Human skeletal muscle size with ultrasound imaging: a comprehensive review

Automatic Segmentation of Quadriceps Femoris Cross-Sectional Area in Ultrasound Images: Development and Validation of Convolutional Neural Networks in People With Anterior Cruciate Ligament Injury and Surgery

OBJECTIVE

Deep learning approaches such as DeepACSA enable automated segmentation of muscle ultrasound cross-sectional area (CSA). Although they provide fast and accurate results, most are developed using data from healthy populations. The changes in muscle size and quality following anterior cruciate ligament (ACL) injury challenges the validity of these automated approaches in the ACL population. Quadriceps muscle CSA is an important outcome following ACL injury; therefore, our aim was to validate DeepACSA, a convolutional neural network (CNN) approach for ACL injury.

METHODS

Quadriceps panoramic CSA ultrasound images (vastus lateralis [VL] n = 430, rectus femoris [RF] n = 349, and vastus medialis [VM] n = 723) from 124 participants with an ACL injury (age 22.8 ± 7.9 y, 61 females) were used to train CNN models. For VL and RF, combined models included extra images from healthy participants (n = 153, age 38.2, range 13-78) that the DeepACSA was developed from. All models were tested on unseen external validation images (n = 100) from ACL-injured participants. Model predicted CSA results were compared to manual segmentation results.

RESULTS

All models showed good comparability (ICC > 0.81, < 14.1% standard error of measurement, mean differences of <1.56 cm2) to manual segmentation. Removal of the erroneous predictions resulted in excellent comparability (ICC > 0.94, < 7.40% standard error of measurement, mean differences of <0.57 cm2). Erroneous predictions were 17% for combined VL, 11% for combined RF, and 20% for ACL-only VM models.

CONCLUSION

The new CNN models provided can be used in ACL-injured populations to measure CSA of VL, RF, and VM muscles automatically. The models yield high comparability to manual segmentation results and reduce the burden of manual segmentation.

Validation of Ultrasound Measurement of Vastus Lateralis for Appendicular Skeletal Muscle Mass in Chronic Kidney Disease Patients with Hemodialysis

BACKGROUND

Chronic kidney disease patients undergoing hemodialysis (HD) are at a high risk of developing sarcopenia. This study aimed to validate the performance of ultrasound (US) measurements of the vastus lateralis (VL) for estimating muscle mass and diagnosing sarcopenia in CKD patients with HD.

METHODS

Forty-six patients were enrolled in this study. Muscle thickness (MT) and echo intensity (EI) of VL, physical performance, and biochemical markers were collected to establish a linear regression model for predicting appendicular skeletal muscle mass (ASM), using dual-energy X-ray absorptiometry (DXA) as the reference standard. The model's performance was validated, and its diagnostic accuracy for sarcopenia was also evaluated.

RESULTS

An ASM prediction model was derived: -20.17 + 1.90 × MT_VL (cm) + 1.58 × male + 0.16 × Height (cm) + 0.09 × Weight (kg) + 0.05 × Age (year), with a standard estimated error of 1.44 kg and adjusted R-squared of 0.84. The model exhibited high correlation and an acceptable limit of agreement, compared to DXA measurement. EI displayed a negative correlation with ASM and MT.

CONCLUSIONS

The ASM adjusted with BMI demonstrated superior performance in diagnosing sarcopenia compared to the ASM adjusted with height. Ultrasound provides a cost-effective bedside tool for evaluating muscle conditions in HD patients.

Skeletal muscle estimation: A review of techniques and their applications

Quantifying skeletal muscle size is necessary to identify those at risk for conditions that increase frailty, morbidity, and mortality, as well as decrease quality of life. Although muscle strength, muscle quality, and physical performance have been suggested as important assessments in the screening, prevention, and management of sarcopenic and cachexic individuals, skeletal muscle size is still a critical objective marker. Several techniques exist for estimating skeletal muscle size; however, each technique presents with unique characteristics regarding simplicity/complexity, cost, radiation dose, accessibility, and portability that are important factors for assessors to consider before applying these modalities in practice. This narrative review presents a discussion centred on the theory and applications of current non-invasive techniques for estimating skeletal muscle size in diverse populations. Common instruments for skeletal muscle assessment include imaging techniques such as computed tomography, magnetic resonance imaging, peripheral quantitative computed tomography, dual-energy X-ray absorptiometry, and Brightness-mode ultrasound, and non-imaging techniques like bioelectrical impedance analysis and anthropometry. Skeletal muscle size can be acquired from these methods using whole-body and/or regional assessments, as well as prediction equations. Notable concerns when conducting assessments include the absence of standardised image acquisition/processing protocols and the variation in cut-off thresholds used to define low skeletal muscle size by clinicians and researchers, which could affect the accuracy and prevalence of diagnoses. Given the importance of evaluating skeletal muscle size, it is imperative practitioners are informed of each technique and their respective strengths and weaknesses.

