Novel 3D MRI-Based Volumetric Assessment of Rotator Cuff Musculature Demonstrates Stronger Correlation with Preoperative Functional Status When Compared to the Goutallier Grading Scheme.

BACKGROUND: The Goutallier classification (GC) is used to assess fatty atrophy in rotator cuff (RC) tears, yet limitations exist. A battery of 3D-magnetic resonance imaging (MRI) volumetric scores (VS) was developed to provide comprehensive characterization of RC pathology. The purposes of this study were to: (1) Describe the correlation between GC and VS for supraspinatus changes in RC tears, (2) Characterize the chronicity of RC tears using the battery of 12 VS measurements, and (3) Compare GC and VS to determine which method most closely corresponds with preoperative patient reported outcome measures (PROMs). METHODS: Preoperative shoulder MRIs were reviewed after arthroscopic RC repair. Preoperative GC stage and Patient-Reported Outcomes Measurement Information System (PROMIS) physical function (PF) and pain interference (PI) scores were collected. The battery of VS included fat infiltration (FIS), muscle size (MSS) and relative volume contribution (RCS) for each RC muscle. Backwards linear regression was performed to compare GC stage with preoperative PROMIS PF/PI to determine which VS measurement most closely correlated with preoperative PROMs. RESULTS: Eighty-two patients underwent RC repair (mean age 55±8.2 years, 63% male, 68% GC stage ≤1). In evaluation of the supraspinatus, there was a moderate positive correlation between GC and FIS (r = 0.459, p < 0.001); strong negative correlations were observed between MSS (r = -0.800, p < 0.001) and RCS (r = -0.745, p < 0.001) when compared to GC. A negligible linear correlation was observed between GC and preoperative PROMIS PF (r = -0.106, p = 0.343) and PI (r = -0.071, p = 0.528). On multivariate analysis, subscapularis MSS (beta > 0, p = 0.064) was a positive predictor, and subscapularis FIS (beta < 0, p = 0.137), teres minor MSS (beta < 0, p = 0.141) and FIS (beta < 0, p = 0.070) were negative predictors of preoperative PF (r = 0.343, p = 0.044); while supraspinatus MSS (beta > 0, p = 0.009) and FIS (beta > 0, p = 0.073), teres minor FIS (beta > 0, p = 0.072) and subscapularis FIS (beta > 0, p = 0.065) were positive predictors of preoperative PI (r = 0.410, p = 0.006). CONCLUSION: Although gold standard in evaluation of RC pathology, GC demonstrated negligible correlation with preoperative functional disability. Alternatively, a battery of 3D VS showed strong correlation with GC through a quantitative, comprehensive evaluation of the RC unit including several moderate predictors of preoperative functional disability.

The need for speed - Does the force-velocity property significantly alter strain distributions within skeletal muscle?

Skeletal muscles are complex structures with nonlinear constitutive properties. This complexity often requires finite element (FE) modeling to better understand muscle behavior and response to activation, especially the fiber strain distributions that can be difficult to measure in vivo. However, many FE muscle models designed to study fiber strain do not include force-velocity behavior. To investigate force-velocity property impact on strain distributions within skeletal muscle, we modified a muscle constitutive model with active and passive force-length properties to include force-velocity properties. We implemented the new constitutive model as a plugin for the FE software FEBio and applied it to four geometries: 1) a single element, 2) a multiple-element model representing a single fiber, 3) a model of tapering fibers, and 4) a model representing the bicep femoris long head (BFLH) morphology. Maximum fiber velocity and boundary conditions of the finite element models were varied to test their influence on fiber strain distribution. We found that force-velocity properties in the constitutive model behaved as expected for the single element and multi-element conditions. In the tapered fiber models, fiber strain distributions were impacted by changes in maximum fiber velocity; the range of strains increased with maximum fiber velocity, which was most noted in isometric contraction simulations. In the BFLH model, maximum fiber velocity had minimal impact on strain distributions, even in the context of sprinting. Taken together, the combination of muscle model geometry, activation, and displacement parameters play a critical part in determining the magnitude of impact of force-velocity on strain distribution.

