scholarly journals SUN-390 Computed Tomography Derived Skeletal Muscle Radiodensity Is Better Predictor of Muscle Power Than Skeletal Muscle Area in Community-Dwelling Older Adults

2020 ◽  
Vol 4 (Supplement_1) ◽  
Author(s):  
Heewon Choi ◽  
Namki Hong ◽  
Narae Park ◽  
Chang Oh Kim ◽  
Hyeon Chang Kim ◽  
...  
Keyword(s):  
Risk Factors ◽  
Computed Tomography ◽  
Skeletal Muscle ◽  
Muscle Function ◽  
Community Dwelling ◽  
Muscle Area ◽  
Jump Power ◽  
Skeletal Muscle Area ◽  
Community Dwelling Older Adults ◽  
Conventional Risk Factors

Abstract Computed tomography (CT) derived skeletal muscle area (SMA) and muscle radiodensity (SMD) reflect distinctive quantitative, qualitative characteristics of skeletal muscle. Peak jump power reflects the ability to exert force within a limited time, which has greater relationship with mobility and risk of falls. CT-based SMA and SMD may have potential as useful surrogates for muscle function. However, the association of CT-based muscle parameters, especially SMD, with peak jump power has not been investigated yet. Community-dwelling older adults enrolled in the Korean Urban Rural Elderly study from 2016 to 2018 underwent abdominal CT scans and countermovement two-legged jumping test on ground reaction force platform. SMA and SMD were measured at CT images at L3 vertebral level. Mean age of 1523 patients was 74.7 years and 65.1% was female. For peak jump force, L3SMA was stronger contributing factor than SMD (standardized beta of SMA vs. SMD = 0.16 vs. 0.08 for men; 0.12 vs. 0.05 for women; p < 0.05 for all). However, SMD was a better indicator of peak jump power compared to SMA in both sexes (standardized beta of SMD vs. SMA = 0.21 vs. 0.17 for men; 0.15 vs. 0.13 for women; p < 0.05 for all). These associations remained robust even after adjustment for age, height, weight, triglyceride, HDL cholesterol, high sensitivity C-reactive protein, and insulin resistance. One standard deviation decrease of SMD was associated with 8% elevated odds of low jump power relative to weight after adjustment for potential confounders (adjusted OR = 1.08, p < 0.001), whereas the association between SMA and low jump power was attenuated. SMD improved discrimination for individuals with low jump power when added to SMA and conventional risk factors (Area under the receiver-operating characteristics curve 0.732 to 0.750, p=0.006). SMD was an independent predictor of jump power with additive discriminatory value to SMA and conventional risk factors. Our findings suggest the potential complimentary role of SMD as muscle quality indicator beyond muscle mass as a surrogate for muscle function.

Marked losses of computed tomography–derived skeletal muscle area and density over the first month of a critical illness are not associated with energy and protein delivery

Nutrition ◽  
2021 ◽  
Vol 82 ◽  
pp. 111061
Author(s):  
Kate J. Lambell ◽  
Gerard S. Goh ◽  
Audrey C. Tierney ◽  
Adrienne Forsyth ◽  
Vinodh Nanjayya ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Skeletal Muscle ◽  
Critical Illness ◽  
Protein Delivery ◽  
Muscle Area ◽  
Skeletal Muscle Area

scholarly journals Computed tomography-based psoas skeletal muscle area and radiodensity are poor sentinels for whole L3 skeletal muscle values

2020 ◽  
Vol 39 (7) ◽  
pp. 2227-2232 ◽  
Author(s):  
Katie E. Rollins ◽  
Aravin Gopinath ◽  
Amir Awwad ◽  
Ian A. Macdonald ◽  
Dileep N. Lobo
Keyword(s):  
Computed Tomography ◽  
Skeletal Muscle ◽  
Muscle Area ◽  
Skeletal Muscle Area

scholarly journals Milk and resistance exercise intervention to improve muscle function in community-dwelling older adults at risk of sarcopenia (MIlkMAN): protocol for a pilot study

