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Classification of Spinal Deformities Using a Parametric Torsion Estimator

  • Jesse Shen
  • Stefan Parent
  • Samuel KadouryEmail author
Conference paper
Part of the Lecture Notes in Computational Vision and Biomechanics book series (LNCVB, volume 17)

Abstract

Adolescent idiopathic scoliosis (AIS) is a 3D deformity of the spine. However, the most widely accepted and used classification systems still rely on the 2D aspects of X-rays. Yet, a 3D classification of AIS remains elusive as there is no widely accepted 3D parameter in the clinical practice. The goal of this work is to propose a true 3D parameter that quantifies the torsion in thoracic AIS and automatically classifies patients in appropriate 3D sub-groups based on their diagnostic biplanar X-rays. First, an image-based approach anchored on prior statistical distributions is used to reconstruct the spine in 3D from biplanar X-rays. Geometric torsion measuring the twisting effect of the spine is then estimated using a novel technique that approximates local arc-lengths with parametric curve fitting at the neutral vertebra in the thoracolumbar/lumbar segment. We evaluated the method with a case series analysis of 255 patients with thoracic spine deformations recruited at our institution. The torsion index was evaluated in the thoracolumbar/lumbar junction in 3 sub-groups stratified by their lumbar modifier. An improvement in torsion estimation stability (\(\mathrm{mm }^{-1}\)) was observed in comparison to a previous approach. An automatic classification based on torsion indices identified two groups: one with high torsion values (\(2.81\,\mathrm{mm }^{-1}\)) and one with low torsion values (\(0.60\,\mathrm{mm }^{-1}\)), showing the existence of two sub-groups of 3D deformations stemming from the same 2Dclass.

Keywords

Adolescent Idiopathic Scoliosis Cobb Angle Spinal Curve Apical Vertebra Scoliotic Spine 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.CHU Sainte-Justine Research CenterMontréalCanada
  2. 2.CHU Sainte-Justine Research Center, Department of SurgeryUniversité de MontréalMontréalCanada
  3. 3.CHU Sainte-Justine Research Center, MEDICALÉcole Polytechnique de MontréalMontréalCanada

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