It's more than the amount that counts: implications of collagen organization on passive muscle tissue properties revealed with micromechanical models and experiments.

Collagen accumulation is often used to characterize skeletal muscle fibrosis, but the role of collagen in passive muscle mechanics remains debated. Here we combined finite-element models and experiments to examine how collagen organization contributes to macroscopic muscle tissue properties. Tissue microstructure and mechanical properties were measured from in vitro biaxial experiments and imaging in dystrophin knockout (mdx) and wild-type (WT) diaphragm muscle. Micromechanical models of intramuscular and epimuscular extracellular matrix (ECM) regions were developed to account for complex microstructure and predict bulk properties, and directly calibrated and validated with the experiments. The models predicted that intramuscular collagen fibres align primarily in the cross-muscle fibre direction, with greater cross-muscle fibre alignment in mdx models compared with WT. Higher cross-muscle fibre stiffness was predicted in mdx models compared with WT models and differences between ECM and muscle properties were seen during cross-muscle fibre loading. Analysis of the models revealed that variation in collagen fibre distribution had a much more substantial impact on tissue stiffness than ECM area fraction. Taken together, we conclude that collagen organization explains anisotropic tissue properties observed in the diaphragm muscle and provides an explanation for the lack of correlation between collagen amount and tissue stiffness across experimental studies.

Regional and bilateral MRI and gene signatures in facioscapulohumeral dystrophy: implications for clinical trial design and mechanisms of disease progression.

Identifying the aberrant expression of DUX4 in skeletal muscle as the cause of facioscapulohumeral dystrophy (FSHD) has led to rational therapeutic development and clinical trials. Several studies support the use of MRI characteristics and the expression of DUX4-regulated genes in muscle biopsies as biomarkers of FSHD disease activity and progression. We performed lower-extremity MRI and muscle biopsies in the mid-portion of the tibialis anterior (TA) muscles bilaterally in FSHD subjects and validated our prior reports of the strong association between MRI characteristics and expression of genes regulated by DUX4 and other gene categories associated with FSHD disease activity. We further show that measurements of normalized fat content in the entire TA muscle strongly predict molecular signatures in the mid-portion of the TA, indicating that regional biopsies can accurately measure progression in the whole muscle and providing a strong basis for inclusion of MRI and molecular biomarkers in clinical trial design. An unanticipated finding was the strong correlations of molecular signatures in the bilateral comparisons, including markers of B-cells and other immune cell populations, suggesting that a systemic immune cell infiltration of skeletal muscle might have a role in disease progression.

Agent-based model demonstrates the impact of nonlinear, complex interactions between cytokines on muscle regeneration.

Muscle regeneration is a complex process due to dynamic and multiscale biochemical and cellular interactions, making it difficult to identify microenvironmental conditions that are beneficial to muscle recovery from injury using experimental approaches alone. To understand the degree to which individual cellular behaviors impact endogenous mechanisms of muscle recovery, we developed an agent-based model (ABM) using the Cellular Potts framework to simulate the dynamic microenvironment of a cross-section of murine skeletal muscle tissue. We referenced more than 100 published studies to define over 100 parameters and rules that dictate the behavior of muscle fibers, satellite stem cells (SSC), fibroblasts, neutrophils, macrophages, microvessels, and lymphatic vessels, as well as their interactions with each other and the microenvironment. We utilized parameter density estimation to calibrate the model to temporal biological datasets describing cross-sectional area (CSA) recovery, SSC, and fibroblast cell counts at multiple time points following injury. The calibrated model was validated by comparison of other model outputs (macrophage, neutrophil, and capillaries counts) to experimental observations. Predictions for eight model perturbations that varied cell or cytokine input conditions were compared to published experimental studies to validate model predictive capabilities. We used Latin hypercube sampling and partial rank correlation coefficient to identify in silico perturbations of cytokine diffusion coefficients and decay rates to enhance CSA recovery. This analysis suggests that combined alterations of specific cytokine decay and diffusion parameters result in greater fibroblast and SSC proliferation compared to individual perturbations with a 13% increase in CSA recovery compared to unaltered regeneration at 28 days. These results enable guided development of therapeutic strategies that similarly alter muscle physiology (i.e. converting ECM-bound cytokines into freely diffusible forms as studied in cancer therapeutics or delivery of exogenous cytokines) during regeneration to enhance muscle recovery after injury.