Validation of an Artificial Intelligence-Based Ultrasound Imaging System for Quantifying Muscle Architecture Parameters of the Rectus Femoris in Disease-Related Malnutrition (DRM)

(1) Background: The aim was to validate an AI-based system compared to the classic method of reading ultrasound images of the rectus femur (RF) muscle in a real cohort of patients with disease-related malnutrition. (2) Methods: One hundred adult patients with DRM aged 18 to 85 years were enrolled. The risk of DRM was assessed by the Global Leadership Initiative on Malnutrition (GLIM). The variation, reproducibility, and reliability of measurements for the RF subcutaneous fat thickness (SFT), muscle thickness (MT), and cross-sectional area (CSA), were measured conventionally with the incorporated tools of a portable ultrasound imaging device (method A) and compared with the automated quantification of the ultrasound imaging system (method B). (3) Results: Measurements obtained using method A (i.e., conventionally) and method B (i.e., raw images analyzed by AI), showed similar values with no significant differences in absolute values and coefficients of variation, 58.39-57.68% for SFT, 30.50-28.36% for MT, and 36.50-36.91% for CSA, respectively. The Intraclass Correlation Coefficient (ICC) for reliability and consistency analysis between methods A and B showed correlations of 0.912 and 95% CI [0.872-0.940] for SFT, 0.960 and 95% CI [0.941-0.973] for MT, and 0.995 and 95% CI [0.993-0.997] for CSA; the Bland-Altman Analysis shows that the spread of points is quite uniform around the bias lines with no evidence of strong bias for any variable. (4) Conclusions: The study demonstrated the consistency and reliability of this new automatic system based on machine learning and AI for the quantification of ultrasound imaging of the muscle architecture parameters of the rectus femoris muscle compared with the conventional method of measurement.

Association between physical fitness tests and neuromuscular properties

PURPOSE

While various fitness tests have been developed to assess physical performances, it is unclear how these tests are affected by differences, such as, in morphological and neural factors. This study was aimed to investigate associations between individual differences in physical fitness tests and neuromuscular properties.

METHODS

One hundred and thirty-three young adults participated in various general physical fitness tests and neuromuscular measurements. The appendicular skeletal muscle mass (ASM) was estimated by bioelectrical impedance analysis. Echo intensity (EI) was evaluated from the vastus lateralis. During submaximal knee extension force, high-density surface electromyography of the vastus lateralis was recorded and individual motor unit firings were detected. Y-intercept (i-MU) and slope (s-MU) from the regression line between the recruitment threshold and motor unit firing rate were calculated.

RESULTS

Stepwise multiple regression analyses revealed that knee extension strength could be explained (adjusted R2 = 0.712) by ASM (β = 0.723), i-MU (0.317), EI (- 0.177), and s-MU (0.210). Five-sec stepping could be explained by ASM (adjusted R2 = 0.212). Grip strength, side-stepping, and standing broad jump could be explained by ASM and echo intensity (adjusted R2 = 0.686, 0.354, and 0.627, respectively). Squat jump could be explained by EI (adjusted R2 = 0.640). Counter-movement jump could be explained by EI and s-MU (adjusted R2 = 0.631). On the other hand, i-MU and s-MU could be explained by five-sec stepping and counter-movement jump, respectively, but the coefficients of determination were low (adjusted R2 = 0.100 and 0.045).

CONCLUSION

Generally developed physical fitness tests were mainly explained by morphological factors, but were weakly affected by neural factors involved in performance.

Fully Automated Analysis of Muscle Architecture from B-Mode Ultrasound Images with DL_Track_US

OBJECTIVE

B-mode ultrasound can be used to image musculoskeletal tissues, but one major bottleneck is analyses of muscle architectural parameters (i.e., muscle thickness, pennation angle and fascicle length), which are most often performed manually.

