Các mô hình hiện tại để hiểu sự khởi phát và tiến triển của các dị dạng vẹo cột sống ở bệnh nhân vẹo cột sống vô căn ở tuổi thanh thiếu niên: Một đánh giá có hệ thống

Spine Deformity - Tập 11 - Trang 545-558 - 2022
A. R. Meiring1, E. P. de Kater1, A. Stadhouder2,3, B. J. van Royen2,4,3, P. Breedveld1, T. H. Smit2,3
1Faculty of Mechanical, Maritime and Materials Engineering, Delft University of Technology, Delft, The Netherlands
2Department of Orthopedic Surgery and Sports Medicine, Amsterdam UMC, Amsterdam, The Netherlands
3Amsterdam Movement Sciences, Amsterdam, The Netherlands
4Emma Children’s Hospital, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands

Tóm tắt

Để tạo ra một cái nhìn tổng quan cập nhật và toàn diện về các nghiên cứu mô hình đã được thực hiện nhằm hiểu cơ chế cơ học liên quan đến các dị dạng của vẹo cột sống vô căn ở thanh thiếu niên (AIS), dự đoán nguy cơ tiến triển độ cong và từ đó củng cố các lý thuyết về nguyên nhân sinh bệnh. Trong đánh giá có hệ thống này, một tìm kiếm trực tuyến trong Scopus và PubMed cùng với phân tích các tài liệu tham khảo thứ cấp đã được thực hiện, dẫn đến 86 nghiên cứu. Các loại mô hình được chiết xuất và các nghiên cứu được phân loại tương ứng. Mô hình động vật, cùng với mô hình học máy, tạo thành danh mục các mô hình hộp đen. Danh mục này được coi là có liên quan nhất về mặt lâm sàng. Trong khi các mô hình động vật cung cấp ý tưởng cụ thể về tác động cơ học trong các dị dạng vẹo cột sống, mô hình học máy được phát hiện là dự đoán tốt nhất cho sự tiến triển độ cong. Danh mục thứ hai, đó là các mô hình nhân tạo, cũng giống như mô hình động vật, có một mô hình cụ thể như là kết quả, nhưng tập trung nhiều hơn vào quá trình cơ học của dị dạng vẹo cột sống. Danh mục thứ ba được hình thành bởi các mô hình tính toán, rất phổ biến trong các nghiên cứu dựa trên các tham số nguyên nhân sinh bệnh. Chúng cũng là những mô hình tốt nhất trong việc tính toán áp lực và biến dạng trên đốt sống, đĩa đệm giữa các đốt sống, và các mô mềm xung quanh khác. Nghiên cứu này trình bày một cái nhìn tổng quan toàn diện về các kỹ thuật mô hình hiện tại để hiểu cơ chế của các dị dạng vẹo cột sống, dự đoán nguy cơ tiến triển độ cong trong AIS và từ đó củng cố các lý thuyết về nguyên nhân sinh bệnh. Mặc dù AIS vẫn được xem là một vấn đề phức tạp và đa yếu tố, sự tiến triển của dị dạng này có thể được dự đoán với độ chính xác tốt. Mô hình hóa AIS phát triển nhanh chóng và có thể dẫn đến việc xác định các yếu tố nguy cơ và các chiến lược giảm thiểu trong tương lai gần. Cái nhìn tổng quan được trình bày cung cấp một cơ sở để theo dõi sự phát triển này.