A new look at an old problem: 3D modeling of accommodation reveals how age-related biomechanical changes contribute to dysfunction in presbyopia.

Presbyopia is an age-related ocular disorder where accommodative ability declines so that an individual's focusing range is insufficient to provide visual clarity for near and distance vision tasks without corrective measures. With age, the eye exhibits changes in biomechanical properties of many components involved in accommodation, including the lens, sclera, and ciliary muscle. Changes occur at different rates, affecting accommodative biomechanics differently, but individual contributions to presbyopia are unknown. We used a finite element model (FEM) of the accommodative mechanism to simulate age-related changes in lens stiffness, scleral stiffness, and ciliary contraction to predict differences in accommodative function. The FEM predicts how ciliary muscle action leads to lens displacement by initializing a tensioned unaccommodated lens (Phase 0) then simulating ciliary muscle contraction in accommodation (Phase 1). Model inputs were calibrated to replicate experimentally measured lens and ciliary muscle in 30-year-old eyes. Predictions of accommodative lens deformation were verified with additional imaging studies. Model variations were created with altered lens component stiffnesses, scleral stiffness, or ciliary muscle section activations, representing fifteen-year incremental age-related changes. Model variations predict significant changes in accommodative function with age-related biomechanical property changes. Lens changes only significantly altered lens thickening with advanced age (46% decrease at 75 years old) while sclera changes produced progressive dysfunction with increasing age (23%, 36%, 49% decrease at 45, 60, and 75 years old). Ciliary muscle changes effected lens position modulation. Model predictions identified potential mechanisms of presbyopia that likely work in combination to reduce accommodative function and could indicate effectiveness of treatment strategies and their dependency on patient age or relative ocular mechanical properties.

Fiber-type traps: revisiting common misconceptions about skeletal muscle fiber types with application to motor control, biomechanics, physiology, and biology.

Skeletal muscle is a highly complex tissue that is studied by scientists from a wide spectrum of disciplines, including motor control, biomechanics, exercise science, physiology, cell biology, genetics, regenerative medicine, orthopedics, and engineering. Although this diversity in perspectives has led to many important discoveries, historically, there has been limited overlap in discussions across fields. This has led to misconceptions and oversimplifications about muscle biology that can create confusion and potentially slow scientific progress across fields. The purpose of this synthesis paper is to bring together research perspectives across multiple muscle fields to identify common assumptions related to muscle fiber type that are points of concern to clarify. These assumptions include 1) classification by myosin isoform and fiber oxidative capacity is equivalent, 2) fiber cross-sectional area (CSA) is a surrogate marker for myosin isoform or oxidative capacity, and 3) muscle force-generating capacity can be inferred from myosin isoform. We address these three fiber-type traps and provide some context for how these misunderstandings can and do impact experimental design, computational modeling, and interpretations of findings, from the perspective of a range of fields. We stress the dangers of generalizing findings about "muscle fiber types" among muscles or across species or sex, and we note the importance for precise use of common terminology across the muscle fields.

Validity of Inertial Measurement Units to Measure Lower-Limb Kinematics and Pelvic Orientation at Submaximal and Maximal Effort Running Speeds.