METHODS

In this study we trained two different neural networks (classic U-Net and U-Net with VGG16 pre-trained encoder) to detect muscle fascicles and aponeuroses using a set of labeled musculoskeletal ultrasound images. We determined the best-performing model based on intersection over union and loss metrics. We then compared neural network predictions on an unseen test set with those obtained via manual analysis and two existing semi/automated analysis approaches (simple muscle architecture analysis [SMA] and UltraTrack). DL_Track_US detects the locations of the superficial and deep aponeuroses, as well as multiple fascicle fragments per image.

RESULTS

For single images, DL_Track_US yielded results similar to those produced by a non-trainable automated method (SMA; mean difference in fascicle length: 5.1 mm) and human manual analysis (mean difference: -2.4 mm). Between-method differences in pennation angle were within 1.5°, and mean differences in muscle thickness were less than 1 mm. Similarly, for videos, there was overlap between the results produced with UltraTrack and DL_Track_US, with intraclass correlations ranging between 0.19 and 0.88.

CONCLUSION

DL_Track_US is fully automated and open source and can estimate fascicle length, pennation angle and muscle thickness from single images or videos, as well as from multiple superficial muscles. We also provide a user interface and all necessary code and training data for custom model development.

Exploring the Intersection of Geophysics and Diagnostic Imaging in the Health Sciences

To develop diagnostic imaging approaches, this paper emphasizes the transformational potential of merging geophysics with health sciences. Diagnostic imaging technology improvements have transformed the health sciences by enabling earlier and more precise disease identification, individualized therapy, and improved patient care. This review article examines the connection between geophysics and diagnostic imaging in the field of health sciences. Geophysics, which is typically used to explore Earth's subsurface, has provided new uses of its methodology in the medical field, providing innovative solutions to pressing medical problems. The article examines the different geophysical techniques like electrical imaging, seismic imaging, and geophysics and their corresponding imaging techniques used in health sciences like tomography, magnetic resonance imaging, ultrasound imaging, etc. The examination includes the description, similarities, differences, and challenges associated with these techniques and how modified geophysical techniques can be used in imaging methods in health sciences. Examining the progression of each method from geophysics to medical imaging and its contributions to illness diagnosis, treatment planning, and monitoring are highlighted. Also, the utilization of geophysical data analysis techniques like signal processing and inversion techniques in image processing in health sciences has been briefly explained, along with different mathematical and computational tools in geophysics and how they can be implemented for image processing in health sciences. The key findings include the development of machine learning and artificial intelligence in geophysics-driven medical imaging, demonstrating the revolutionary effects of data-driven methods on precision, speed, and predictive modeling.

Compensation strategy of shoulder synergist muscles is not stereotypical in patients with rotator cuff repair

Rotator cuff tear is a common shoulder injury that causes shoulder dysfunction and pain. Although surgical repair is the primary treatment for rotator cuff tear, it is well recognized that impaired force exertion of muscles connecting to the involved tendon and subsequent complemental change in the force exertion of synergist muscles persist even after repair. This study aimed to identify the compensation strategy of shoulder abductors by examining how synergist muscles respond to supraspinatus (SSP) muscle force deficit in patients with rotator cuff repair. Muscle shear modulus, an index of muscle force, was assessed for SSP, infraspinatus, upper trapezius, and middle deltoid muscles in repaired and contralateral control shoulders of 15 patients with unilateral tendon repair of the SSP muscle using ultrasound shear wave elastography while the patients passively or actively held their arm in shoulder abduction. In the repaired shoulder, the shear modulus of the SSP muscle declined, whereas that of other synergist muscles did not differ relative to that of the control. To find the association between the affected SSP and each of the synergist muscles, a regression analysis was used to assess the shear moduli at the population level. However, no association was observed between them. At the individual level, there was a tendency of variation among patients with regard to a specific muscle whose shear modulus complementarily increased. These results suggest that the compensation strategy for SSP muscle force deficit varies among individuals, being nonstereotypical in patients with rotator cuff injury.

