Review of musculoskeletal modelling in a clinical setting: Current use in rehabilitation design, surgical decision making and healthcare interventions

Smith, Samuel H.L.; Coppack, Russell J; Bogert, Antonie J. van den; Bennett, Alexander N.; Bull, Anthony M.J.

doi:10.1016/j.clinbiomech.2021.105292

Cited by 27 publications

(15 citation statements)

References 87 publications

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“…Despite their potential impact, MSK models are not yet employed on a wide scale in healthcare [3,4] and a well-established framework to accurately predict neuromusculoskeletal dynamics of healthy and pathologic individuals is still lacking [5]. This is also associated to the lack of gold standards, which makes it difficult to quantify the advantages or disadvantages of available approaches [2].…”

Section: Introductionmentioning

confidence: 99%

Modeling Musculoskeletal Dynamics during Gait: Evaluating the Best Personalization Strategy through Model Anatomical Consistency

et al. 2021

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No consensus exists on how to model human articulations within MSK models for the analysis of gait dynamics. We propose a method to evaluate joint models and we apply it to three models with different levels of personalization. The method evaluates the joint model’s adherence to the MSK hypothesis of negligible joint work by quantifying ligament and cartilage deformations resulting from joint motion; to be anatomically consistent, these deformations should be minimum. The contrary would require considerable external work to move the joint, violating a strong working hypothesis and raising concerns about the credibility of the MSK outputs. Gait analysis and medical resonance imaging (MRI) from ten participants were combined to build lower limb subject-specific MSK models. MRI-reconstructed anatomy enabled three levels of personalization using different ankle joint models, in which motion corresponded to different ligament elongation and cartilage co-penetration. To estimate the impact of anatomical inconsistency in MSK outputs, joint internal forces resulting from tissue deformations were computed for each joint model and MSK simulations were performed ignoring or considering their contribution. The three models differed considerably for maximum ligament elongation and cartilage co-penetration (between 5.94 and 50.69% and between −0.53 and −5.36 mm, respectively). However, the model dynamic output from the gait simulations were similar. When accounting for the internal forces associated with tissue deformation, outputs changed considerably, the higher the personalization level the smaller the changes. Anatomical consistency provides a solid method to compare different joint models. Results suggest that consistency grows with personalization, which should be tailored according to the research question. A high level of anatomical consistency is recommended when individual specificity and the behavior of articular structures is under investigation.

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Section: Introductionmentioning

confidence: 99%

Modeling Musculoskeletal Dynamics during Gait: Evaluating the Best Personalization Strategy through Model Anatomical Consistency

et al. 2021

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“…SDM tools that have been developed for the treatment of early-stage osteoarthritis range from providing basic information and questions or questionnaires in print, video, computer tablet, or website[ 18 25 26 27 ] to using computerized modeling. [ 28 29 ] Dolan et al . [ 28 ] reported consistently positive patient responses for the use of a computerized interactive clinical decision dashboard for treatment of osteoarthritis pain with nine analgesic options.…”

Section: Discussionmentioning

confidence: 99%

Development of a personalized shared decision-making tool for knee osteoarthritis and user-testing with African American and Latina women

Jones

Maurer

Parks

et al. 2022

J Family Med Prim Care

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Background: Patients with chronic knee pain are often unaware of treatment options and likely outcomes—information that is critical to decision-making. A consistent framework for communicating patient-personalized information enables clinicians to provide consistent, targeted, and relevant information. Our objective was to user-test a shared decision-making (SDM) tool for chronic knee pain. Methods: A cross-functional team developed a Markov-based health economics model and tested the model outputs with patient panels, patient and clinician focus groups, and clinical specialists. The resulting SDM tool was user-tested in a parallel-designed, randomized controlled study with 52 African American and 52 Latina women from geographically representative areas of the US. Participants were randomized to counseling with or without the SDM tool. Feedback was collected at intervention and at 1 month after intervention and analyzed with Student’s t-tests and Chi-squared analyses (alpha = 0.05). Results: Qualitative results indicated patients understood the material, rated the overall experience highly, and were likely to recommend the physician. The SDM group reported high satisfaction with the tool. A greater proportion of the SDM group (56%) reported increased physical activity over baseline at 1 month compared with the control group (33%) ( P = 0.0005). New use of medications for knee pain (58% SDM; 49% control) did not differ significantly between groups ( P = 0.15). Conclusion: Use of this innovative SDM tool was associated with high satisfaction and a significant increase in self-reported physical activity level at 1 month. The SDM tool may elicit behavioral changes to promote musculoskeletal health.

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“…Multi-scale in silico models are a very promising tool for assessing cartilage structure and function, as the models appear to yield valid estimates of cartilage loads. However, in order to introduce in silico models as a clinical tool, they should be personalized for each patient (e.g., based on imaging), as similarly stated for musculoskeletal models 63 . Moreover, combining this with wearables or deep learning networks will enable the efficient handling of larger sample sizes ((Fig.…”

Section: Computational Modellingmentioning

confidence: 99%

Osteoarthritis year in review 2021: mechanics

Harlaar

Macri

Wesseling

2022

Osteoarthritis and Cartilage

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Review of musculoskeletal modelling in a clinical setting: Current use in rehabilitation design, surgical decision making and healthcare interventions

Cited by 27 publications

References 87 publications

Modeling Musculoskeletal Dynamics during Gait: Evaluating the Best Personalization Strategy through Model Anatomical Consistency

Modeling Musculoskeletal Dynamics during Gait: Evaluating the Best Personalization Strategy through Model Anatomical Consistency

Development of a personalized shared decision-making tool for knee osteoarthritis and user-testing with African American and Latina women

Osteoarthritis year in review 2021: mechanics

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