An MRI-Based Patient-Specific Computational Framework for the Calculation of Range of Motion of Total Hip Replacements

The calculation of range of motion (ROM) is a key factor during preoperative planning of total hip replacements (THR), to reduce the risk of impingement and dislocation of the artificial hip joint. To support the preoperative assessment of THR, a magnetic resonance imaging (MRI)-based computational framework was generated; this enabled the estimation of patient-specific ROM and type of impingement (bone-to-bone, implant-to-bone, and implant-to-implant) postoperatively, using a three-dimensional computer-aided design (CAD) to visualize typical clinical joint movements. Hence, patient-specific CAD models from 19 patients were generated from MRI scans and a conventional total hip system (Bicontact(R) hip stem and Plasmacup(R) SC acetabular cup with a ceramic-on-ceramic bearing) was implanted virtually. As a verification of the framework, the ROM was compared between preoperatively planned and the postoperatively reconstructed situations; this was derived based on postoperative radiographs (n = 6 patients) during different clinically relevant movements. The data analysis revealed there was no significant difference between preoperatively planned and postoperatively reconstructed ROM ( increment (ROM)) of maximum flexion ( increment (ROM) = 0 degrees, p = 0.854) and internal rotation ( increment (ROM) = 1.8 degrees, p = 0.917). Contrarily, minor differences were observed for the ROM during maximum external rotation ( increment (ROM) = 9 degrees, p = 0.046). Impingement, of all three types, was in good agreement with the preoperatively planned and postoperatively reconstructed scenarios during all movements. The calculated ROM reached physiological levels during flexion and internal rotation movement; however, it exceeded physiological levels during external rotation. Patients, where implant-to-implant impingement was detected, reached higher ROMs than patients with bone-to-bone impingement. The proposed framework provides the capability to predict postoperative ROM of THRs.