The use of a hip endoprosthesis due to degenerative diseases of the hip joint is the most frequently performed joint replacement worldwide. Preoperative planning of the implantation taking into account the individual morphology based on medical image data is standard in clinical practice. Although it is proven in the literature that functional parameters, such as the resulting hip joint force and sagittal pelvic tilt, are of high importance for the surgical success, they are routinely not considered in the preoperative planning. This is mainly due to the increased technical and time-consuming as well as cost-intensive effort to estimate these postoperative parameters.
The project therefore investigates the accuracies with which the postoperative functional parameters hip joint force and pelvic tilt can be predicted by preoperative estimation using morpho-functional models in routine clinical practice, and to what extent these results correlate with postoperative clinical follow-up examinations of therapy outcome quality. For the prediction of hip joint strength, on the one hand, the previously required patient-specific motion data for simulation by means of complex multibody simulation will be replaced by statistical modeling of parameterized motion data. As a second method, simplified analytical models will be used to determine hip joint force for the most important activities of daily living. Both methods will be validated with data from instrumented hip implants in the OrthoLoad database. To predict functional pelvic tilt, pre- and postoperative CT and EOS datasets are correlated with morphological parameters of the bony pelvis. The modeling approaches will then be integrated into a computer-based planning system and evaluated against clinical data.
The project MoFuMo is funded by the German Research Foundation.