Inertial measurement units (IMUs) have been validated for measuring sagittal plane lower-limb kinematics during moderate-speed running, but their accuracy at maximal speeds remains less understood. This study aimed to assess IMU measurement accuracy during high-speed running and maximal effort sprinting on a curved non-motorized treadmill using discrete (Bland-Altman analysis) and continuous (root mean square error [RMSE], normalised RMSE, Pearson correlation, and statistical parametric mapping analysis [SPM]) metrics. The hip, knee, and ankle flexions and the pelvic orientation (tilt, obliquity, and rotation) were captured concurrently from both IMU and optical motion capture systems, as 20 participants ran steadily at 70%, 80%, 90%, and 100% of their maximal effort sprinting speed (5.36 ± 0.55, 6.02 ± 0.60, 6.66 ± 0.71, and 7.09 ± 0.73 m/s, respectively). Bland-Altman analysis indicated a systematic bias within ±1° for the peak pelvic tilt, rotation, and lower-limb kinematics and -3.3° to -4.1° for the pelvic obliquity. The SPM analysis demonstrated a good agreement in the hip and knee flexion angles for most phases of the stride cycle, albeit with significant differences noted around the ipsilateral toe-off. The RMSE ranged from 4.3° (pelvic obliquity at 70% speed) to 7.8° (hip flexion at 100% speed). Correlation coefficients ranged from 0.44 (pelvic tilt at 90%) to 0.99 (hip and knee flexions at all speeds). Running speed minimally but significantly affected the RMSE for the hip and ankle flexions. The present IMU system is effective for measuring lower-limb kinematics during sprinting, but the pelvic orientation estimation was less accurate.

Objective analysis of partial three-dimensional rotator cuff muscle volume and fat infiltration across ages and sex from clinical MRI scans.

Objective analysis of rotator cuff (RC) atrophy and fatty infiltration (FI) from clinical MRI is limited by qualitative measures and variation in scapular coverage. The goals of this study were to: develop/evaluate a method to quantify RC muscle size, atrophy, and FI from clinical MRIs (with typical lateral only coverage) and then quantify the effects of age and sex on RC muscle. To develop the method, 47 full scapula coverage CTs with matching clinical MRIs were used to: correct for variation in scan capture, and ensure impactful information of the RC is measured. Utilizing this methodology and automated artificial intelligence, 170 healthy clinical shoulder MRIs of varying age and sex were segmented, and each RC muscle's size, relative contribution, and FI as a function of scapula location were quantified. A two-way ANOVA was used to examine the effect of age and sex on RC musculature. The analysis revealed significant (p < 0.05): decreases in size of the supraspinatus, teres minor, and subscapularis with age; decreased supraspinatus and increased infraspinatus relative contribution with age; and increased FI in the infraspinatus with age and in females. This study demonstrated that clinically obtained MRIs can be utilized for automatic 3D analysis of the RC. This method is not susceptible to coverage variation or patient size. Application of methodology in a healthy population revealed differences in RC musculature across ages and FI level between sexes. This large database can be used to reference expected muscle characteristics as a function of scapula location and could eventually be used in conjunction with the proposed methodology for analysis in patient populations.

In vivo imaging of skeletal muscle form and function: 50 years of insight.

Skeletal muscle form and function has fascinated scientists for centuries. Our understanding of muscle function has long been driven by advancements in imaging techniques. For example, the sliding filament theory of muscle, which is now widely leveraged in biomechanics research, stemmed from observations made possible by scanning electron microscopy. Over the last 50 years, advancing in medical imaging, combined with ingenuity and creativity of biomechanists, have provide a wealth of new and important insights into in vivo human muscle function. Incorporation of in vivo imaging has also advanced computational modeling and allowed our research to have an impact in many clinical populations. While this review does not provide a comprehensive or meta-analysis of the all the in vivo muscle imaging work over the last five decades, it provides a narrative about the past, present, and future of in vivo muscle imaging.

