Refining muscle geometry and wrapping in the TLEM 2 model for improved hip contact force prediction

Abstract

Musculoskeletal models represent a powerful tool to gain knowledge on the internal forces acting at the joint level in a non-invasive way. However, these models can present some errors associated with the level of detail in their geometrical representation. For this reason, a thorough validation is necessary to prove the reliability of their predictions. This study documents the development of a generic musculoskeletal model and proposes a working logic and simulation techniques for identifying specific model features in need of refinement; as well as providing a quantitative validation for the prediction of hip contact forces (HCF). The model, implemented in the AnyBody Modeling System and based on the cadaveric dataset TLEM 2.0, was scaled to match the anthropometry of a patient fitted with an instrumented hip implant and to reproduce gait kinematics based on motion capture data. The relative contribution of individual muscle elements to the HCF and joint moments was analyzed to identify critical geometries, which were then compared to muscle magnetic resonance imaging (MRI) scans and, in case of inconsistencies, were modified to better match the volumetric scans. The predicted HCF showed good agreement with the overall trend and timing of the measured HCF from the instrumented prosthesis. The average root mean square error (RMSE), calculated for the total HCF was found to be 0.298*BW. Refining the geometries of the muscles thus identified reduced RMSE on HCF magnitudes by 17% (from 0.359*BW to 0.298*BW) over the whole gait cycle. The detailed study of individual muscle contributions to the HCF succeeded in identifying muscles with incorrect anatomy, which would have been difficult to intuitively identify otherwise. Despite a certain residual over-prediction of the final hip contact forces in the stance phase, a satisfactory level of geometrical accuracy of muscle paths has been achieved with the refinement of this model.

Fig 1. Free-body diagram of the leg for the calculation of muscle contribution to HCF.

The directions of the force arrows are chosen to aid intuition. In reality, the sign convention for forces in Eq 1 should be fixed such that a positive force will always pull (or push) the system.

Fig 2. New wrapping surfaces for Gluteus Maximus.

Each muscle element has its own wrapping cylinder (in red). The cylinders are aligned to match the overall muscle shape, and constructed to follow the underlying pelvis bone geometry. Figure a. (from posterior) show all the wrapping surfaces of the 12 strands of the muscle, while figure b. (sagittal) highlights a single cylinder for the most distal strand of the Gluteus Maximus Inferior.

Fig 3. New origins for Gluteus Medius and Minimus.

New origin points for the Gluteus Medius (a.) and Gluteus Minimus (b.) compared the segmented muscles (in blue) from the original cadaver MRI scans.

Fig 4. New wrapping surfaces for Iliacus and Psoas.

New wrapping surfaces (red cylinder) for Iliacus (a.) and Psoas (b.) muscles compared to segmented muscles (in blue) from the original MRI scans.

Fig 5. New wrapping surfaces for knee flexors.

Wrapping cylinder (in red) of Semimembranosus, Semitendinosus, and Bicep Femoris elements (a.), and Gastrocnemius (b.) around the femoral condyles, compared to the segmented muscles from the original cadaver MRI scans (in blue).

Fig 6. New line of action for Tensor Fasciae Latae.

New lines of action for Tensor Fasciae Latae elements with muscle path points defined inferiorly to the surface of the trochanter.

Fig 7. Predicted and measured HCF over a gait cycle.

HCF predicted by the musculoskeletal model before (dashed lines) and after (solid dark lines) muscle wrapping modifications compared to the measured HCF from the instrumented implant (solid shaded lines) [8,29]. The upper plot reports the total HCF magnitude (in black), while the bottom one reports the single HCF components: medio-lateral (MD) in green, antero-posterior (AP) in blue, and proximo-distal (PD) in red.

Fig 8. Predicted muscle activations during gait vs. average timing of EMGs.

Comparison between predicted muscle activations and average “on-off” timing of EMG signals reported for THR patients by Agostini et al. [36].