Femoral version impacts the long-term functioning of the femoroacetabular joint. Accurate measurements of version are thus required for success in total hip arthroplasties and hip reconstructive surgeries. These are impossible to obtain without visualization of the distal femur, which is often unavailable preoperatively as the majority of imaging scans are isolated to the pelvis and proximal femur. We developed an automated algorithm for identifying the major landmarks of the femur. These landmarks were then used to identify proximal axes and create a statistical shape model of the proximal femur across 144 asymptomatic femora. With six proximal axes selected, and 200 parameters (distances and angles between points) from the shape model measured, the best-fitting linear correlation was found. The difference between true version and version predicted by this model was 0.00 ± 5.13° with a maximum overestimation and underestimation of 11.80 and 15.35°, respectively. The mean absolute difference was 4.14°. This model and its prediction of femoral version are a substantial improvement over pre-operative 2D or intra-operative visual estimation measures. © 2018 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 36:3161-3168, 2018.
Keywords: FAI and morphology; artifacts; diagnostic imaging; hip and knee arthroplasty; hip, computational modeling; novel and functional imaging.
© 2018 Orthopaedic Research Society. Published by Wiley Periodicals, Inc.