Từ khóa

#vẹo cột sống #vẹo cột sống vô căn #mô hình hóa #học máy #cơ học #tiến triển

Tài liệu tham khảo

de Baat P, van Biezen EC, de Baat C (2012) Scoliosis: review of types, aetiology, diagnostics, and treatment 1. Ned Tijdschr Tandheelkd 119:474–478. https://doi.org/10.1007/s00586-011-1699-4 Phan P, Mezghani N, Aubin CE et al (2011) Computer algorithms and applications used to assist the evaluation and treatment of adolescent idiopathic scoliosis: a review of published articles 2000–2009. Eur Spine J 20:1058–1068. https://doi.org/10.1007/s00586-011-1699-4 Man GCW, Wang WWJ, Yim APY et al (2014) A review of pinealectomy-induced melatonin-deficient animal models for the study of etiopathogenesis of adolescent idiopathic scoliosis. Int J Mol Sci 15:16484–16499. https://doi.org/10.3390/ijms150916484 Hefti F (2013) Pathogenesis and biomechanics of adolescent idiopathic scoliosis (AIS). J Child Orthop 7:17–24. https://doi.org/10.1007/s11832-012-0460-9 Wang W, Baran GR, Betz RR et al (2014) The Use of finite element models to assist understanding and treatment for scoliosis: a review paper. Spine Deform 2:10–27. https://doi.org/10.1016/j.jspd.2013.09.007 Smit TH (2020) Adolescent idiopathic scoliosis: The mechanobiology of differential growth. JOR Spine 3:1–13. https://doi.org/10.1002/jsp2.1115 Breedveld P, Herder JL, Tomiyama T (2022) Teaching creativity in mechanical design. Delft. https://doi.org/10.5281/ZENODO.5849490 Duong L, Cheriet F, Labelle H (2006) Three-dimensional classification of spinal deformities using fuzzy clustering. Spine 31:923–930. https://doi.org/10.1097/01.brs.0000209312.62384.c1 Duong L, Mac-Thiong JM, Cheriet F et al (2009) Three-dimensional subclassification of Lenke type 1 scoliotic curves. J Spinal Disord Tech 22:135–143. https://doi.org/10.1097/BSD.0b013e31816845bc Kadoury S, Labelle H (2012) Classification of three-dimensional thoracic deformities in adolescent idiopathic scoliosis from a multivariate analysis. Eur Spine J 21:40–49. https://doi.org/10.1007/s00586-011-2004-2 Thong WE, Labelle H, Shen J et al (2015) Stacked auto-encoders for classification of 3D Spine models in adolescent idiopathic scoliosis. Lecture Notes Comput Vis Biomech 20:13–25 Thong W, Parent S, Wu J et al (2016) Three-dimensional morphology study of surgical adolescent idiopathic scoliosis patient from encoded geometric models. Eur Spine J 25:3104–3113. https://doi.org/10.1007/s00586-016-4426-3 Kadoury S, Shen J, Parent S (2014) Global geometric torsion estimation in adolescent idiopathic scoliosis. Med Biol Eng Compu 52:309–319. https://doi.org/10.1007/s11517-013-1132-8 García-Cano E, ArámbulaCosío F, Duong L et al (2018) Prediction of spinal curve progression in adolescent idiopathic scoliosis using random forest regression. Comput Biol Med 103:34–43. https://doi.org/10.1016/j.compbiomed.2018.09.029 Kadoury S, Mandel W, Roy-Beaudry M et al (2017) 3-D morphology prediction of progressive spinal deformities from probabilistic modeling of discriminant manifolds. IEEE Trans Med Imaging 36:1194–1204. https://doi.org/10.1109/TMI.2017.2657225 Ajemba PO, Ramirez L, Durdle NG et al (2005) A support vectors classifier approach to predicting the risk of progression of adolescent idiopathic scoliosis. IEEE Trans Inf Technol Biomed 9:276–282. https://doi.org/10.1109/TITB.2005.847169 Kadoury S, Cheriet F, Labelle H (2008) Prediction of the T2–T12 kyphosis in adolescent idiopathic scoliosis using a multivariate regression model. Stud Health Technol Inf 140:269–272. https://doi.org/10.3233/978-1-58603-888-5-269 Aubert B, Vergari C, Ilharreborde B et al (2016) 3D reconstruction of rib cage geometry from biplanar radiographs using a statistical parametric model approach. Comput Methods Biomech Biomed Eng Imaging Vis 4:281–295. https://doi.org/10.1080/21681163.2014.913990 Villemure I, Aubin CE, Grimard G et al (2001) Progression of