European Spine Journal

, Volume 28, Issue 9, pp 1970–1976 | Cite as

Quasi-automatic early detection of progressive idiopathic scoliosis from biplanar radiography: a preliminary validation

  • Claudio VergariEmail author
  • Laurent Gajny
  • Isabelle Courtois
  • Eric Ebermeyer
  • Kariman Abelin-Genevois
  • Youngwoo Kim
  • Tristan Langlais
  • Raphael Vialle
  • Ayman Assi
  • Ismat Ghanem
  • Jean Dubousset
  • Wafa Skalli
Original Article



To validate the predictive power and reliability of a novel quasi-automatic method to calculate the severity index of adolescent idiopathic scoliosis (AIS).


Fifty-five AIS patients were prospectively included (age 10–15, Cobb 16° ± 4°). Patients underwent low-dose biplanar X-rays, and a novel fast method for 3D reconstruction of the spine was performed. They were followed until skeletal maturity (stable patients) or brace prescription (progressive patients). The severity index was calculated at the first examination, based on 3D parameters of the scoliotic curve, and it was compared with the patient’s final outcome (progressive or stable). Three operators have repeated the 3D reconstruction twice for a subset of 30 patients to assess reproducibility (through Cohen’s kappa and intra-class correlation coefficient).


Eighty-five percentage of the patients were correctly classified as stable or progressive by the severity index, with a sensitivity of 92% and specificity of 74%. Substantial intra-operator agreement and good inter-operator agreement were observed, with 80% of the progressive patients correctly detected at the first examination. The novel severity index assessment took less than 4 min of operator time.


The fast and semiautomatic method for 3D reconstruction developed in this work allowed for a fast and reliable calculation of the severity index. The method is fast and user friendly. Once extensively validated, this severity index could allow very early initiation of conservative treatment for progressive patients, thus increasing treatment efficacy and therefore reducing the need for corrective surgery.

Graphical abstract

These slides can be retrieved under Electronic Supplementary Material.


Adolescent idiopathic scoliosis 3D reconstruction Reliability Feature extraction Severity index 



The authors are grateful to the ParisTech BiomecAM chair program on subject-specific musculoskeletal modeling (with the support of ParisTech and Yves Cotrel Foundations, Société Générale, Proteor and Covea).

Compliance with ethical standards

Conflict of interest

Wafa Skalli holds patents related to the EOS system and associated 3D reconstruction methods, with no personal financial benefit (royalties rewarded for research and education). Raphael Vialle received consulting fees from EOS Imaging unrelated to this study.

Supplementary material

586_2019_5998_MOESM1_ESM.pptx (141 kb)
Supplementary material 1 (PPTX 141 kb)