Athlete Muscular Phenotypes Identified and Compared with High-Dimensional Clustering of Lower Limb Muscle Volume Measurements.

INTRODUCTION: Athletes use their skeletal muscles to demonstrate performance. Muscle force generating capacity is correlated with volume, meaning that variations in sizes of different muscles may be indicative of how athletes meet different demands in their sports. Medical imaging enables in vivo quantification of muscle volumes; however, muscle volume distribution has not been compared across athletes of different sports. PURPOSE: The goal of this work was to define "muscular phenotypes" in athletes of different sports and compare these using hierarchical clustering. METHODS: Muscle volumes normalized by body mass of athletes (football, baseball, basketball, or track) were compared with control participants to quantify size differences using z -scores. z -Scores of 35 muscles described the pattern of volume deviation within each athlete's lower limb, characterizing their muscular phenotype. Data-driven high-dimensional clustering analysis was used to group athletes presenting similar phenotypes. Efficacy of clustering to identify similar phenotypes was demonstrated by grouping athletes' contralateral limbs before other athletes' limbs. RESULTS: Analyses revealed that athletes did not tend to cluster with others competing in the same sport. Basketball players with similar phenotypes grouped by clustering also demonstrated similarities in performance. Clustering also identified muscles with similar volume variation patterns across athletes, and principal component analysis revealed specific muscles that accounted for most of the variance (gluteus maximus, sartorius, semitendinosus, vastus medialis, vastus lateralis, and rectus femoris). CONCLUSIONS: Athletes exhibit heterogeneous lower limb muscle volumes that can be characterized and compared as individual muscular phenotypes. Clustering revealed that athletes with the most similar phenotypes do not always play the same sport such that patterns of muscular heterogeneity across a group of athletes reflect factors beyond their specific sports.

A Deep Learning Algorithm for Automatic 3D Segmentation of Rotator Cuff Muscle and Fat from Clinical MRI Scans.

The authors aimed to develop and validate an automated artificial intelligence (AI) algorithm for three-dimensional (3D) segmentation of all four rotator cuff (RC) muscles to quantify intramuscular fat infiltration (FI) and individual muscle volume. The dataset included retrospectively collected RC MRI scans in 232 patients (63 with normal RCs, 169 with RC tears). A two-stage AI model was developed to segment all RC muscles and their FI in each stage. For comparison, single-stage and Otsu filtering models were created. Using the two-stage model, segmentation performance demonstrated high Dice scores (mean, 0.92 ± 0.14 [SD]), low volume errors (mean, 5.72% ± 9.23), and low FI errors (mean, 1.54% ± 2.79) when validated in 30 scans. There was a significant correlation between the 3D FI in the RC tear scans with a Goutallier grade (ρ = 0.53, P < .001) and FI found from a single two-dimensional (2D) section (all muscles, ρ > 0.70; P < .001). However, Bland-Altman analysis of the 3D compared with the 2D analyses of FI demonstrated a proportional bias (all muscles, P < .001). Compared with Goutallier classification or single-image quantification, the AI method allowed for more variability in images and led to objective separate quantifications of muscle volume and FI in all RC muscles. Keywords: Rotator Cuff, Artificial Intelligence, Segmentation, Fat Infiltration, Muscle Volume, MRI, Shoulder Supplemental material is available for this article. © RSNA, 2023.

Validation of the association between MRI and gene signatures in facioscapulohumeral dystrophy muscle: implications for clinical trial design.

