Morpho-functional modeling for patient-specific planning in total hip arthroplasty (MoFuMo)

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.

Funding

The project MoFuMo is funded by the German Research Foundation.

Partner

  • Julius Wolff Institut, Charité, Berlin (JWI)
  • Kameda Daiichi Hospital, Niigata Hip Joint Center, Japan

Related Topics

Publications

  • L. Berger, K. Tokunaga & K. Radermacher: Correlation between score values and morphofunctional parameters in THA. In: J.W. Giles (ed.): Proceedings of The 22nd Annual Meeting of the International Society for Computer Assisted Orthopaedic Surgery, 6, 2024, pp. 1-3 [DOI: 10.29007/zb7x]
  • L. Berger, K. Tokunaga & K. Radermacher: Approach towards psoas syndrome risk modeling in preoperative planning for THA. In: J.W. Giles (ed.): Proceedings of The 22nd Annual Meeting of the International Society for Computer Assisted Orthopaedic Surgery, 6, 2024, pp. 4-7 [DOI: 10.29007/4cld]
  • M.C.M. Fischer, S.A.G.A. Grothues, J. Habor, M. de la Fuente & K. Radermacher: A robust method for automatic identification of femoral landmarks, axes, planes and bone coordinate systems using surface models. Scientific Reports, 2020, 10(20859), pp. 1-11 [DOI: 10.1038/s41598-020-77479-z]
  • M.C.M. Fischer, K. Tokunaga, M. Okamoto, J. Habor & K. Radermacher: Preoperative factors improving the prediction of the postoperative sagittal orientation of the pelvis in standing position after total hip arthroplasty. Scientific Reports, 2020, 10(15944), pp. 1-10 [DOI: 10.1038/s41598-020-72782-1]
  • M.C.M. Fischer, F. Krooß, J. Habor & K. Radermacher: A robust method for automatic identification of landmarks on surface models of the pelvis. Scientific Reports, 2019, 9(13322), pp. 1-10 [DOI: 10.1038/s41598-019-49573-4]
  • M.C.M. Fischer, K. Tokunaga, M. Okamoto & K. Radermacher: Proximal Femoral Asymmetry in Japanese Patients before Total Hip Arthroplasty. In: P. Meere & F. Rodriguez Y Baena (ed.): CAOS 2019. The 19th Annual Meeting of the International Society for Computer Assisted Orthopaedic Surgery, 3, 2019, pp. 127-132 [DOI: 10.29007/ms33]
  • M.C.M. Fischer, S. Schörner, S. Rohde, C. Lüring & K. Radermacher: Relationship between pelvic morphology and functional parameters in standing position for patient-specific cup planning in THA. In: K. Radermacher & F. Rodriguez Y Baena (ed.): CAOS2017. EPiC Series in Health Sciences, 1, 2017, pp. 88-92 [DOI: 10.29007/41f9]

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