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Current models to understand the onset and progression of scoliotic deformities in adolescent idiopathic scoliosis: a systematic review

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Abstract

Purpose

To create an updated and comprehensive overview of the modeling studies that have been done to understand the mechanics underlying deformities of adolescent idiopathic scoliosis (AIS), to predict the risk of curve progression and thereby substantiate etiopathogenetic theories.

Methods

In this systematic review, an online search in Scopus and PubMed together with an analysis in secondary references was done, which yielded 86 studies. The modeling types were extracted and the studies were categorized accordingly.

Results

Animal modeling, together with machine learning modeling, forms the category of black box models. This category is perceived as the most clinically relevant. While animal models provide a tangible idea of the biomechanical effects in scoliotic deformities, machine learning modeling was found to be the best curve-progression predictor. The second category, that of artificial models, has, just as animal modeling, a tangible model as a result, but focusses more on the biomechanical process of the scoliotic deformity. The third category is formed by computational models, which are very popular in etiopathogenetic parameter-based studies. They are also the best in calculating stresses and strains on vertebrae, intervertebral discs, and other surrounding tissues.

Conclusion

This study presents a comprehensive overview of the current modeling techniques to understand the mechanics of the scoliotic deformities, predict the risk of curve progression in AIS and thereby substantiate etiopathogenetic theories. Although AIS remains to be seen as a complex and multifactorial problem, the progression of its deformity can be predicted with good accuracy. Modeling of AIS develops rapidly and may lead to the identification of risk factors and mitigation strategies in the near future. The overview presented provides a basis to follow this development.

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Adapted from Crijns et al. [34], with permission

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Adapted from Grünwald et al. [62], permission requested

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Adapted from Barba et al. [67], permission requested

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References

  1. 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

    Article  PubMed  Google Scholar 

  2. 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

    Article  PubMed  PubMed Central  Google Scholar 

  3. 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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. 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

    Article  PubMed  PubMed Central  Google Scholar 

  5. 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

    Article  PubMed  Google Scholar 

  6. Smit TH (2020) Adolescent idiopathic scoliosis: The mechanobiology of differential growth. JOR Spine 3:1–13. https://doi.org/10.1002/jsp2.1115

    Article  Google Scholar 

  7. Breedveld P, Herder JL, Tomiyama T (2022) Teaching creativity in mechanical design. Delft. https://doi.org/10.5281/ZENODO.5849490