vertebral and spinal three-dimensional deformities in adolescent idiopathic scoliosis: a longitudinal study. Spine 26:2244–2250. https://doi.org/10.1097/00007632-200110150-00016 Kaddioui H, Duong L, Joncas J et al (2020) Convolutional neural networks for automatic risser stage assessment. Radiol Artif Intell 2:e180063. https://doi.org/10.1148/ryai.2020180063 Kokabu T, Kanai S, Kawakami N et al (2021) An algorithm for using deep learning convolutional neural networks with three dimensional depth sensor imaging in scoliosis detection. Spine J 21:980–987. https://doi.org/10.1016/j.spinee.2021.01.022 Wu H, Ronsky JL, Poncet P et al (2005) Prediction of scoliosis progression in time series using a hybrid learning technique. Ann Int Conf IEEE Eng Med Biol Proc 7:6452–6455. https://doi.org/10.1109/iembs.2005.1615976 Galbusera F, Niemeyer F, Wilke HJ et al (2019) Fully automated radiological analysis of spinal disorders and deformities: a deep learning approach. Eur Spine J. https://doi.org/10.1007/s00586-019-05944-z Wang H, Zhang T, Cheung KMC et al (2021) Application of deep learning upon spinal radiographs to predict progression in adolescent idiopathic scoliosis at first clinic visit. Clin Med 42:101–220. https://doi.org/10.1016/j.eclinm.2021.101220 Cheuk KY, Zhu TY, Yu FWP et al (2015) Abnormal Bone mechanical and structural properties in adolescent idiopathic scoliosis: a study with finite element analysis and structural model index. Calcif Tissue Int 97:343–352. https://doi.org/10.1007/s00223-015-0025-2 Tajdari M, Pawar A, Li H et al (2021) Image-based modelling for adolescent idiopathic scoliosis: mechanistic machine learning analysis and prediction. Comput Methods Appl Mech Eng 374:113–590. https://doi.org/10.1016/j.cma.2020.113590 Tajdari M, Maqsood A, Li H et al (2021) Artificial intelligence data-driven 3D model for AIS. Studies in health technology and informatics. In: Liu X-C, Thometz JG (eds) Northwestern University McCormick School of Engineering Evanston. IOS Press, IL, pp 141–145 Bagnall KM, Beuerlein M, Johnson P et al (2001) Pineal transplantation after pinealectomy in young chickens has no effect on the development of scoliosis. Spine 26:1022–1027. https://doi.org/10.1097/00007632-200105010-00007 Cheung KM, Wang T, Poon AM et al (2005) The effect of pinealectomy on scoliosis development in young nonhuman primates. Spine 30:2009–2013. https://doi.org/10.1097/01.brs.0000179087.38730.5d O’Kelly C, Wang X, Raso J et al (1999) The production of scoliosis after pinealectomy in young chickens, rats, and hamsters. Spine 24:35–43. https://doi.org/10.1097/00007632-199901010-00009 Machida M, Weinstein SL, Dubousset J (1999) Pathogenesis of idiopathic scoliosis. Spine 24:1985–1989. https://doi.org/10.1007/978-4-431-56541-3 Fagan AB, Kennaway DJ, Oakley AP (2009) Pinealectomy in the chicken: a good model of scoliosis? Eur Spine J 18:1154–1159. https://doi.org/10.1007/s00586-009-0927-7 Beuerlein M, Wang X, Moreau M et al (2001) Development of scoliosis following pinealectomy in young chickens is not the result of an artifact of the surgical procedure. Microsc Res Tech 53:81–86. https://doi.org/10.1002/jemt.1071 Aota Y, Terayama H, Saito T (2013) Pinealectomy in a broiler chicken model impairs endochondral ossification and induces rapid cancellous bone loss. Spine J 13:1607–1616. https://doi.org/10.1016/j.spinee.2013.05.017 Kono H, MacHida M, Saito M et al (2011) Mechanism of osteoporosis in adolescent idiopathic scoliosis: experimental scoliosis in pinealectomized chickens. J Pineal Res 51:387–393. https://doi.org/10.1111/j.1600-079X.2011.00901.x Turgut M, Basaloglu HK, Yenisey Ç et al (2006) Surgical pinealectomy accelerates intervertebral disc degeneration process in chicken. Eur Spine J 15:605–612. https://doi.org/10.1007/s00586-005-0972-9 Machida M, Dubousset J, Imamura Y et al (1994) Pathogenesis of idiopathic