BMJ Open ◽  
2019 ◽  
Vol 9 (10) ◽  
pp. e031048 ◽  
Author(s):  
Antoneta Granic ◽  
Christopher Hurst ◽  
Lorelle Dismore ◽  
Karen Davies ◽  
Emma Stevenson ◽  
...  
Keyword(s):  
Older Adults ◽  
Skeletal Muscle ◽  
At Risk ◽  
Pilot Study ◽  
Resistance Exercise ◽  
Muscle Function ◽  
Community Dwelling ◽  
Skimmed Milk ◽  
And Function ◽  
Community Dwelling Older Adults

IntroductionSarcopenia is a progressive muscle disorder characterised by decline in skeletal muscle mass, strength and function leading to adverse health outcomes, including falls, frailty, poor quality of life and death. It occurs more commonly in older people and can be accelerated by poor diet and low physical activity. Intervention studies incorporating higher dietary protein intakes or protein supplementation combined with resistance exercise (RE) have been shown to limit muscle function decline. However, less is known about the role of whole foods in reducing the risk of sarcopenia. Milk is a source of high-quality nutrients, which may be beneficial for skeletal muscle. This pilot study examines the feasibility and acceptability of milk consumption with RE to improve muscle function in community-dwelling older adults at risk of sarcopenia.Methods and analysis30 older adults aged ≥65 years will be randomly allocated to three groups: ‘whole milk+RE’, ‘skimmed milk+RE’ or ‘control drink+RE’. Assessments will take place in participants’ homes, including screening (milk allergies, grip strength, walking speed), baseline and postintervention health and function. All participants will undertake a structured RE intervention twice a week for 6 weeks at a local gym, followed by the consumption of 500 mL of whole or skimmed milk (each ~20 g of protein) or an isocaloric control drink and another 500 mL at home. Participants’ views about the study will be assessed using standardised open-ended questions. The primary outcomes include feasibility and acceptability of the intervention with recruitment, retention and intervention response rates. Analyses will include descriptive statistics, exploration of qualitative themes and intervention fidelity.Ethics and disseminationOutputs include pilot data to support funding applications; public involvement events; presentation at conferences and peer-reviewed publication.Trial registration numberISRCTN13398279; Pre-results.

scholarly journals A Deep Learning Model to Automate Skeletal Muscle Area Measurement on Computed Tomography Images

2021 ◽  
Vol 11 ◽  
Author(s):  
Kaushalya C. Amarasinghe ◽  
Jamie Lopes ◽  
Julian Beraldo ◽  
Nicole Kiss ◽  
Nicholas Bucknell ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Skeletal Muscle ◽  
Observer Variation ◽  
Ct Scans ◽  
Muscle Area ◽  
Curative Intent ◽  
Pet Ct ◽  
Skeletal Muscle Area ◽  
Nsclc Patients ◽  
Testing Set

BackgroundMuscle wasting (Sarcopenia) is associated with poor outcomes in cancer patients. Early identification of sarcopenia can facilitate nutritional and exercise intervention. Cross-sectional skeletal muscle (SM) area at the third lumbar vertebra (L3) slice of a computed tomography (CT) image is increasingly used to assess body composition and calculate SM index (SMI), a validated surrogate marker for sarcopenia in cancer. Manual segmentation of SM requires multiple steps, which limits use in routine clinical practice. This project aims to develop an automatic method to segment L3 muscle in CT scans.MethodsAttenuation correction CTs from full body PET-CT scans from patients enrolled in two prospective trials were used. The training set consisted of 66 non-small cell lung cancer (NSCLC) patients who underwent curative intent radiotherapy. An additional 42 NSCLC patients prescribed curative intent chemo-radiotherapy from a second trial were used for testing. Each patient had multiple CT scans taken at different time points prior to and post- treatment (147 CTs in the training and validation set and 116 CTs in the independent testing set). Skeletal muscle at L3 vertebra was manually segmented by two observers, according to the Alberta protocol to serve as ground truth labels. This included 40 images segmented by both observers to measure inter-observer variation. An ensemble of 2.5D fully convolutional neural networks (U-Nets) was used to perform the segmentation. The final layer of U-Net produced the binary classification of the pixels into muscle and non-muscle area. The model performance was calculated using Dice score and absolute percentage error (APE) in skeletal muscle area between manual and automated contours.ResultsWe trained five 2.5D U-Nets using 5-fold cross validation and used them to predict the contours in the testing set. The model achieved a mean Dice score of 0.92 and an APE of 3.1% on the independent testing set. This was similar to inter-observer variation of 0.96 and 2.9% for mean Dice and APE respectively. We further quantified the performance of sarcopenia classification using computer generated skeletal muscle area. To meet a clinical diagnosis of sarcopenia based on Alberta protocol the model achieved a sensitivity of 84% and a specificity of 95%.ConclusionsThis work demonstrates an automated method for accurate and reproducible segmentation of skeletal muscle area at L3. This is an efficient tool for large scale or routine computation of skeletal muscle area in cancer patients which may have applications on low quality CTs acquired as part of PET/CT studies for staging and surveillance of patients with cancer.

