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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.
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Distrofia Muscular Facioescapuloumeral , Humanos , Distrofia Muscular Facioescapuloumeral/diagnóstico por imagem , Distrofia Muscular Facioescapuloumeral/genética , Distrofia Muscular Facioescapuloumeral/metabolismo , Proteínas de Homeodomínio/genética , Ensaios Clínicos como Assunto , Músculo Esquelético/metabolismo , Imageamento por Ressonância Magnética , Biomarcadores/metabolismo , Progressão da DoençaRESUMO
BACKGROUND: The Goutallier classification (GC) is used to assess fatty atrophy in rotator cuff (RC) tears, yet limitations exist. A battery of 3-dimensional (3D) magnetic resonance imaging (MRI) volumetric scores (VSs) was developed to provide comprehensive characterization of RC pathology. The purposes of this study were to (1) describe the correlation between GC and VSs for supraspinatus changes in RC tears, (2) characterize the chronicity of RC tears using a battery of 12 VS measurements, and (3) compare GC and VSs 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 VSs included fat infiltration (FIS), muscle size (MSS), and relative volume contribution (RCS) for each RC muscle. Backward linear regression was performed to compare GC stage with preoperative PROMIS PF and 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 < .001); strong negative correlations were observed between MSS (r = -0.800, P < .001) and RCS (r = -0.745, P < .001) when compared to GC. A negligible linear correlation was observed between GC and preoperative PROMIS PF (r = -0.106, P = .343) and PI (r = -0.071, P = .528). On multivariate analysis, subscapularis MSS (ß >0, P = .064) was a positive predictor and subscapularis FIS (ß <0, P = .137), teres minor MSS (ß <0, P = .141), and FIS (ß <0, P = .070) were negative predictors of preoperative PF (r = 0.343, P = .044); in contrast, supraspinatus MSS (ß >0, P = .009) and FIS (ß >0, P = .073), teres minor FIS (ß >0, P = .072), and subscapularis FIS (ß >0, P = .065) were positive predictors of preoperative PI (r = 0.410, P = .006). CONCLUSION: Although the criterion standard in evaluation of RC pathology, GC demonstrated negligible correlation with preoperative functional disability. Alternatively, a battery of 3D VSs showed strong correlation with GC through a quantitative, comprehensive evaluation of the RC unit including several moderate predictors of preoperative functional disability.
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BACKGROUND: People with multiple sclerosis (PwMS) have balance deficits while ambulating through environments that contain moving objects or visual manipulations to perceived self-motion. However, their ability to parse object from self-movement has not been explored. The purpose of this research was to examine the effect of medial-lateral oscillations of the visual field and of objects within the scene on gait in PwMS and healthy age-matched controls using virtual reality (VR). METHODS: Fourteen PwMS (mean age 49 ± 11 years, functional gait assessment score of 27.8 ± 1.8, and Berg Balance scale score 54.7 ± 1.5) and eleven healthy controls (mean age: 53 ± 12 years) participated in this study. Dynamic balance control was assessed while participants walked on a treadmill at a self-selected speed while wearing a VR headset that projected an immersive forest scene. Visual conditions consisted of (1) no visual manipulations (speed-matched anterior/posterior optical flow), (2) 0.175 m mediolateral translational oscillations of the scene that consisted of low pairing (0.1 and 0.31 Hz) or (3) high pairing (0.15 and 0.465 Hz) frequencies, (4) 5 degree medial-lateral rotational oscillations of virtual trees at a low frequency pairing (0.1 and 0.31 Hz), and (5) a combination of the tree and scene movements in (3) and (4). RESULTS: We found that both PwMS and controls exhibited greater instability and visuomotor entrainment to simulated mediolateral translation of the visual field (scene) during treadmill walking. This was demonstrated by significant (p < 0.05) increases in mean step width and variability and center of mass sway. Visuomotor entrainment was demonstrated by high coherence between center of mass sway and visual motion (magnitude square coherence = ~ 0.5 to 0.8). Only PwMS exhibited significantly greater instability (higher step width variability and center of mass sway) when objects moved within the scene (i.e., swaying trees). CONCLUSION: Results suggest the presence of visual motion processing errors in PwMS that reduced dynamic stability. Specifically, object motion (via tree sway) was not effectively parsed from the observer's self-motion. Identifying this distinction between visual object motion and self-motion detection in MS provides insight regarding stability control in environments with excessive external movement, such as those encountered in daily life.
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Esclerose Múltipla , Adulto , Idoso , Teste de Esforço/métodos , Marcha , Humanos , Pessoa de Meia-Idade , Modalidades de Fisioterapia , Equilíbrio Postural , CaminhadaRESUMO
Facioscapulohumeral muscular dystrophy (FSHD) affects roughly 1 in 7500 individuals. While at the population level there is a general pattern of affected muscles, there is substantial heterogeneity in muscle expression across- and within-patients. There can also be substantial variation in the pattern of fat and water signal intensity within a single muscle. While quantifying individual muscles across their full length using magnetic resonance imaging (MRI) represents the optimal approach to follow disease progression and evaluate therapeutic response, the ability to automate this process has been limited. The goal of this work was to develop and optimize an artificial intelligence-based image segmentation approach to comprehensively measure muscle volume, fat fraction, fat fraction distribution, and elevated short-tau inversion recovery signal in the musculature of patients with FSHD. Intra-rater, inter-rater, and scan-rescan analyses demonstrated that the developed methods are robust and precise. Representative cases and derived metrics of volume, cross-sectional area, and 3D pixel-maps demonstrate unique intramuscular patterns of disease. Future work focuses on leveraging these AI methods to include upper body output and aggregating individual muscle data across studies to determine best-fit models for characterizing progression and monitoring therapeutic modulation of MRI biomarkers.
