3D Muscle Deformation Mapping at Submaximal Isometric Contractions: Applications to Aging Muscle

Malis, Vadim; Sinha, Usha; Sinha, Shantanu

doi:10.3389/fphys.2020.600590

Cited by 9 publications

(12 citation statements)

References 57 publications

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“…The continuum‐scale muscle components are modeled by a hybrid finite element formulation with a bilinear displacement field and a constant pressure field. The continuum muscle simulations are quasi‐static under the plane‐strain condition, which is consistent with the experimental observations that the out‐of‐plane deformation is relatively small compared to the in‐plane deformation 3,5,12,35–37 …”

Section: Methodssupporting

confidence: 84%

“…The continuum muscle simulations are quasi-static under the plane-strain condition, which is consistent with the experimental observations that the out-of-plane deformation is relatively small compared to the in-plane deformation. 3,5,12,[35][36][37]…”

Section: Methodsmentioning

confidence: 99%

“…1 The muscle fibers are surrounded by CT with collagen fibers. It has been shown that the material phases of this composite type of microstructure are essential to the continuum-scale force transmission of the muscle [2][3][4][5] and to an improved understanding of the aging effects on skeletal muscles. [6][7][8][9][10] Hence, it becomes imperative to examine the contribution of various factors (material properties, microstructure, and morphology of the tissue) that affect these passive materials, to the deformation and force output of the muscle.…”

Section: Introductionmentioning

confidence: 99%

“…8,9,14 However, it is difficult to design experiments to non-invasively measure lateral transmission of force. Experimentally, it has been observed using velocity-sensitized magnetic resonance imaging (MRI) that the principal strain directions of the muscle do not align with the fiber direction as the skeletal muscle tissue deforms, 5 implying the existence of shear deformation along the fiber direction. The angle difference between the principal strain direction and the fiber direction can be correlated with the shear deformation and further, the maximum shear strain has also been measured experimentally.…”

Section: Introductionmentioning

confidence: 99%

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Multiscale modeling of passive material influences on deformation and force output of skeletal muscles

Taneja

Chen

et al. 2022

Numer Methods Biomed Eng

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Passive materials in human skeletal muscle tissues play an important role in force output of skeletal muscles. This paper introduces a multiscale modeling framework to investigate how age-associated variations on microscale passive muscle components, including microstructural geometry (e.g., connective tissue thickness) and material properties (e.g., anisotropy), influence the force output and deformations of the continuum skeletal muscle. We first define a representative volume element (RVE) for the microstructure of muscle and determine the homogenized macroscale mechanical properties of the RVE from the separate mechanical properties of the individual components of the RVE, including muscle fibers and connective tissue with its associated collagen fibers. The homogenized properties of the RVE are then used to define the elements of the continuum muscle model to evaluate the force output and deformations of the whole muscle. Conversely, the regional deformations of the continuum model are fed back to the RVE model to determine the responses of the individual microscale components. Simulations of muscle isometric contractions at a range of muscle lengths are performed to investigate the effects of muscle architectural changes (e.g., pennation angles) due to aging on force output and muscle deformation. The correlations between the pennation angle, the shear deformation in the microscale connective tissue (an indicator for the lateral force transmission), the angle difference between the fiber direction and principal strain direction and the resulting shear deformation at the continuum scale, as well as the force output of the skeletal muscle are also discussed.

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Section: Methodssupporting

confidence: 84%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Multiscale modeling of passive material influences on deformation and force output of skeletal muscles

Taneja

Chen

et al. 2022

Numer Methods Biomed Eng

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“…The time-accumulated peaks of and were determined and labelled as and , respectively. Scheme 2 has been previously used to extract the principal strain rate and/or the tract-oriented strain rates in the brain [23, 25, 26, 41-44] and other biological tissues (e.g., leg muscles [45-48], tongue [49, 50], myocardium [51-53]).…”

Section: Methodsmentioning

confidence: 99%

Brain strain rate response: addressing computational ambiguity and experimental data for model validation

Zhou

Liu

et al. 2022

Preprint

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Traumatic brain injury (TBI) is an alarming global public health issue with high morbidity and mortality rates. Although the causal link between external insults and consequent brain injury remains largely elusive, both strain and strain rate are generally recognized as crucial factors for brain injury development. With respect to the flourishment of strain-based exploration, concerning ambiguity and inconsistency are noted in the scheme for strain rate calculation within the TBI research community. Furthermore, there is no experimental data that can be used to validate the strain rate responses of finite element (FE) models of the human brain. Thus, the current work presented a theoretical clarification of two commonly used strain rate computational schemes: the strain rate was either calculated as the time derivative of strain or derived from the strain-rate tensor. To further substantiate this theoretical disparity, these two schemes were respectively implemented to estimate the strain rate responses from a previous-published cadaveric experiment and an FE brain model secondary to a concussive impact. The results clearly showed scheme-dependent responses, both in the experimentally determined principal strain rate and FE-derived principal and tract-oriented strain rates. The results suggest that cross-scheme comparison of strain rate responses is inappropriate, and the utilized strain rate computational scheme needs to be reported in future studies. The newly calculated experimental strain rate curves can be used for strain rate validation of FE head models.

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Time‐dependent diffusion tensor imaging and diffusion modeling of age‐related differences in the medial gastrocnemius and feasibility study of correlations to histopathology

et al. 2023

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PurposeImplement STEAM‐DTI to model time‐dependent diffusion eigenvalues using the random permeable barrier model (RPBM) to study age‐related differences in the medial gastrocnemius (MG) muscle. Validate diffusion model‐extracted fiber diameter for histological assessment.MethodsDiffusion imaging at different diffusion times (Δ) was performed on seven young and six senior participants. Time‐dependent diffusion eigenvalues (λ2(t), λ3(t), and D⊥(t); average of λ2(t) and λ3(t)) were fit to the RPBM to extract tissue microstructure parameters. Biopsy of the MG tissue for histological assessment was performed on a subset of participants (four young, six senior).Resultsλ3(t) was significantly higher in the senior cohort for the range of diffusion times. RPBM fits to λ2(t) yielded fiber diameters in agreement to those from histology for both cohorts. The senior cohort had lower values of volume fraction of membranes, ζ, in fits to λ2(t), λ3(t), and D⊥(t) (significant for fit to λ3(t)). Fits of fiber diameter from RPBM to that from histology had the highest correlation for the fit to λ2(t).ConclusionThe age‐related patterns in λ2(t) and λ3(t) could tentatively be explained from RPBM fits; these patterns may potentially arise from a decrease in fiber asymmetry and an increase in permeability with age.

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3D Muscle Deformation Mapping at Submaximal Isometric Contractions: Applications to Aging Muscle

Cited by 9 publications

References 57 publications

Multiscale modeling of passive material influences on deformation and force output of skeletal muscles

Multiscale modeling of passive material influences on deformation and force output of skeletal muscles

Brain strain rate response: addressing computational ambiguity and experimental data for model validation

Time‐dependent diffusion tensor imaging and diffusion modeling of age‐related differences in the medial gastrocnemius and feasibility study of correlations to histopathology

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