scoliosis: SEPs in chicken with experimentally induced scoliosis and in patients with idiopathic scoliosis. J Pediatric Orthop 14:329–335. https://doi.org/10.1097/01241398-199405000-00010 Cheung KM, Wang T, Hu YG et al (2003) Primary thoracolumbar scoliosis in pinealectomized chickens. Spine 28:2499–2504. https://doi.org/10.1097/01.BRS.0000092366.30032.97 Machida M, Yamada H, Yamada T et al (2005) Rib length in experimental scoliosis induced by pinealectomy in chickens. Spine 30:E692–E696. https://doi.org/10.1097/01.brs.0000187874.38074.77 Nette F, Dolynchuk K, Wang X et al (2002) The effects of exposure to intense, 24 h light on the development of scoliosis in young chickens. Stud Health Technol Inform 91:1–6. https://doi.org/10.3233/978-1-60750-935-6-1 Machida M, Dubousset J, Yamada T et al (2006) Experimental scoliosis in melatonin-deficient C57BL/6J mice without pinealectomy. J Pineal Res 41:1–7. https://doi.org/10.1111/j.1600-079X.2005.00312.x Machida M, Miyashita Y, Murai I et al (1997) Role of serotonin for scoliotic deformity in pinealectomized chicken. Spine 22:1297–1301. https://doi.org/10.1097/00007632-199706150-00004 Akel I, Kocak O, Bozkurt G et al (2009) The effect of calmodulin antagonists on experimental scoliosis: a pinealectomized chicken model. Spine 34:533–538. https://doi.org/10.1097/BRS.0b013e31818be0b1 Turhan E, Acaroglu E, Bozkurt G et al (2006) Unilateral enucleation affects the laterality but not the incidence of scoliosis in pinealectomized chicken. Spine 31:133–138. https://doi.org/10.1097/01.brs.0000194781.53260.dc Blecher R, Krief S, Galili T et al (2017) The proprioceptive system masterminds spinal alignment: insight into the mechanism of scoliosis. Dev Cell 42:388–399. https://doi.org/10.1016/j.devcel.2017.07.022 Blecher R, Heinemann-Yerushalmi L, Assaraf E et al (2018) New functions for the proprioceptive system in skeletal biology. Philos Transact R Soc B Biol Sci. https://doi.org/10.1098/rstb.2017.0327 Lafortune P, Aubin CE, Boulanger H et al (2007) Biomechanical simulations of the scoliotic deformation process in the pinealectomized chicken: a preliminary study. Scoliosis 2:1–9. https://doi.org/10.1186/1748-7161-2-16 Somerville EW (1952) Rotational lordosis: the development of the single curve. J Bone Joint Surg 34:421–427. https://doi.org/10.1302/0301-620X.34B3.421 Murray DW, Bulstrode CJ (1996) The development of adolescent idiopathic scoliosis. Eur Spine J 5(4):251–257. https://doi.org/10.1007/BF00301328 Yang Z, Xie Y, Li M (2009) Three-dimensional spring model: a new hypothesis of pathogenesis of adolescent idiopathic scoliosis. Med Hypotheses 73:709–713. https://doi.org/10.1016/j.mehy.2009.02.046 Cheng Y, Shi Y, Xu B et al (2021) The uncoupled anterior and posterior spinal ligament tension (UAPLT)–an improvement to three-dimensional spring model of adolescent idiopathic scoliosis (AIS) pathogenesis. Med Hypotheses 152:10–13. https://doi.org/10.1016/j.mehy.2021.110616 Crijns TJ, Stadhouder A, Smit TH (2017) Restrained differential growth: the initiating event of adolescent Idio- pathic Scoliosis? Spine 42:E726–E732. https://doi.org/10.1097/BRS.0000000000001946 Meade KP, Bunch WH, Vanderby R et al (1987) Progression of unsupported curves in adolescent idiopathic scoliosis. Spine 12:520–526. https://doi.org/10.1097/00007632-198707000-00002 Wu H, Ronsky JL, Cheriet F et al (2010) Prediction of scoliosis progression with serial three-dimensional spinal curves and the artificial progression surface technique. Med Biol Eng Compu 48:1065–1075. https://doi.org/10.1007/s11517-010-0654-6 Kiriyama Y, Watanabe K, Matsumoto M et al (2014) Quantification of the spatial strain distribution of scoliosis using a thin-plate spline method. J Biomech 47:302–307. https://doi.org/10.1016/j.jbiomech.2013.10.013 Neelakantan S, Purohit PK, Pasha S (2021) A reduced-order model of the spine to study pediatric