    Article  Google Scholar 

  8. 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

    Article  PubMed  Google Scholar 

  9. 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

    Article  PubMed  Google Scholar 

  10. 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

    Article  PubMed  Google Scholar 

  11. 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

    Article  Google Scholar 

  12. 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

    Article  PubMed  Google Scholar 

  13. 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

    Article  Google Scholar 

  14. 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

    Article  PubMed  Google Scholar 

  15. 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

    Article  PubMed  Google Scholar 

  16. 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

    Article  PubMed  Google Scholar 

  17. 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

    Article  CAS  Google Scholar 

  18. 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

    Article  Google Scholar 

  19. 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

    Article  CAS  PubMed  Google Scholar 

  20. 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

    Article  PubMed  PubMed Central  Google Scholar 

  21. 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

    Article  PubMed  Google Scholar 

  22. 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

    Article  Google Scholar 

  23. 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

    Article  PubMed  Google Scholar 

  24. 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

    Article  CAS  Google Scholar 

  25. 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

    Article  CAS  PubMed  Google Scholar 

  26. 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

    Article  Google Scholar 

  27. 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

    Google Scholar 

  28. 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

    Article  CAS  PubMed  Google Scholar 

  29. 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

    Article  PubMed  Google Scholar 

  30. 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

    Article  PubMed  Google Scholar 

  31. 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

    Article  CAS  PubMed  Google Scholar 

  32. 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

    Article  PubMed  PubMed Central  Google Scholar 

  33. 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

    Article  CAS  PubMed  Google Scholar 

  34. 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

    Article  PubMed  Google Scholar 

  35. 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

    Article  CAS  PubMed  Google Scholar 

  36. 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

    Article  PubMed  Google Scholar 

  37. 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

    Article  CAS  Google Scholar 

  38. 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

    Article  PubMed  Google Scholar 

  39. 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

    Article  PubMed  Google Scholar 

  40. 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

    Article  PubMed  Google Scholar 

  41. 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

    Article  CAS  PubMed  Google Scholar 

  42. 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

    Article  CAS  PubMed  Google Scholar 

  43. 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

    Article  PubMed  Google Scholar 

  44. 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

    Article  PubMed  Google Scholar 

  45. 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

    Article  CAS  PubMed  Google Scholar 

  46. 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

    Article  Google Scholar 

  47. 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

    Article  Google Scholar 

  48. 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

    Article  Google Scholar 

  49. Murray DW, Bulstrode CJ (1996) The development of adolescent idiopathic scoliosis. Eur Spine J 5(4):251–257. https://doi.org/10.1007/BF00301328

    Article  CAS  PubMed  Google Scholar 

  50. 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

    Article  PubMed  Google Scholar 

  51. 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

    Article  Google Scholar 

  52. 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

    Article  PubMed  Google Scholar 

  53. 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

    Article  CAS  PubMed  Google Scholar 

  54. 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

    Article  Google Scholar 

  55. 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

    Article  PubMed  Google Scholar 

  56. 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

    Article  PubMed  Google Scholar 

  57. 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

    Article  CAS  PubMed  Google Scholar 

  58. 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

    Article  CAS  PubMed  Google Scholar 

  59. 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

    Article  Google Scholar 

  60. 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

    Article  PubMed  Google Scholar 

  61. 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

    PubMed  PubMed Central  Google Scholar 

  62. 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

    Article  Google Scholar 

  63. 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

    Article  Google Scholar 

  64. 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

    Article  Google Scholar 

  65. 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

    Article  Google Scholar 

  66. 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

    Article  PubMed  Google Scholar 

  67. 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

    Article  PubMed  Google Scholar 

  68. 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

    Article  CAS  Google Scholar 

  69. 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

    Article  PubMed  Google Scholar 

  70. 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

    Article  CAS  PubMed  Google Scholar 

  71. 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

    Article  Google Scholar 

  72. 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

    Article  CAS  Google Scholar 

  73. 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

    Article  CAS  PubMed  Google Scholar 

  74. 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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  75. 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

    Article  Google Scholar 

  76. 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

    Article  PubMed  Google Scholar 

  77. 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

    Article  Google Scholar 

  78. 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

    Article  PubMed  Google Scholar 

  79. 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

    Article  Google Scholar 

  80. 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

    Article  Google Scholar 

  81. 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

    Article  PubMed  PubMed Central  Google Scholar 

  82. 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

    Article  CAS  PubMed  Google Scholar 

  83. 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

    Article  CAS  Google Scholar 

  84. 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

    Article  PubMed  Google Scholar 

  85. 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

    Article  Google Scholar 

  86. 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

    Article  Google Scholar 

  87. 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

    Article  Google Scholar 

  88. 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

    Article  Google Scholar 

  89. 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

    Article  Google Scholar 

  90. 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

    Article  Google Scholar 

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ARM: conception of the work, drafting the work, final approval, accountability agreement. EK: conception of the work, revising the work, final approval, accountability agreement. AS: interpretation of the work, revising the work, final approval, accountability agreement. BJR: interpretation of the work, revising the work, final approval, accountability agreement. PB: analysis of the work, revising the work, final approval, accountability agreement. THS: analysis of the work, revising the work, final approval, accountability agreement.

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Correspondence to T. H. Smit.

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Meiring, A.R., de Kater, E.P., Stadhouder, A. et al. Current models to understand the onset and progression of scoliotic deformities in adolescent idiopathic scoliosis: a systematic review. Spine Deform 11, 545–558 (2023). https://doi.org/10.1007/s43390-022-00618-1

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