  1. 1.
    Negrini S, Donzelli S, Aulisa AG et al (2018) 2016 SOSORT guidelines: orthopaedic and rehabilitation treatment of idiopathic scoliosis during growth. Scoliosis Spinal Disord 13:3. CrossRefGoogle Scholar
  2. 2.
    Weinstein SL, Dolan LA, Wright JG, Dobbs MB (2013) Effects of bracing in adolescents with idiopathic scoliosis. N Engl J Med 369:1512–1521. CrossRefGoogle Scholar
  3. 3.
    Negrini S, Minozzi S, Bettany-Saltikov J, et al (2015) Braces for idiopathic scoliosis in adolescents. Cochrane database Syst Rev 6:CD006850.
  4. 4.
    Roussouly P, Labelle H, Rouissi J, Bodin A (2013) Pre- and post-operative sagittal balance in idiopathic scoliosis: a comparison over the ages of two cohorts of 132 adolescents and 52 adults. Eur Spine J 22:203–215. CrossRefGoogle Scholar
  5. 5.
    Grivas TB, Hresko MT, Labelle H et al (2013) The pendulum swings back to scoliosis screening: screening policies for early detection and treatment of idiopathic scoliosis—current concepts and recommendations. Scoliosis 8:16. CrossRefGoogle Scholar
  6. 6.
    Hresko MT, Talwalkar V, Schwend R et al (2016) Early detection of idiopathic scoliosis in adolescents. J Bone Joint Surg Am 98:e67. CrossRefGoogle Scholar
  7. 7.
    Mehta MH (1972) The rib-vertebra angle in the early diagnosis between resolving and progressive infantile scoliosis. J Bone Jt Surg Br Vol 54-B:230–243CrossRefGoogle Scholar
  8. 8.
    De Korvin G, Randriaminahisoa T, Cugy E et al (2014) Detection of progressive idiopathic scoliosis during growth using back surface topography: a prospective study of 100 patients. Ann Phys Rehabil Med 57:629–639. CrossRefGoogle Scholar
  9. 9.
    Poncet P, Dansereau J, Labelle H (2001) Geometric torsion in idiopathic scoliosis: three-dimensional analysis and proposal for a new classification. Spine (Phila Pa 1976) 26:2235–2243CrossRefGoogle Scholar
  10. 10.
    Kong Y, Shi L, Hui SCN et al (2014) Variation in anisotropy and diffusivity along the medulla oblongata and the whole spinal cord in adolescent idiopathic scoliosis: a pilot study using diffusion tensor imaging. Am J Neuroradiol 35:1621 LP–1627CrossRefGoogle Scholar
  11. 11.
    Perdriolle R, Vidal J (1981) A study of scoliotic curve. The importance of extension and vertebral rotation (author’s transl). Rev Chir Orthop Reparatrice Appar Mot 67:25–34Google Scholar
  12. 12.
    Dubousset J (1994) Three-dimensional analysis of the scoliotic deformity. In: Weinstein SL (ed) The pediatric spine: principles and practice. Raven Press Ltd., New York, pp 479–496Google Scholar
  13. 13.
    Skalli W, Vergari C, Ebermeyer E et al (2017) Early detection of progressive adolescent idiopathic scoliosis: a severity index. (Phila Pa 1976) 42:823–830CrossRefGoogle Scholar
  14. 14.
    Faro FD, Marks MC, Pawelek J, Newton PO (2004) Evaluation of a functional position for lateral radiograph acquisition in adolescent idiopathic scoliosis. Spine (Phila Pa 1976) 29:2284–2289CrossRefGoogle Scholar
  15. 15.
    Danielsson AJ, Hasserius R, Ohlin A, Nachemson AL (2007) A prospective study of brace treatment versus observation alone in adolescent idiopathic scoliosis: a follow-up mean of 16 years after maturity. Spine (Phila Pa 1976) 32:2198–2207. CrossRefGoogle Scholar
  16. 16.
    Bunnell WP (1986) The natural history of idiopathic scoliosis before skeletal maturity. Spine (Phila Pa 1976) 11:773–776CrossRefGoogle Scholar
  17. 17.
    Di Felice F, Zaina F, Donzelli S, Negrini S (2018) The natural history of idiopathic scoliosis during growth: a meta-analysis. Am J Phys Med Rehabil 97:346–356. CrossRefGoogle Scholar
  18. 18.
    Bujang MA, Adnan TH (2016) Requirements for minimum sample size for sensitivity and specificity analysis. J Clin Diagn Res 10:YE01–YE06. Google Scholar
  19. 19.
    Lonstein JE, Carlson JM (1984) The prediction of curve progression in untreated idiopathic scoliosis during growth. J Bone Jt Surg Am 66:1061–1071CrossRefGoogle Scholar
  20. 20.
    Humbert L, De Guise JA, Aubert B et al (2009) 3D reconstruction of the spine from biplanar X-rays using parametric models based on transversal and longitudinal inferences. Med Eng Phys 31:681–687. CrossRefGoogle Scholar
  21. 21.
    Gajny L, Ebrahimi S, Vergari C et al (2018) Quasi-automatic 3D reconstruction of the full spine from low-dose biplanar X-rays based on statistical inferences and image analysis. Eur Spine J. Google Scholar
  22. 22.
    Ebrahimi S, Angelini E, Gajny L, Skalli W (2016) Lumbar spine posterior corner detection in X-rays using Haar-based features. In: IEEE 13th international symposium on biomedical imaging (ISBI), pp 180–183Google Scholar
  23. 23.
    Ebrahimi S, Gajny L, Skalli W, Angelini E (2018) Vertebral corners detection on sagittal X-rays based on shape modelling, random forest classifiers and dedicated visual features. Comput Methods Biomech Biomed Eng Imaging Vis. Google Scholar
  24. 24.
    Landis JR, Koch GG (1977) The measurement of observer agreement for categorical data. Biometrics 33:159–174. CrossRefGoogle Scholar
  25. 25.
    Pomero V, Mitton D, Laporte S et al (2004) Fast accurate stereoradiographic 3D-reconstruction of the spine using a combined geometric and statistic model. Clin Biomech 19:240–247. CrossRefGoogle Scholar
  26. 26.
    Kohashi Y, Oga M, Sugioka Y (1996) A new method using top views of the spine to predict the progression of curves in idiopathic scoliosis during growth. Spine (Phila Pa 1976) 21:212–217CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  • Claudio Vergari
    • 1
    Email author
  • Laurent Gajny
    • 1
  • Isabelle Courtois
    • 2
  • Eric Ebermeyer
    • 2
  • Kariman Abelin-Genevois
    • 3
  • Youngwoo Kim
    • 1
  • Tristan Langlais
    • 4
  • Raphael Vialle
    • 4
  • Ayman Assi
    • 5
  • Ismat Ghanem
    • 5
  • Jean Dubousset
    • 1
  • Wafa Skalli
    • 1
  1. 1.LBM/Institut de Biomécanique Humaine Georges CharpakArts et Métiers ParisTechParisFrance
  2. 2.Unite RachisCHU - Hospital BellevueSaint-ÉtienneFrance
  3. 3.Department of Orthopaedic SurgeryCentre médico-chirurgical et de réadaptation des MassuesLyonFrance
  4. 4.Department of Paediatric Orthopaedics, Armand Trousseau Hospital, APHPSorbonne UniversityParisFrance
  5. 5.Laboratory of Biomechanics and Medical Imaging, Faculty of MedicineUniversity of Saint-JosephBeirutLebanon

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