scoliosis. Biomech Model Mechanobiol 20:467–480. https://doi.org/10.1007/s10237-020-01394-5 Veldhuizen AG, Scholten PJ (1987) Kinematics of the scoliotic spine as related to the normal spine. Spine 12:852–858. https://doi.org/10.1097/00007632-198711000-00005 Herzenberg JE, Waanders NA, Closkey RF et al (1990) Cobb angle versus spinous process angle in adolescent idiopathic scoliosis: The relationship of the anterior and posterior deformities. Spine 15:874–879. https://doi.org/10.1097/00007632-199009000-00007 Heidari B, FitzPatrick D, Synnott K et al (2004) Modelling of annulus fibrosus imbalance as an aetio- logical factor in adolescent idiopathic scoliosis. Clin Biomech 19:217–224. https://doi.org/10.1016/j.clinbiomech.2003.12.007 Brun-Cottan B, Assemat P, Doyeux V et al (2021) An energy approach describes spine equilibrium in adolescent idiopathic scoliosis. Biomech Model Mechanobiol 20:359–370. https://doi.org/10.1007/s10237-020-01390-9 Guilbert ML, Raison M, Fortin C et al (2019) Development of a multibody model to assess efforts along the spine for the rehabilitation of adolescents with idiopathic scoliosis. J Musculoskelet Neuronal Interact 19:4–12 Samadi B, Raison M, Achiche S et al (2020) Identification of the most relevant intervertebral effort indicators during gait of adolescents with idiopathic scoliosis. Comput Methods Biomech Biomed Engin 23:664–674. https://doi.org/10.1080/10255842.2020.1758075 Jalalian A, Tay FEH, Arastehfar S et al (2017) A patient-specific multibody kinematic model for representation of the scoliotic spine movement in frontal plane of the human body. Multibody Syst Dyn 39:197–220. https://doi.org/10.1007/s11044-016-9556-1 Jalalian A, Tay FEH, Arastehfar S et al (2017) A new method to approximate load–displacement rela- tionships of spinal motion segments for patient-specific multi-body models of scoliotic spine. Med Biol Eng Compu 55:1039–1050. https://doi.org/10.1007/s11517-016-1576-8 Jalalian A, Tay FEH, Arastehfar S et al (2017) Finding line of action of the force exerted on erect spine based on lateral bending test in personalization of scoliotic spine models. Med Biol Eng Compu 55:673–684. https://doi.org/10.1007/s11517-016-1550-5 Pialasse J-P, Descarreaux M, Mercier P et al (2015) Gait & Posture Sensory reweighting is altered in adolescent patients with scoliosis: evidence from a neuromechanical model. Gait Posture 42:558–563. https://doi.org/10.1016/j.gaitpost.2015.08.013 Vanderby R, Daniele M, Patwardhan A et al (1986) A method for the identification of in-vivo segmental stiffness properties of the spine. J Biomech Eng 108:312–316. https://doi.org/10.1115/1.3138620 Pasha S (2019) 3D Deformation Patterns of S Shaped Elastic Rods as a Pathogenesis Model for Spinal Deformity in Adolescent Idiopathic Scoliosis. Sci Rep 9:1–10. https://doi.org/10.1038/s41598-019-53068-7 Pasha S, de Reuver S, Homans JF et al (2021) Sagittal curvature of the spine as a predictor of the pediatric spinal deformity development. Spine Deform 9:923–932. https://doi.org/10.1007/s43390-020-00279-y Meijer GJ, Homminga J, Hekman EE et al (2010) The effect of three-dimensional geometrical changes during adolescent growth on the biomechanics of a spinal motion segment. J Biomech 43:1590–1597. https://doi.org/10.1016/j.jbiomech.2010.01.028 Pasha S, Aubin CE, Parent S et al (2014) Biomechanical loading of the sacrum in adolescent idiopathic scoliosis. Clin Biomech 29:296–303. https://doi.org/10.1016/j.clinbiomech.2013.12.004 Zhang Q, Chon TE, Zhang Y et al (2021) Finite element analysis of the lumbar spine in adolescent idiopathic scoliosis subjected to different loads. Comput Biol Med 136(104):745. https://doi.org/10.1016/j.compbiomed.2021.104745 Villemure I, Aubin CE, Dansereau J et al (2002) Simulation of progressive deformities in adolescent idiopathic scoliosis using a biomechanical model integrating vertebral