# Do we need medical imaging-informed musculoskeletal models for simulations in healthy adults? A new workflow based on magnetic resonance imaging highlights the importance of personalized geometry

## TL;DR

This study shows that personalized musculoskeletal models based on MRI data are important even for healthy adults, as they capture anatomical differences that generic models miss, leading to more accurate joint force estimates.

## Contribution

A semi-automatic workflow for creating MRI-based musculoskeletal models is introduced, demonstrating the importance of personalization in healthy adults.

## Key findings

- MRI-based models showed wider pelvis and different femur/tibia proportions compared to generic-scaled models.
- MRI-based models produced higher peak joint contact forces with greater individual variation, especially at the knee.
- Personalized models captured anatomical sex differences absent in generic models and aligned well with cadaver data.

## Abstract

Musculoskeletal simulations often rely on generic models that may fail to accurately represent individual anatomy. While personalization using medical imaging can enhance model accuracy, it is often assumed to be more critical for pathological cases or pediatric populations, as generic models are typically based on healthy adults. However, even in healthy adults, generic models may not capture individual anatomical variability. In this study, we present a semi-automatic workflow for creating personalized musculoskeletal models based on magnetic resonance imaging (MRI). Our workflow concentrates on creating subject-specific joint centers and muscle paths. It also reconstructs bone surfaces without requiring MRI segmentation. It integrates 3D Slicer and Python scripts, and uses Thin-Plate Spline (‘TPS’) mapping of anatomically equivalent (‘homologous’) landmarks from generic models onto participants’ anatomy. We applied this workflow to eight healthy participants, generating both generic-scaled and MRI-based models. Simulations were performed using participants’ 3D motion capture data. Two model types were compared using a number of parameters, including model geometry, joint kinematics, dynamics, and resultant joint contact forces during one gait cycle. The results revealed clear geometric differences between the model types, with MRI-based models exhibiting a wider pelvis (mean distance between ischial bones was 98.0 ± 5.0 mm in generic-scaled and 11.0 ± 8.0 mm in MRI-based models) and distinct femur/tibia proportions (the mean ratio was 0.92 ± 0.040 in generic-scaled and 0.99 ± 0.033 in MRI-based models). MRI-based models captured systematic anatomical differences between males and females that were absent in generic-scaled models. These geometric differences substantially affected joint loading estimates. MRI-based models consistently produced higher peak joint contact forces with greater inter-individual variation, particularly at the knee joints. Early stance knee peak joint contact force was higher in the MRI-based compared with the generic-scaled model by 0.84 ± 1.28 body weights on average. Despite these differences in geometry and loading, joint kinematics were similar within individuals (mean difference was 0.8 ± 2.47°) and muscle moment arms aligned well with published cadaver data, supporting the validity of the personalization approach. This workflow simplifies the creation of MRI-based musculoskeletal models and challenges the assumption that personalization is unnecessary for healthy adults. The findings reveal significant sensitivity of joint contact forces to individual morphology, emphasizing the importance of personalized models even in healthy populations for biomechanical analyses.

Understanding healthy and pathological movement patterns in humans is essential for injury prevention, rehabilitation, and optimizing sports performance. Musculoskeletal modeling is a powerful tool for exploring these questions, as it allows researchers to study joint moments, muscle activation patterns, and joint contact forces. However, most studies rely on generic musculoskeletal models that are scaled linearly to match a participant’s dimensions. This approach fails to accurately capture individual bone and muscle morphology. Personalization is often assumed to be more critical for pathological cases or children, while generic models are considered sufficient for healthy adults. To challenge this assumption, we developed a semi-automatic workflow for creating personalized musculoskeletal models based on magnetic resonance imaging (MRI). Our method avoids the need for bone segmentation and instead uses a non-affine fitting function to closely match individual geometry. By comparing MRI-based personalized models with generic-scaled models in eight healthy adults, we identified systematic biases in one of the most widely used musculoskeletal models. These findings demonstrate that even in healthy adults, personalization is important for accurately capturing individual anatomy and biomechanics. Our personalization pipeline is openly available, easy to implement, and designed to facilitate the use of highly personalized models in both clinical and research settings. This advancement has the potential to improve treatment planning, biomechanical assessments, and the overall accuracy of musculoskeletal modeling studies in the future.