using invariant shape parameters. J Biomech 1982;15(8):583–98.
• [29] Analysis of left-right asymmetry of the back shape of scoliotic patients. Proc SPIE 1985;602:266–71.
• [30] Drerup B, Hierholzer E. Assessment of scoliotic deformity from back shape asymmetry using an improved mathematical model. Clin Biomech 1996;11(7):376–83.
• [31] 3D sensing of back symmetry curve suited for dynamic analysis of spinal deformities. Automatika 2018;59(2):172–83.
• [32] Maliheh Ghaneei AK, Li Y, Parent EC, Adeeb S. 3D markerless asymmetry analysis in the management of adolescent idiopathic scoliosis. BMC Musculoskelet Disord 2018;19(385):1–10.
• [33] Ghaneei M, Ekyalimpa R, Westover L, Parent EC, Adeeb S. Customized k-nearest neighbourhood analysis in the management of adolescent idiopathic scoliosis using 3D markerless asymmetry analysis. Comput Methods Biomech Biomed Eng 2019;19(385):1–11.
• [34] Moreland M, Pope M, Wilder D, Stokes I, Frymoyer J. Moiré fringe topography of the human body. Med Instrum 1981;15 (2):129–32.
• [35] Porto F, Gurgel JL, Russomano T, Farinatti PDTV. Moiré topography: characteristics and clinical application. Gait Posture 2010;32(3).
• [36] Patias P, Grivas TB, Kaspiris A, Aggouris C, Drakoutos E. A review of the trunk surface metrics used as scoliosis and other deformities evaluation indices. Scoliosis 2010;5:12.
• [37] Suzuki N, Ono T, Tezuka M, Kamilshi S. Moire topography and back shape analysis-clinical application. International Symposium on 3-D Scoliotic Deformities Stuttgart: Gustav Fisher Verlag Dansereau J 1992;124–8.
• [38] Cobb J. Outline for the study of scoliosis. Instr Course Lect 1948;5:261–75.