Quantitative vertebral morphometry based on parametric modeling of vertebral bodies in 3D

Abstract

Quantitative vertebral morphometry (QVM) was performed by parametric modeling of vertebral bodies in three dimensions (3D). Identification of vertebral fractures in two dimensions is a challenging task due to the projective nature of radiographic images and variability in the vertebral shape. By generating detailed 3D anatomical images, computed tomography (CT) enables accurate measurement of vertebral deformations and fractures. A detailed 3D representation of the vertebral body shape is obtained by automatically aligning a parametric 3D model to vertebral bodies in CT images. The parameters of the 3D model describe clinically meaningful morphometric vertebral body features, and QVM in 3D is performed by comparing the parameters to their statistical values. Thresholds and parameters that best discriminate between normal and fractured vertebral bodies are determined by applying statistical classification analysis. The proposed QVM in 3D was applied to 454 normal and 228 fractured vertebral bodies, yielding classification sensitivity of 92.5% at 7.5% specificity, with corresponding accuracy of 92.5% and precision of 86.1%. The 3D shape parameters that provided the best separation between normal and fractured vertebral bodies were the vertebral body height and the inclination and concavity of both vertebral endplates. The described QVM in 3D is able to efficiently and objectively discriminate between normal and fractured vertebral bodies and identify morphological cases (wedge, (bi)concavity, or crush) and grades (1, 2, or 3) of vertebral body fractures. It may be therefore valuable for diagnosing and predicting vertebral fractures in patients who are at risk of osteoporosis.