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Inteligência Artificial , Progressão da Doença , Imageamento por Ressonância Magnética , Distrofia Muscular Facioescapuloumeral , Humanos , Distrofia Muscular Facioescapuloumeral/diagnóstico por imagem , Distrofia Muscular Facioescapuloumeral/patologia , Imageamento por Ressonância Magnética/métodos , Masculino , Feminino , Pessoa de Meia-Idade , Adulto , Músculo Esquelético/diagnóstico por imagem , Músculo Esquelético/patologia , Processamento de Imagem Assistida por Computador/métodosRESUMO
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.
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Inteligência Artificial , Manguito Rotador , Feminino , Humanos , Atrofia , Imageamento por Ressonância Magnética , Manguito Rotador/diagnóstico por imagem , Comportamento Sexual , MasculinoRESUMO
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.
RESUMO
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.
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BACKGROUND: Multiple sclerosis (MS) is associated with an increased risk of falls, degeneration of sensory organization, and possible increased reliance on vision for balance control. RESEARCH QUESTION: The aim of this study was to assess differences in standing postural control between people with MS and age and sex matched controls during medial-lateral (ML) oscillations of the visual field, with and without blinders to the lower periphery. METHODS: Ten persons with MS (mean age 54.0 ± 5.3 years) and ten age and sex matched controls (mean age: 56.3 ± 6.0 years) participated in this study. Balance control was assessed while participants stood in a Christie Cave system while wearing stereoscopic glasses that projected an immersive forest scene. Visual conditions consisted of 2 m ML visual oscillations of the scene at five frequencies (0.0, 0.3, 0.6, 0.7 and 0.8 Hz) with and without blinders to block the lower periphery. RESULTS AND SIGNIFICANCE: The results demonstrated that, in comparison to controls, participants with MS had a significantly larger center of pressure sway in both the ML and AP direction to ML visual oscillations. Additionally, participants with MS and controls both increased center of pressure frequency content to the visual oscillation frequency, while participants with MS also increased relative power at the visual oscillation frequency in the AP direction. Blinders of lower periphery reduced the percent power at the visual oscillation frequency in both groups and reduced overall sway in participants with MS during visual oscillations. Overall, results indicate that postural balance is sensitive to visual feedback in people with MS. The elicited AP sway to ML visual oscillation could reflect errors in visual processing for the control of balance, and decreased sway in response to blocking vision of the lower peripheral field could indicate an increased reliance on visual cues to maintain balance.
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Esclerose Múltipla , Acidentes por Quedas/prevenção & controle , Retroalimentação Sensorial , Humanos , Pessoa de Meia-Idade , Equilíbrio Postural , Campos VisuaisRESUMO
A hallmark of human locomotion is that it continuously adapts to changes in the environment and predictively adjusts to changes in the terrain, both of which are major challenges to lower limb amputees due to the limitations in prostheses and control algorithms. Here, the ability of a single-network nonlinear autoregressive model to continuously predict future ankle kinematics and kinetics simultaneously across ambulation conditions using lower limb surface electromyography (EMG) signals was examined. Ankle plantarflexor and dorsiflexor EMG from ten healthy young adults were mapped to normal ranges of ankle angle and ankle moment during level overground walking, stair ascent, and stair descent, including transitions between terrains (i.e., transitions to/from staircase). Prediction performance was characterized as a function of the time between current EMG/angle/moment inputs and future angle/moment model predictions (prediction interval), the number of past EMG/angle/moment input values over time (sampling window), and the number of units in the network hidden layer that minimized error between experimentally measured values (targets) and model predictions of ankle angle and moment. Ankle angle and moment predictions were robust across ambulation conditions with root mean squared errors less than 1° and 0.04 Nm/kg, respectively, and cross-correlations (R2) greater than 0.99 for prediction intervals of 58 ms. Model predictions at critical points of trip-related fall risk fell within the variability of the ankle angle and moment targets (Benjamini-Hochberg adjusted p > 0.065). EMG contribution to ankle angle and moment predictions occurred consistently across ambulation conditions and model outputs. EMG signals had the greatest impact on noncyclic regions of gait such as double limb support, transitions between terrains, and around plantarflexion and moment peaks. The use of natural muscle activation patterns to continuously predict variations in normal gait and the model's predictive capabilities to counteract electromechanical inherent delays suggest that this approach could provide robust and intuitive user-driven real-time control of a wide variety of lower limb robotic devices, including active powered ankle-foot prostheses.
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Immersive virtual reality provides a safe and costeffective approach to administrating balance disruption during ambulation. Previous research has explored the effects of applying continuous perturbations in a virtual environment to challenge balance. This pilot study investigates the ability to disrupt balance with discrete visual perturbations during ambulation in healthy young adults. During the study participants walked on a treadmill within a virtual environment. As they walked the entire visual scene was intermittently shifted to the left or right 1 meter over 1 second. The results demonstrate a significant decrease in step length (p <; 0.05) and change in center of mass excursion (p <; 0.05) across participants (N=13). Changes in gait lasted up to three steps after application, suggesting a consistent challenge to dynamic balance control as a result of the discrete visual perturbation . Further, participants did not demonstrate a reduction in response to the discrete visual perturbation with repeated exposure. The results indicate that discrete visual perturbations of a virtual scene can be used to challenge gait and modulate center of mass sway. The use of visual perturbations within a virtual environment to challenge dynamic balance could provide a safer and more affordable avenue for balance rehabilitation by reducing the need for systems that physically perturb balance.