Prediction of Collapse Using Patient-Specific Finite Element Analysis of Osteonecrosis of the Femoral Head

Objective: To develop a prediction method for femoral head collapse by using patient-specific finite element analysis of osteonecrosis of the femoral head (ONFH).

Methods: The retrospective study recruited 40 patients with ARCO stage-II ONFH (40 pre-collapse hips). Patients were divided into two groups according to the 1-year follow-up outcomes: patient group without femoral head collapse (noncollapse group, n = 20) and patient group with collapse (collapse group, n = 20). CT scans of the hip were performed for all patients once they joined the study. Patient-specific finite element models were generated based on these original CT images following the same procedures: segmenting the necrotic lesion and viable proximal femur, meshing the computational models, assigning different material properties according to the Hounsfield unit distribution, simulating the stress loading of the slow walking gait, and measuring the distribution of the von Mises stress. Receiver operating characteristic (ROC) curve analysis was used to evaluate the predictive performance of the maximum level of the von Mises stress. The optimal cut-off value was selected based on the Youden index and the corresponding predictive accuracy was reported as well.

Results: The mean level of the maximum von Mises stress in the collapse group was 2.955 ± 0.539 MPa, whereas the mean stress level in the noncollapse group was 1.923 ± 0.793 MPa (P < 0.01). ROC analysis of the maximum von Mises stress found that the area under the ROC curve was 0.842 (95% CI: 0.717-0.968, P < 0.01). The maximum Youden index was 0.60, which corresponded to two optimal cut-off values: 2.7801 MPa (sensitivity: 0.70; specificity: 0.90; predictive accuracy: 80.00%; LR+: 7), and 2.7027 MPa (sensitivity: 0.75; specificity: 0.85; predictive accuracy: 77.50%; LR+: 5).

Conclusion: Finite element analysis is a potential method for femoral head collapse prediction among pre-collapse ONFH patients. The maximum level of the von Mises stress on the weight-bearing surface of the femoral head could be a good biomechanical marker to classify the collapse risk. The collapse prediction method based on patient-specific finite element analysis is, thus, suitable to apply to clinical practice, but further testing on a larger dataset is desirable.