Ultrasound measurement of vastus lateralis and vastus medialis muscle parameters to identify chronic thyrotoxic myopathy

Introduction

Chronic thyrotoxic myopathy (CTM) is a common, easily neglected complication of hyperthyroidism. There are currently no standard diagnostic criteria for CTM, and the ultrasonic characteristics of CTM-affected skeletal muscle remain unclear. Herein, we aimed to evaluate hyperthyroid patients for CTM by ultrasound and identify ultrasonic muscle parameter cutoffs for CTM diagnosis.

Materials and methods

Each participant underwent ultrasonography. The original (muscle thickness (MT), pennation angle (PA), and cross-sectional area (CSA)) and corrected (MT/height (HT), MT/body mass index (BMI), CSA/HT, and CSA/BMI) parameters of the vastus lateralis and vastus medialis (VM) were evaluated. The diagnostic effectiveness of ultrasound for predicting CTM was determined using receiver operating characteristic (ROC) curve analysis. Our study included 203 participants: 67 CTM patients (18 males, 49 females), 67 non-CTM patients (28 males, 39 females) and 69 healthy controls (20 males, 49 females).

Results

The CTM group had lower muscular ultrasonic and anthropometric parameters, higher thyroid hormone and thyroid-stimulating hormone receptor antibody (TRAb) levels, and a longer duration of hyperthyroidism than the non-CTM group (P < 0.05). The VM-PA, VM-CSA, VM-CSA/HT, and VM-CSA/BMI were lower in females than in males (P < 0.05). Free thyroxine (FT4) and TRAb both showed significant negative correlations with VM-MT, VM-MT/HT, VM-CSA, and VM-CSA/HT (P < 0.05). VM-MT/BMI and VM-CSA/HT, respectively, best predicted male and female CTM (AUC = 0.84, 0.85; cutoff ≤ 0.07, < 4.01).

Conclusion

Ultrasound measurement of muscular parameters, especially in the VM, is a valid and feasible way of diagnosing and characterizing possible CTM in hyperthyroidism.

Construct and criterion validity of muscle ultrasonography for assessment of skeletal muscle in patients recovering from COVID-19

Background: The purpose was to investigate the content, construct, and criterion validity of muscle ultrasound in a mixed cohort of participants recovering from mild and critical COVID-19. Methods: A secondary analysis of a prospective cross-sectional study was conducted on data obtained from a battery of muscle and physical function assessments including a muscle biopsy and muscle ultrasonography (US). Rectus femoris (RF) muscle thickness (mT), quadricep complex (QC) mT, RF muscle cross-sectional area (CSA) using 2D freeform trace and estimated from Feret's diameter, and RF echo intensity (EI) were assessed with US. Muscle fiber CSA, fiber type, protein content in muscle fibers, extracellular matrix content (ECM; wheat-germ agglutin), and percent area of collagen in ECM (picrosirius red) were examined from vastus lateralis muscle biopsies. Spearman rho correlations (r) were performed to assess validity of ultrasound parameters. Results: Thirty-three individuals participated including 11 patients surviving critical COVID-19, 15 individuals recovering from mild-COVID, and 7 controls. There were several significant correlations between RF mT, QC mT, RF CSA, and RF EI with age, comorbid burden, body-mass index, and measures of muscle strength, muscle power, and physical function (range r = 0.35-0.83). RF Feret's CSA correlated to CSA of type II muscle fibers (r = 0.41, p = 0.022) and the average size of all muscle fibers (r = 0.39, p = 0.031). RF EI was correlated with collagen in muscle ECM (r = 0.53, p = 0.003) and protein content in muscle tissue (r = -0.52, p = 0.012). Conclusion: Muscle size and quality measured using US has moderate content and construct validity, and to lesser extent, fair to moderate criterion validity in a mixed cohort of individuals recovering from COVID. Muscle ultrasound quality (EI) appears to be sensitive at detecting muscle dysfunction as it is associated with strength, power, physical function, and collagen distribution in a mixed group of individuals recovering from COVID-19.

