Utilization of Mid-Thigh Magnetic Resonance Imaging to Predict Lean Body Mass and Knee Extensor Strength in Obese Adults

Leg Muscle Volume, Intramuscular Fat and Force Generation: Insights From a Computer-Vision Model and Fat-Water MRI

BACKGROUND

Maintaining skeletal muscle health (i.e., muscle size and quality) is crucial for preserving mobility. Decreases in lower limb muscle volume and increased intramuscular fat (IMF) are common findings in people with impaired mobility. We developed an automated method to extract markers of leg muscle health, muscle volume and IMF, from MRI. We then explored their associations with age, body mass index (BMI), sex and voluntary force generation.

METHODS

We trained (n = 34) and tested (n = 16) a convolutional neural network (CNN) to segment five muscle groups in both legs from fat-water MRI to explore muscle volume and IMF. In 95 participants (70 females, 25 males, mean age [standard deviation] = 34.2 (11.2) years, age range = 18-60 years), we explored associations between the CNN measures and age, BMI and sex, and then in a subset of 75 participants, we explored associations between CNN muscle volume, CNN IMF and maximum plantarflexion force after controlling for age, BMI and sex.

RESULTS

The CNN demonstrated high test accuracy (Sørensen-Dice index ≥ 0.87 for all muscle groups) and reliability (muscle volume ICC2,1 ≥ 0.923 and IMF ICC2,1 ≥ 0.815 for all muscle groups) compared to manual segmentation. CNN muscle volume was positively associated with BMI across all muscle groups (p ≤ 0.001) but not with age (p ≥ 0.406). CNN IMF was positively associated with age for all muscle groups (p ≤ 0.015), and CNN IMF was positively associated with BMI for all muscle groups (p ≤ 0.043) except the right deep posterior compartment (p = 0.130). Males had greater CNN volume of all muscle groups (p < 0.001) except the left and right gastrocnemius (p ≥ 0.067). Gastrocnemius CNN IMF was greater in females (p ≤ 0.043). Plantarflexion force was positively associated with lateral compartment, soleus and gastrocnemius CNN volume (p ≤ 0.025) but not with CNN IMF (p ≥ 0.358).

CONCLUSIONS

Computer-vision models combined with fat-water MRI permits the non-invasive, automatic assessment of leg muscle volume and IMF. Associations with age, BMI and sex are important when interpreting these measures. Markers of leg muscle health may enhance our understanding of the relationship between muscle health, force generation and mobility.

TRIAL REGISTRATION

ClinicalTrials.gov identifier: NCT02157038.

Poor muscle quality: A hidden and detrimental health condition in obesity

Poor muscle quality (MQ) is a hidden health condition in obesity, commonly disregarded and underdiagnosed, associated with poor health-related outcomes. This narrative review provides an in-depth exploration of MQ in obesity, including definitions, available assessment methods and challenges, pathophysiology, association with health outcomes, and potential interventions. MQ is a broad term that can include imaging, histological, functional, or metabolic assessments, evaluating beyond muscle quantity. MQ assessment is highly heterogeneous and requires further standardization. Common definitions of MQ include 1) muscle-specific strength (or functional MQ), the ratio between muscle strength and muscle quantity, and 2) muscle composition (or morphological MQ), mainly evaluating muscle fat infiltration. An individual with obesity might still have normal or higher muscle quantity despite having poor MQ, and techniques for direct measurements are needed. However, the use of body composition and physical function assessments is still limited in clinical practice. Thus, more accessible techniques for assessing strength, muscle mass, and composition should be further explored. Obesity leads to adipocyte dysfunction, generating a low-grade chronic inflammatory state, which leads to mitochondrial dysfunction. Adipocyte and mitochondrial dysfunction result in metabolic dysfunction manifesting clinically as insulin resistance, dyslipidemia, and fat infiltration into organs such as muscle, which in excess is termed myosteatosis. Myosteatosis decreases muscle cell function and insulin sensitivity, creating a vicious cycle of inflammation and metabolic derangements. Myosteatosis increases the risk of poor muscle function, systemic metabolic complications, and mortality, presenting prognostic potential. Interventions shown to improve MQ include nutrition, physical activity/exercise, pharmacology, and metabolic and bariatric surgery.

Time to Reflect on Return to Sport Timing Following ACL Reconstruction

The time of return to sport following anterior cruciate ligament (ACL) reconstruction is a commonly discussed topic within clinical settings and the sports medicine literature. Emerging science has demonstrated protective effects of delaying the time of sport clearance on athlete reinjury. Though a single time cutoff is unlikely to be applicable for all athletes, large inconsistencies in the time of return to sport clearance are present in both the literature and within prescribed clinical protocols. A multitude of patient factors, such as perceived function, objective function, confidence, post-operative goals, among others, are vital for how athletes are progressed and released for sport participation. This Current Opinion article is constructed to discuss the time to return to sport after ACL reconstruction-factors that may influence timing decisions, how time is assessed within the scientific literature-and to promote discussion on this common topic within the sports medicine and athletic communities. The aim of the article is not to establish defined clinical time cutoffs for this population.