Sensitivity analysis of a patient-specific finite element simulation pipeline incorporating automated vertebral segmentation for predicting vertebral strength of a clinical database.

Abstract

Vertebral metastases compromise bone integrity and may lead to fractures with substantial clinical and economic consequences. Finite element (FE) modeling based on computed tomography (CT) scans enables individualized biomechanical assessment but remains underused clinically due to workflow limitations. To evaluate the sensitivity and accuracy of a patient-specific finite element (FE) simulation pipeline that incorporates automated vertebral segmentation for predicting vertebral strength in metastatic cases. Thirty vertebrae (18 metastatic, 12 healthy) from 12 patients were analyzed using two finite element (FE) models (perfectly elasto-plastic vs. linear elastic) within an automated segmentation pipeline. Intra- and inter-operator reproducibility, sensitivity to boundary condition definition, and model-type comparisons were performed. Failure loads were normalized to derive equivalent stresses. Automated segmentation demonstrated excellent agreement with manual reference (R² = 0.996 p < 0.001; no systematic bias). Sensitivity to operator-defined boundary conditions was minimal (<1%). The elasto-plastic model provided significantly lower failure loads than the linear elastic model (-25% on average). This study supports the feasibility of a fully-automated CT-based finite-element (FE) pipeline for vertebral fracture risk assessment in both healthy and metastatic vertebrae.