Identifying the aberrant expression of DUX4 in skeletal muscle as the cause of facioscapulohumeral dystrophy (FSHD) has led to rational therapeutic development and clinical trials. Several studies support the use of MRI characteristics and the expression of DUX4-regulated genes in muscle biopsies as biomarkers of FSHD disease activity and progression, but reproducibility across studies needs further validation. We performed lower-extremity MRI and muscle biopsies in the mid-portion of the tibialis anterior (TA) muscles bilaterally in FSHD subjects and validated our prior reports of the strong association between MRI characteristics and expression of genes regulated by DUX4 and other gene categories associated with FSHD disease activity. We further show that measurements of normalized fat content in the entire TA muscle strongly predict molecular signatures in the mid-portion of the TA. Together with moderate-to-strong correlations of gene signatures and MRI characteristics between the TA muscles bilaterally, these results suggest a whole muscle model of disease progression and provide a strong basis for inclusion of MRI and molecular biomarkers in clinical trial design.

Personalized volumetric assessment of lower body muscles in patients with knee injuries: A descriptive case series.

BACKGROUND: Patients with knee joint pathology present with variable muscular responses across the muscles of the lower limb and pelvis. Conventional approaches to characterizing muscle function are limited to gross strength assessments that may overlook subtle changes both in the thigh, hip and shank musculature. PURPOSE: To describe individualized patterns of lower extremity muscle volumes in patients with knee pathologies. METHODS: This was a retrospective case series performed in a University medical center. Nine patients diagnosed with meniscus tear recommended to undergo meniscectomy volunteered. Participants underwent 3.0 Tesla magnetic resonance imaging (MRI) of the lower extremities. Thirty-five MRI-derived muscle volumes were compared between limbs and expressed as percentage asymmetry. For additional context, z-scores were also calculated for mass- and height-normalized muscles and pre-determined muscle groupings relative to a normative database. RESULTS: There were no consistent patterns observed when considering between-limb asymmetries among all patients. The ankle musculature (dorsiflexors, plantar flexors, and invertors) was the only muscle group to be consistently smaller than normal for all patients, with the psoas major and flexor hallucis longus being the only individual muscles. The severity or chronicity of injury and presence of surgical intervention did not appear to have a clear effect on muscle volumes. CONCLUSION: Patients with a history of meniscal pathology demonstrate inconsistent patterns of lower extremity muscle volumes about the hip, knee, and ankle between limbs and in comparison to uninjured individuals. These data support the need for individualized assessment and intervention in this population.

The development of a HAMstring InjuRy (HAMIR) index to mitigate injury risk through innovative imaging, biomechanics, and data analytics: protocol for an observational cohort study.

BACKGROUND: The etiology of hamstring strain injury (HSI) in American football is multi-factorial and understanding these risk factors is paramount to developing predictive models and guiding prevention and rehabilitation strategies. Many player-games are lost due to the lack of a clear understanding of risk factors and the absence of effective methods to minimize re-injury. This paper describes the protocol that will be followed to develop the HAMstring InjuRy (HAMIR) index risk prediction models for HSI and re-injury based on morphological, architectural, biomechanical and clinical factors in National Collegiate Athletic Association Division I collegiate football players. METHODS: A 3-year, prospective study will be conducted involving collegiate football student-athletes at four institutions. Enrolled participants will complete preseason assessments of eccentric hamstring strength, on-field sprinting biomechanics and muscle-tendon volumes using magnetic-resonance imaging (MRI). Athletic trainers will monitor injuries and exposure for the duration of the study. Participants who sustain an HSI will undergo a clinical assessment at the time of injury along with MRI examinations. Following completion of structured rehabilitation and return to unrestricted sport participation, clinical assessments, MRI examinations and sprinting biomechanics will be repeated. Injury recurrence will be monitored through a 6-month follow-up period. HAMIR index prediction models for index HSI injury and re-injury will be constructed. DISCUSSION: The most appropriate strategies for reducing risk of HSI are likely multi-factorial and depend on risk factors unique to each athlete. This study will be the largest-of-its-kind (1200 player-years) to gather detailed information on index and recurrent HSI, and will be the first study to simultaneously investigate the effect of morphological, biomechanical and clinical variables on risk of HSI in collegiate football athletes. The quantitative HAMIR index will be formulated to identify an athlete's propensity for HSI, and more importantly, identify targets for injury mitigation, thereby reducing the global burden of HSI in high-level American football players. Trial Registration The trial is prospectively registered on ClinicalTrials.gov (NCT05343052; April 22, 2022).