Lightweight Force-Controlled Device for Freehand Ultrasound Acquisition

This study investigates a force-controlled auxiliary device for freehand ultrasound (US) examinations. The designed device allows sonographers to maintain a steady target pressure on the US probe, thereby improving the US image quality and reproducibility. The use of a screw motor to power the device and a Raspberry Pi as the system controller results in a lightweight and portable device, while a screen enhances user-interactivity. Using gravity compensation, error compensation, an adaptive proportional-integral-derivative algorithm, and low-pass signal filtering, the designed device provides highly accurate force control. Several experiments using the developed device, including clinical trials relating to the jugular and superficial femoral veins, validate its utility in ensuring the desired pressure in response to varying environments and prolonged US examinations, enabling low or high pressures to be maintained and lowering the threshold of clinical experience. Moreover, the experimental results show that the designed device effectively relieves the stress on the sonographer's hand joints during US examinations and enables rapid assessment of the tissue elasticity characteristics. With automatic pressure tracking between probe and patient, the proposed device offers potentially significant benefits for the reproducibility and stability of US images and the health of sonographers.

Transversus Abdominis Ultrasound Thickness during Popular Trunk-Pilates Exercises in Young and Middle-Aged Women

The transversus abdominis (TrA) is a core muscle that contributes to functional mobility and lumbar stability. This study aimed to compare the changes in TrA thickness during different Pilates exercises, and to identify the exercise that elicited the greatest TrA activation. Forty-four healthy women were divided into two groups: young (25-35 years old) and middle-aged (36-55 years old). TrA thickness was assessed by ultrasound while the participants performed five Pilates exercises: basic position, hundred, hip roll, side plank, and dead bug. A repeated measures analysis of variance revealed that the dead bug exercise induced a significantly higher increase in TrA thickness (relative to rest) than the other exercises (p < 0.05). The young group also showed a significantly higher overall TrA thickness than the middle-aged group (p < 0.05). The findings suggest that the dead bug exercise is the most effective for enhancing TrA activation among the Pilates exercises tested. The basic position and the hundred exercises can be used as warm-up exercises before performing more challenging exercises such as the hip roll, the side plank, and the dead bug. The sequence of exercises can be similar for both young and middle-aged women.

Human skeletal muscle-specific atrophy with aging: a comprehensive review

Age-related skeletal muscle atrophy appears to be a muscle group-specific process, yet only a few specific muscles have been investigated and our understanding in this area is limited. This review provides a comprehensive summary of the available information on age-related skeletal muscle atrophy in a muscle-specific manner, nearly half of which comes from the quadriceps. Decline in muscle-specific size over ∼50 yr of aging was determined from 47 cross-sectional studies of 982 young (∼25 yr) and 1,003 old (∼75 yr) individuals and nine muscle groups: elbow extensors (-20%, -0.39%/yr), elbow flexors (-19%, -0.38%/yr), paraspinals (-24%, -0.47%/yr), psoas (-29%, -0.58%/yr), hip adductors (-13%, -0.27%/yr), hamstrings (-19%, -0.39%/yr), quadriceps (-27%, -0.53%/yr), dorsiflexors (-9%, -0.19%/yr), and triceps surae (-14%, -0.28%/yr). Muscle-specific atrophy rate was also determined for each of the subcomponent muscles in the hamstrings, quadriceps, and triceps surae. Of all the muscles included in this review, there was more than a fivefold difference between the least (-6%, -0.13%/yr, soleus) to the most (-33%, -0.66%/yr, rectus femoris) atrophying muscles. Muscle activity level, muscle fiber type, sex, and timeline of the aging process all appeared to have some influence on muscle-specific atrophy. Given the large range of muscle-specific atrophy and the large number of muscles that have not been investigated, more muscle-specific information could expand our understanding of functional deficits that develop with aging and help guide muscle-specific interventions to improve the quality of life of aging women and men.

In vivoestimation of anisotropic mechanical properties of the gastrocnemius during functional loading with MR elastography

Objective.In vivoimaging assessments of skeletal muscle structure and function allow for longitudinal quantification of tissue health. Magnetic resonance elastography (MRE) non-invasively quantifies tissue mechanical properties, allowing for evaluation of skeletal muscle biomechanics in response to loading, creating a better understanding of muscle functional health.Approach. In this study, we analyze the anisotropic mechanical response of calf muscles using MRE with a transversely isotropic, nonlinear inversion algorithm (TI-NLI) to investigate the role of muscle fiber stiffening under load. We estimate anisotropic material parameters including fiber shear stiffness (μ1), substrate shear stiffness (μ2), shear anisotropy (ϕ), and tensile anisotropy (ζ) of the gastrocnemius muscle in response to both passive and active tension.Main results. In passive tension, we found a significant increase inμ1,ϕ,andζwith increasing muscle length. While in active tension, we observed increasingμ2and decreasingϕandζduring active dorsiflexion and plantarflexion-indicating less anisotropy-with greater effects when the muscles act as agonist.Significance. The study demonstrates the ability of this anisotropic MRE method to capture the multifaceted mechanical response of skeletal muscle to tissue loading from muscle lengthening and contraction.