scholarly journals Muscle Function is Associated With Presence, New-onset, or Worsening of Hepatic Steatosis Assessed by Biochemical Parameters, Independent of Muscle Mass

2021 ◽  
Vol 5 (Supplement_1) ◽  
pp. A295-A296
Author(s):  
Namki Hong ◽  
Seunghyun Lee ◽  
Kyoungjin Kim ◽  
Jee-Seon Shim ◽  
Hyeon Chang Kim ◽  
...  
Keyword(s):  
Skeletal Muscle ◽  
Liver Disease ◽  
Hepatic Steatosis ◽  
Muscle Mass ◽  
Muscle Function ◽  
Biochemical Parameters ◽  
Community Dwelling ◽  
Jump Power ◽  
New Onset

Abstract Non-alcoholic fatty liver disease (NAFLD) becomes a major health problem leading to metabolic complications and end-stage liver disease, lacking effective therapeutic interventions. Skeletal muscle deficit, or sarcopenia, is related to accelerated accumulation of ectopic fat at liver. Skeletal muscle can be a novel intervention target of NAFLD. However, previous studies focused on the association between muscle mass and NAFLD, whereas the association of muscle function with NAFLD, a more clinically relevant assessment regarding skeletal muscle, remains unclear. Among participants enrolled between 2013 to 2014 in cardiovascular and Metabolic Diseases Etiology Research Center (CMERC) study (n=807), a cohort of community-dwelling Korean adults to study cardiovascular risk factors, a total of 500 individuals were recruited for 5-year follow-up. Hepatic steatosis was defined by hepatic steatosis index 36 or higher (HSI=8X(AST/ALT)+BMI+2 [if diabetes]+2 [if female]). New-onset of hepatic steatosis was defined as newly developed hepatic steatosis at current follow-up compared to baseline and worsening of HSI was defined as the highest quartile of HSI changes (2 or higher HSI increase). Muscle function was assessed by peak countermovement jump power relative weight (W/kg), 5 times chair rise test (CRT; in seconds), and grip strength (GS; in kg). Appendicular lean mass (ALM) was measured using bioimpedance analysis (InBody770, Biospace, Seoul, Korea). A total of 439 subjects (women 74%; mean age 57 ± 8 year) were analyzed after excluding those with excessive alcohol intake (n=51) and any missing values (n=10). Hepatic steatosis was present in 40% of subjects, which was increased from baseline period (33%, p<0.001). Low peak jump power (adjusted odds ratio [aOR] 1.14 per 1 W/kg decrease), GS (aOR 1.08 per 1kg decrease), and CRT performance (aOR 1.09 per 1 second increase; p<0.05 for all) were all associated with elevated odds of hepatic steatosis, after adjustment for age, gender, height, ALM, and metabolic syndrome components. Compared to those without hepatic steatosis at baseline and follow-up, those with persistent hepatic steatosis had significantly lower jump power in both men and women (33 vs. 40 W/kg in men, p=0.027; 26 vs. 29 W/kg in women, p<0.001). Jump power remained as robust predictor for new-onset hepatic steatosis or worsening of HSI (aOR 1.05 per 1W/kg decrease, p=0.044), whereas GS, CRT, and ALM were not. Muscle function measured by jump power was associated with presence or worsening of hepatic steatosis assessed by biochemical parameters, independent of muscle mass. Acknowledgement: We thank CMERC participants and all research staffs for this work. Funding: This study was supported by research grants from Hanmi Pharmaceutical Co.,Ltd. (4-2018-0845).