Diaphragm muscle fibrosis involves changes in collagen organization with mechanical implications in Duchenne muscular dystrophy.

In Duchenne muscular dystrophy (DMD), diaphragm muscle dysfunction results in respiratory insufficiency, a leading cause of death in patients. Increased muscle stiffness occurs with buildup of fibrotic tissue, characterized by excessive accumulation of extracellular matrix (ECM) components such as collagen, and prevents the diaphragm from achieving the excursion lengths required for respiration. However, changes in mechanical properties are not explained by collagen amount alone and we must consider the complex structure and mechanics of fibrotic tissue. The goals of our study were to 1) determine if and how collagen organization changes with the progression of DMD in diaphragm muscle tissue and 2) predict how collagen organization influences the mechanical properties of the ECM. We first visualized collagen structure with scanning electron microscopy (SEM) images and then developed an analysis framework to quantify collagen organization and generate image-based finite-element models. Image analysis revealed increased collagen fiber straightness and alignment in mdx over wild type (WT) at 3 mo (straightness: mdx = 0.976 ± 0.0108, WT = 0.887 ± 0.0309, alignment: mdx = 0.876 ± 0.0333, WT = 0.759 ± 0.0416) and 6 mo (straightness: mdx = 0.942 ± 0.0182, WT = 0.881 ± 0.0163, alignment: mdx = 0.840 ± 0.0315, WT = 0.759 ± 0.0368). Collagen fibers retained a transverse orientation relative to muscle fibers (70°-90°) in all groups. Mechanical models predicted an increase in the transverse relative to longitudinal (muscle fiber direction) stiffness, with stiffness ratio (transverse/longitudinal) increased in mdx over WT at 3 mo (mdx = 5.45 ± 2.04, WT = 1.97 ± 0.670) and 6 mo (mdx = 4.05 ± 0.985, WT = 1.96 ± 0.506). This study revealed changes in diaphragm ECM structure and mechanics during disease progression in the mdx muscular dystrophy mouse phenotype, highlighting the need to consider the role of collagen organization on diaphragm muscle function.NEW & NOTEWORTHY Scanning electron microscopy images of decellularized diaphragm muscle from WT and mdx, Duchenne muscular dystrophy model, mice revealed that collagen fibers in the epimysium are oriented transverse to muscle fibers, with age- and disease-dependent changes in collagen arrangement. Finite-element models generated from these images predicted that changes in collagen arrangement during disease progression influence the mechanical properties of the extracellular matrix. Thus, changes in collagen fiber-level structure are implicated on tissue-level properties during fibrosis.

A Preliminary Study of Anatomical Changes Following the Use of a Pedicled Buccal Fat Pad Flap During Primary Palatoplasty.

OBJECTIVE: The purpose of this study was to examine the surgical impact of the pedicled buccal fat pad (BFP) flap on the levator veli palatini (LVP) muscle and surrounding velopharyngeal (VP) anatomy following primary palatoplasty using magnetic resonance imaging (MRI). DESIGN: Observational, prospective. SETTING: MRI studies were completed at 3 different facilities. All participants with BFP flap were operated on by the same surgeon. PARTICIPANTS: Five pediatric participants with cleft palate with or without cleft lip (CP±L) who underwent primary palatoplasty with BFP flap placement. Comparison groups consisted of 10 participants: 5 with CP±L who did not receive the BFP flap and 5 healthy controls. INTERVENTIONS: All participants underwent nonsedated MRI 2 to 5 years postoperatively. MAIN OUTCOMES AND MEASURES: Anatomical measures of the velopharynx and LVP among the 3 participant groups. RESULTS: Median values were significantly different among groups for velar length (P = .042), effective velar length (P = .048), effective VP ratio (P = .046), LVP length (P = .021), extravelar LVP length (P = .009), and LVP origin-origin distance (P = .030). Post hoc analysis revealed a statistically significant difference between the BFP and traditional repair groups for effective VP ratio (P = .040), extravelar LVP length (P = .033), and LVP length (P = .022). CONCLUSIONS: This study provides preliminary support that the BFP flap creates a longer velum, with increased distance between the posterior hard palate and the LVP, and a larger effective VP ratio compared to traditional surgical techniques. Future research is needed to determine whether this procedure provides a more favorable mechanism for VP closure.

