Classification of Spinal Deformities Using a Parametric Torsion Estimator

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.