scholarly journals Diagnostic Power of Circulatory Metabolic Biomarkers as Metabolic Syndrome Risk Predictors in Community-Dwelling Older Adults in Northwest of England (A Feasibility Study)

Nutrients ◽  
2021 ◽  
Vol 13 (7) ◽  
pp. 2275
Author(s):  
Razieh Hassannejad ◽  
Hamsa Sharrouf ◽  
Fahimeh Haghighatdoost ◽  
Ben Kirk ◽  
Farzad Amirabdollahian
Keyword(s):  
Risk Factors ◽  
Older Adults ◽  
Metabolic Syndrome ◽  
Roc Analysis ◽  
Cross Validation ◽  
Community Dwelling ◽  
Tnf Α ◽  
Diagnostic Power ◽  
Metabolic Biomarkers ◽  
Community Dwelling Older Adults

Background: Metabolic Syndrome (MetS) is a cluster of risk factors for diabetes and cardiovascular diseases with pathophysiology strongly linked to aging. A range of circulatory metabolic biomarkers such as inflammatory adipokines have been associated with MetS; however, the diagnostic power of these markers as MetS risk correlates in elderly has yet to be elucidated. This cross-sectional study investigated the diagnostic power of circulatory metabolic biomarkers as MetS risk correlates in older adults. Methods: Hundred community dwelling older adults (mean age: 68.7 years) were recruited in a study, where their blood pressure, body composition and Pulse Wave Velocity (PWV) were measured; and their fasting capillary and venous blood were collected. The components of the MetS; and the serum concentrations of Interleukin-6 (IL-6), Tumor Necrosis Factor-α (TNF-α), Plasminogen Activator Inhibitor-I (PAI-I), Leptin, Adiponectin, Resistin, Cystatin-C, C-Reactive Protein (CRP), insulin and ferritin were measured within the laboratory, and the HOMA1-IR and Atherogenic Index of Plasma (AIP) were calculated. Results: Apart from other markers which were related with some cardiometabolic (CM) risk, after Bonferroni correction insulin had significant association with all components of Mets and AIP. These associations also remained significant in multivariate regression. The multivariate odds ratio (OR with 95% confidence interval (CI)) showed a statistically significant association between IL-6 (OR: 1.32 (1.06–1.64)), TNF-α (OR: 1.37 (1.02–1.84)), Resistin (OR: 1.27 (1.04–1.54)) and CRP (OR: 1.29 (1.09–1.54)) with MetS risk; however, these associations were not found when the model was adjusted for age, dietary intake and adiposity. In unadjusted models, insulin was consistently statistically associated with at least two CM risk factors (OR: 1.33 (1.16–1.53)) and MetS risk (OR: 1.24 (1.12–1.37)) and in adjusted models it was found to be associated with at least two CM risk factors and MetS risk (OR: 1.87 (1.24–2.83) and OR: 1.25 (1.09–1.43)) respectively. Area under curve (AUC) for receiver operating characteristics (ROC) demonstrated a good discriminatory diagnostics power of insulin with AUC: 0.775 (0.683–0.866) and 0.785 by cross validation and bootstrapping samples for at least two CM risk factors and AUC: 0.773 (0.653–0.893) and 0.783 by cross validation and bootstrapping samples for MetS risk. This was superior to all other AUC reported from the ROC analysis of other biomarkers. Area under precision-recall curve for insulin was also superior to all other markers (0.839 and 0.586 for at least two CM risk factors and MetS, respectively). Conclusion: Fasting serum insulin concentration was statistically linked with MetS and its risk, and this link is stronger than all other biomarkers. Our ROC analysis confirmed the discriminatory diagnostic power of insulin as CM and MetS risk correlate in older adults.

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