Hand function is critical for daily activities and declines early in many diseases, conditions or disorders affecting the musculoskeletal and neurologic systems. Muscle health markers derived from clinically available magnetic resonance imaging (MRI) scans are strongly associated with functional capacity, may enhance clinical assessment and inform management options. However, traditional muscle MRI assessments require time-intensive manual segmentations. Here, we aim to develop and test a computer-vision model for automated forearm muscle segmentation and investigate associations between MRI-derived muscle markers and age, sex, BMI, functional grip strength and dexterity measures.
We recruited 42 healthy, right-handed adults (54.8% female, median age 37.3 years, median BMI: 23.0). Grip strength and dexterity were measured using the NIH Toolbox motor battery. Dixon fat-water MRI of the right forearm was acquired at 3.0 T, and forearm flexor and extensor muscle compartments were manually segmented for model training. A 2D U-Net convolutional neural network model was trained and tested for segmentation of the forearm flexors and extensors for the assessment of muscle volume and intramuscular fat. Testing accuracy and reliability were assessed using Sørensen–Dice indices, intraclass correlation coefficients (ICCs) and Bland–Altman analyses. Associations between the MRI-derived muscle markers, demographic factors, muscle metrics and hand function were evaluated using partial correlations and regression models.
The segmentation model showed high test accuracy, achieving mean Sørensen–Dice indices of 0.89 (flexors) and 0.85 (extensors) and ICCs of 0.75–0.99 for muscle volume and intramuscular fat. Muscle volume was positively correlated with BMI (p < 0.001) but not age (p > 0.249). Males had larger muscle volumes than females (p < 0.001), with no sex differences in intramuscular fat (p > 0.141), and no association between intramuscular fat and grip strength or dexterity (p > 0.350). We observed strong positive correlations between grip strength and both flexor (p = 0.004) and extensor (p = 0.001) muscle volumes, while dexterity showed no significant associations.
Our findings highlight the accuracy and reliability of automated forearm muscle segmentation using computer vision. BMI emerged as a key determinant of m
Sarcopenia, defined as the loss of skeletal muscle mass and function, is associated with worse postoperative outcomes and reduced survival in patients undergoing surgery for solid tumours, including renal cell carcinoma (RCC). Although radiographic assessment using the skeletal muscle index (SMI) at the L3 vertebral level has emerged as a method for quantifying sarcopenia, a consensus on optimal sarcopenia thresholds, especially in non-metastatic RCC, remains lacking. This study aims to evaluate which of the existing published SMI thresholds can be utilized to predict overall survival (OS) in a racially diverse non-metastatic (nmRCC) cohort.
We retrospectively reviewed 343 patients with any T-stage nmRCC who underwent nephrectomy between 2007 and 2022 at our institution. SMI (cm2/m2) values were calculated using cross-sectional imaging at the L3 level. Six published sarcopenia thresholds were applied. Associations between threshold-defined sarcopenia and OS were evaluated using Kaplan–Meier curves and Cox proportional hazards models adjusted for confounding variables.
Three hundred forty-three patients met inclusion criteria, 62.7% were White, and 33.2% were Black. Median follow-up time was 41.5 months (IQR 17.8–61.7 months), during which there were 62 (18.1%) mortality events. Median SMI measurements for males and females in our cohort were 51.1 and 42.4 cm/m2, respectively. Patients defined as radiographically sarcopenic using thresholds by Derstine et al. (HR 2.11 [95% CI 1.14–3.91], p = 0.018) and Tonnesen et al. (HR 2.11 [95% CI 1.15–4.53], p = 0.028) had independently associated worse OS. Notably, these thresholds were constructed from healthy adult populations.
SMI thresholds derived from healthy cohorts, as proposed by Derstine et al., are associated with OS in patients with nmRCC and may serve as clinically practical tools for identifying high-risk patients. Incorporating radiographic sarcopenia assessment into preoperative workflows may facilitate targeted prehabilitation interventions aimed at improving survival outcomes in this population.
Impaired muscle function is frequent in cirrhosis and potentially participates in liver disease progression. Data from non-cirrhotic patients with steatotic liver disease (SLD) are lacking. Our aims were to determine if muscle function was impaired in a non-cirrhotic cohort of patients with SLD and if the SLD subtype and severity were associated with impaired muscle function.
Patients with SLD and controls were prospectively recruited. Liver disease was assessed by imaging, vibration-controlled transient elastography and non-invasive tests. Muscle function was assessed by the liver frailty index (LFI) and isokinetic dynamometer. Diet and physical activity habits were recorded using dedicated questionnaires to measure the energetic balance.