A 3D model of the soleus reveals effects of aponeuroses morphology and material properties on complex muscle fascicle behavior.

The soleus is an important plantarflexor muscle with complex fascicle and connective tissue arrangement. In this study we created an image-based finite element model representing the 3D structure of the soleus muscle and its aponeurosis connective tissue, including distinct fascicle architecture of the posterior and anterior compartments. The model was used to simulate passive and active soleus lengthening during ankle motion to predict tissue displacements and fascicle architecture changes. Both the model's initial architecture and changes incurred during passive lengthening were consistent with prior in vivo data from diffusion tensor imaging. Model predictions of active lengthening were consistent with axial plane muscle displacements that we measured in eight subjects' lower legs using cine DENSE (Displacement Encoding with Stimulated Echoes) MRI during eccentric dorsiflexion. Regional strains were variable and nonuniform in the model, but average fascicle strains were similar between the compartments for both passive (anterior: 0.18 ± 0.06, posterior: 0.19 ± 0.05) and active (anterior: 0.12 ± 0.05, posterior: 0.13 ± 0.06) lengthening and were two- to three-times greater than muscle belly strain (0.06). We used additional model simulations to investigate the effects of aponeurosis material properties on muscle deformation, by independently varying the longitudinal or transverse stiffness of the posterior or anterior aponeurosis. Results of model variations elucidate how properties of soleus aponeuroses contribute to fascicle architecture changes. Greater longitudinal stiffness of posterior compared to anterior aponeurosis promoted more uniform spatial distribution of muscle tissue deformation. Reduced transverse stiffness in both aponeuroses resulted in larger differences between passive and active soleus lengthening.

Agent-based model provides insight into the mechanisms behind failed regeneration following volumetric muscle loss injury.

Skeletal muscle possesses a remarkable capacity for repair and regeneration following a variety of injuries. When successful, this highly orchestrated regenerative process requires the contribution of several muscle resident cell populations including satellite stem cells (SSCs), fibroblasts, macrophages and vascular cells. However, volumetric muscle loss injuries (VML) involve simultaneous destruction of multiple tissue components (e.g., as a result of battlefield injuries or vehicular accidents) and are so extensive that they exceed the intrinsic capability for scarless wound healing and result in permanent cosmetic and functional deficits. In this scenario, the regenerative process fails and is dominated by an unproductive inflammatory response and accompanying fibrosis. The failure of current regenerative therapeutics to completely restore functional muscle tissue is not surprising considering the incomplete understanding of the cellular mechanisms that drive the regeneration response in the setting of VML injury. To begin to address this profound knowledge gap, we developed an agent-based model to predict the tissue remodeling response following surgical creation of a VML injury. Once the model was able to recapitulate key aspects of the tissue remodeling response in the absence of repair, we validated the model by simulating the tissue remodeling response to VML injury following implantation of either a decellularized extracellular matrix scaffold or a minced muscle graft. The model suggested that the SSC microenvironment and absence of pro-differentiation SSC signals were the most important aspects of failed muscle regeneration in VML injuries. The major implication of this work is that agent-based models may provide a much-needed predictive tool to optimize the design of new therapies, and thereby, accelerate the clinical translation of regenerative therapeutics for VML injuries.