growth modulation. J Biomech Eng 124:784–790. https://doi.org/10.1115/1.1516198 Villemure I, Aubin CE, Dansereau J et al (2004) Biomechanical simulations of the spine deformation process in adolescent idiopathic scoliosis from different pathogenesis hypotheses. Eur Spine J 13:83–90. https://doi.org/10.1007/s00586-003-0565-4 Shi L, Wang D, Driscoll M et al (2011) Biomechanical analysis and modeling of different vertebral growth patterns in adolescent idiopathic scoliosis and healthy subjects. Scoliosis 6:2–9. https://doi.org/10.1186/1748-7161-6-11 Huynh AM, Aubin CE, Rajwani T et al (2007) Pedicle growth asymmetry as a cause of adolescent idiopathic scoliosis: a biomechanical study. Eur Spine J 16:523–529. https://doi.org/10.1007/s00586-006-0235-4 Little JP, Adam CJ (2009) The effect of soft tissue properties on spinal flexibility in scoliosis: biomechanical simulation of fulcrum bending. Spine 34:76–82. https://doi.org/10.1097/BRS.0b013e31818ad584 Song XX, Jin LY, Li XF et al (2018) Effects of low bone mineral status on biomechanical characteristics in idiopathic scoliotic spinal deformity. World Neurosurg 110:e321–e329 Aroeira RMC, Pertence AEM, Kemmoku DT et al (2018) The effect of hypokyphosis on the biomechanical behavior of the adolescent thoracic spine. J Braz Soc Mech Sci Eng. https://doi.org/10.1007/s40430-018-1061-4 Sham ML, Zander T, Rohlmann A et al (2008) Effects of the Rib cage on thoracic Spine flexibility. Biomed Eng 50:361–365. https://doi.org/10.1515/bmt.2005.051 Van Der Plaats A, Veldhuizen AG, Verkerke GJ (2007) Numerical simulation of asymmetrically altered growth as initiation mechanism of scoliosis. Ann Biomed Eng 35:1206–1215. https://doi.org/10.1007/s10439-007-9256-3 Schlager B, Niemeyer F, Galbusera F et al (2018) Asymmetrical intrapleural pressure distribution: a cause for scoliosis? A computational analysis. Eur J Appl Physiol 118:1315–1329. https://doi.org/10.1007/s00421-018-3864-5 Grünwald AT, Roy S, Alves-Pinto A et al (2021) Assessment of adolescent idiopathic scoliosis from body scanner image by finite element simulations. PLoS One 16:1–23. https://doi.org/10.1371/journal.pone.0243736 Kamal Z, Rouhi G, Arjmand N et al (2019) A stability-based model of a growing spine with adolescent idiopathic scoliosis: a combination of musculoskeletal and finite element approaches. Med Eng Phys 64:46–55. https://doi.org/10.1016/j.medengphy.2018.12.015 Kamal Z, Rouhi G (2020) Stress distribution changes in growth plates of a trunk with adolescent idiopathic scoliosis following unilateral muscle paralysis: a hybrid musculoskeletal and finite element model. J Biomech 111(109):997. https://doi.org/10.1016/j.jbiomech.2020.109997 Shayestehpour H, Rasmussen J, Galibarov P et al (2021) An articulated spine and ribcage kinematic model for simulation of scoliosis deformities. Multibody Syst Dyn 53:115–134. https://doi.org/10.1007/s11044-021-09787-9 Schmid S, Burkhart KA, Allaire BT et al (2020) Spinal compressive forces in adolescent idiopathic scoliosis with and without carrying loads: a musculoskeletal modeling study. Front Bioeng Biotechnol 8:1–12. https://doi.org/10.3389/fbioe.2020.00159 Barba N, Ignasiak D, Villa TMT et al (2021) Assessment of trunk muscle activation and intervertebral load in adolescent idiopathic scoliosis by musculoskeletal modelling approach. J Biomech 114:110–154. https://doi.org/10.1016/j.jbiomech.2020.110154 Bassani T, Cina A, Ignasiak D et al (2021) Accounting for biomechanical measures from musculoskeletal simulation of upright posture does not enhance the prediction of curve progression in adolescent idiopathic scoliosis. Front Bioeng Biotechnol 9:1–13. https://doi.org/10.3389/fbioe.2021.703144 Stokes IA, Spence H, Aronsson DD et al (1996) Mechanical modulation of vertebral body growth. Implic Scoliosis Progress Spine 16:1162–1167. https://doi.org/10.1097/01241398-199611000-00040