One-hundred and fifty patients with non-cirrhotic SLD (75 patients with metabolic dysfunction-associated steatotic liver disease [MASLD] and 75 patients with alcohol-related liver disease [ALD]) and 30 non-SLD controls were prospectively recruited. The LFI negatively correlated to lower limb muscle strength assessed by isokinetic dynamometer in all participant groups (r = 0.82 in the control group; r = 0.69 in the pooled SLD group—p < 0.0001). Both SLD groups showed muscle strength impairment assessed by the LFI compared to age- and gender-matched controls. In multivariate analysis, the presence of SLD was associated with impaired muscle function independently of age, BMI and energetic balance, with a higher risk related to ALD.
Patients with SLD already show impaired muscle function compared to controls independently of age, gender and energetic balance. Taken together, our data support a potential disruption of the liver–muscle axis already occurring in SLD prior to cirrhosis.
ClinicalTrials.gov identifier: NCT06514300
Variance in skeletal muscle area (SMA), visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT) negatively impacts outcomes after pancreas surgery. We aim to incorporate an existing deep learning algorithm automating body composition segmentation from computed tomography (CT) for accurate and rapid risk identification.
We conducted a retrospective study of patients having pancreatic surgery at a high-volume centre (2016–2021). Using a deep learning algorithm, we analysed preoperative CT images at the L3 level for SMA, VAT, SAT and IMAT (AutoMATiCA, Cambridge, MA, USA). Two board-certified radiologists validated the analysis. Skeletal muscle index (SMI), VAT and VAT/SAT ratio were calculated. We then evaluated the incidence of pancreas surgery-specific, pulmonary, noninfectious and infectious outcomes.
We reviewed 158 patients: median (IQR) age 67.6 (61.6, 75.3) years; female (52.5%); pancreatic cancer diagnoses (65.8%); and Whipple procedure (81%). Automated body composition calculation time for all patients was 553 s. Patients experiencing composite sepsis complications had higher VAT (193.7 [IQR 132.7, 249.7] vs. 146.2 [IQR 87.3, 220.5], p = 0.029). Additionally, patients experiencing composite infectious complications had higher VAT (193.7 [IQR 133.4, 277.5] vs. 143.1 [IQR 72.2, 202.8], p = 0.041). VAT was also higher in patients with noninfectious complications (274.9 [IQR 228.0, 329.8] vs. 148.7 [IQR 90.9, 221.0]; p = 0.020). Other anthropomorphic features, such as SMA, SAT and IMAT, did not have any relation to postoperative composite outcomes.
Higher visceral adipose tissue was associated with worse outcomes after pancreas surgery. Deep learning applied to CT scans may be valuable for identifying at-risk body compositions associated with adverse surgical outcomes. Further studies are needed to confirm these findings.
Colorectal cancer (CRC) is the fourth most common cancer in the United Kingdom, accounting for ~11% of new cancer diagnoses. CRC is predominantly a disease of ageing, and its occurrence often coincides with an age-associated decline in physiological performance. The stress of surgery can also leave cancer survivors functionally limited. Exercise-based prehabilitation may ameliorate some of the functional decline seen after surgery for CRC, with resistance exercise training (RET) increasingly recognised as an important driver of physiological adaptation in this context. Although prehabilitation with a RET component in operable CRC has been studied, no systematic review exists. This systematic review and meta-analysis aims to delineate the effects of prehabilitation with a RET component in patients with CRC treated with surgery with curative intent, on clinical and functional outcomes.
This systematic review and meta-analysis (PROSPERO: CRD42023421372) was performed in accordance with the PRISMA 2020 statement and PERSiST guidelines. Studies on adults with histologically confirmed or clinically suspected colorectal neoplasia scheduled for surgery with curative intent, undergoing short-course (< 12-week) pre-operative RET were sought via searches on CINAHL, CENTRAL, Embase, Medline, PubMed, Clinicaltrials.gov and ICTRP.
After eligibility review, risk of bias assessment was undertaken and data extracted. Meta-analysis was undertaken on clinical and functional outcomes.
Database searches revealed 5808 reports including 1910 duplicates. Citation searching detected nine reports, and a final 18 were discovered after searching clinical trial databases. After exclusions, eight reports representing 324 (n = 136 female; 42.0%) individuals with CRC were included for systematic review and considered for meta-analysis. All studies were found to carry ‘high’ or ‘critical’ risk of bias. Criteria for meta-analysis was reached for four outcomes: postoperative complications, length-of-stay, 6-min walk test (6MWT) and handgrip strength (HGS). Prehabilitation with a RET component demonstrated statistical and clinically significant increases in 6MWT distance (mean difference [MD]: 34.14 m, 95% confidence intervals [CI]: 16 to 52.27 m). There was no significant difference in postoperative complications (odds ratio: 0.77, 95% CI: 0.47 to 1.29), length-of-stay (MD: 3.02 days, 95% CI: −6.26 days to 0.21 days) or HGS (MD: 0.22 kg, 95% CI: −0.83 kg to 1.27 kg).
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