Seeing the spine in 3D: how will it change what we do?
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Updated: Jun 5, 2026
Three and Four-Dimensional Visualization and Analysis Approaches to Study Vertebrate Axial Elongation and Segmentation
Published on: February 28, 2021
Hubert Labelle1, Carl-Eric Aubin, Roger Jackson
1Division of Orthopaedic Surgery, CHU Sainte-Justine, University of Montreal, Montreal. hubert.labelle@umontreal.ca
Background:
The Scoliosis Research Society (SRS) has appointed a committee to evaluate the clinical relevance and impact of 3D analysis on scoliotic deformities and to develop a 3D classification of adolescent idiopathic scoliosis (AIS). The goal of this article is to summarize and present the work done in recent years within this committee and show how 3D analysis of AIS has the potential to change our current methods to analyse and treat scoliosis.
Methods:
A database of 600 3D reconstructions of the spine of patients with AIS has been established using calibrated PA and lateral radiographs obtained from either digital radiographs or the EOS system. The 3D reconstructions were done using dedicated software and analyzed with the "da Vinci" view, a schematic top view representation of the 3D reconstructions, which summarizes the position of the End-Apex-End vertebrae planes (planes of maximum curvature).
Results:
Preliminary work was done using 3D reconstructions in 409 patients with AIS. Fuzzy clustering techniques were used to show that the cohort could be segmented in 5 easily differentiated curve patterns similar to those of the Lenke and King classifications. Two subsequent articles have shown that 3D reconstructions can be divided in different groups based on the location of the plane of maximum curvature of their curves. One study of 66 cases has shown a consistent loss of kyphosis within the 5 thoracic apical vertebrae. Finally, a study of 172 Lenke 1 curves analyzed by ISO Data cluster analysis has confirmed the presence of 2 statistically different subtypes according to the planes passing through the End-Apex-End vertebrae of the main thoracic curve.
Conclusions:
The study presented suggests that a valid and clinically useful 3D classification of AIS is within reach. 3D analysis has the potential to improve our comprehension of AIS curve types and automatic 3D classification may help decrease the known variability of current 2D classifications.
Level Of Evidence:
Level III, systematic review of retrospective comparative studies.
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