Effects of Low- Versus High-Velocity-Loss Thresholds With Similar Training Volume on Maximal Strength and Hypertrophy in Highly Trained Individuals

AIMS

In the present intervention study, low-velocity-loss (LVL) versus high-velocity-loss (HVL) thresholds in the squat and bench press were compared for changes in muscle strength, power, and hypertrophy.

METHODS

Strength-trained volunteers (7♀ and 9♂; age: 27.2 [3.4] y; height: 174.6 [8.0] cm; body mass: 75.3 [10.1] kg) were randomized into an LVL or HVL threshold group (LVL n = 3♀ + 5♂, and HVL n = 4♀ + 4♂). Training took place 3 times per week over 6 weeks (loads: ∼75%-90% of 1-repetition maximum [1RM]). The thresholds of LVLs and HVLs were set at 20% and 40% of maximal velocity, respectively, for the squat, and at 30% and 60%, respectively, for the bench press. Before and after the intervention, 1RM, leg press power, and squat jump were tested. The load (∼45% of 1RM) corresponding to 1-m/s velocity was assessed in all sessions for both exercises. In addition, the thickness of the vastus lateralis and triceps brachii and body composition (dual-energy X-ray absorptiometry [DEXA]) were measured.

RESULTS

Squat and bench-press 1RM increased similarly in both groups by 7% to 11% (SD: 4%-6%, P < .05). No group differences were observed for changes in jump height, leg press power, or DEXA lean mass. However, HVL showed a small increase in muscle thickness of the vastus lateralis compared with LVL (6 ± 6% [95% CI] group difference, P < .05).

CONCLUSION

For strength-trained individuals, high-volume lower-velocity-loss thresholds were as effective as higher thresholds for improvements in 1RM strength; but local hypertrophy was seemingly elicited faster with higher velocity-loss thresholds.

Effect of radioiodine treatment on muscle mass in hyperthyroid cats

BACKGROUND

Approximately 75% of hyperthyroid cats lose muscle mass as accessed with a muscle condition scoring (MCS) system. After treatment, MCS improves as the cats regain muscle mass.

OBJECTIVES

To quantify the degree of muscle loss in hyperthyroid cats using ultrasonography and evaluate changes in muscle mass after treatment.

ANIMALS

Forty-eight clinically normal cats and 120 cats with untreated hyperthyroidism, 75 of which were reevaluated after radioiodine-131 therapy.

METHODS

Prospective cross-sectional and before-after studies. All cats underwent ultrasonography and measurement of epaxial muscle height (EMH), with subsequent calculation of vertebral and forelimb epaxial muscle scores (VEMS and FLEMS). A subset of hyperthyroid cats underwent repeat muscle imaging 6 months after treatment.

RESULTS

Untreated hyperthyroid cats had a lower EMH than did clinically normal cats (median [25th-75th percentile], 0.98 [0.88-1.16] cm vs 1.34 [1.23-1.58] cm, P < .001). Seventy-seven (64.2%) untreated cats had subnormal EMH. Similarly, compared to normal cats, hyperthyroid cats had lower VEMS (0.93 [0.84-1.07] vs 1.27 [1.18-1.39], P < .001) and FLEMS (1.24 [1.10-1.35] vs 1.49 [1.39-1.63], P < .001). After treatment, EMH increased (1.03 [0.89-1.03] cm to 1.33 [1.17-1.41] cm, P < .001), with abnormally low EMH normalizing in 36/41 (88%). Both VEMS (0.94 [0.87-1.10] to 1.21 [1.10-1.31], P < .001) and FLEMS (1.31 [1.17-1.40] to 1.47 [1.38-1.66], P < .001) also increased after treatment.

CONCLUSIONS AND CLINICAL IMPORTANCE

Almost two-thirds of hyperthyroid cats have abnormally low muscle mass when measured quantitatively by ultrasound. Successful treatment restores muscle mass in >85% of cats. EMH provided the best means of quantitating muscle mass in these cats.