Spectral Shape Analysis of Human Torsos: Application to the Evaluation of Scoliosis Surgery Outcome.

This paper aims at evaluating the effect of spinal surgery on the torso shape appearance of adolescent patients. Current methods that assess the surgical outcome on the trunk shape are limited to its global asymmetry or rely on unreliable manual measurements. We introduce a novel framework to evaluate pre- to postoperative local asymmetry changes using a spectral representation of the torso shape, more specifically, the Laplacian spectrum (eigenvalues and eigenvectors) of a graph. We conduct a statistical analysis on the eigenvalues to efficiently select the spectral space and determine the significant components between preop and postop groups. On the selected eigenvectors, we propose a local analysis based on the concept of Euler characteristic to detect their local maxima and minima, which are then used to compute local left-right (L-R) asymmetries of torso shape. On 49 patients with a thoracic spinal deformity, the method captures significant pre- to postoperative changes of asymmetry at the waist, shoulder blades, shoulders, and breasts. We have evaluated average correction rates for L-R asymmetry of the waist height (67%), shoulder-blade height (64%) and depth (67%), lateral offset between shoulder and neck (61%), and breast height (52%). Spectral torso shape analysis provides a novel approach to quantify the surgical correction of the scoliotic trunk from local shape asymmetry. The proposed method could help the surgeon to understand the impact of different spinal surgery strategies on the postoperative appearance and choose the one that should provide better patient's satisfaction.