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3Purpose: Measurement of muscle mass is paramount in the screening and diagnosis of sarcopenia. Besides muscle quantity however, also quality assessment is important. Ultrasonography (US) has the advantage over dual-energy X-ray absorptiometry (DEXA) and bio-impedance analysis (BIA) to give both quantitative and qualitative information on muscle. However, before its use in clinical practice, several methodological aspects still need to be addressed. Both standardization in measurement techniques and the availability of reference values are currently lacking. This review aims to provide an evidence-based standardization of assessing appendicular muscle with the use of US. Methods: A systematic review was performed for ultrasonography to assess muscle in older people. Pubmed, SCOPUS and Web of Sciences were searched. All articles regarding the use of US in assessing appendicular muscle were used. Description of US-specific parameters and localization of the measurement were retrieved. Results: Through this process, five items of muscle assessment were identified in the evaluated articles: thickness, cross-sectional area, echogenicity, fascicle length and pennation angle. Different techniques for measurement and location of measurement used were noted, as also the different muscles in which this was evaluated. Then, a translation for a clinical setting in a standardized way was proposed. Conclusions: The results of this review provide thus an evidence base for an ultrasound protocol in the assessment of skeletal muscle. This standardization of measurements is the first step in creating conditions to further test the applicability of US for use on a large scale as a routine assessment and follow-up tool for appendicular muscle.
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Background: Manual muscle mass assessment based on Computed Tomography (CT) scans is recognized as a good marker for malnutrition, sarcopenia, and adverse outcomes. However, manual muscle mass analysis is cumbersome and time consuming. An accurate fully automated method is needed. In this study, we evaluate if manual psoas annotation can be substituted by a fully automatic deep learning-based method.
Methods: This study included a cohort of 583 patients with severe aortic valve stenosis planned to undergo Transcatheter Aortic Valve Replacement (TAVR). Psoas muscle area was annotated manually on the CT scan at the height of lumbar vertebra 3 (L3). The deep learning-based method mimics this approach by first determining the L3 level and subsequently segmenting the psoas at that level. The fully automatic approach was evaluated as well as segmentation and slice selection, using average bias 95% limits of agreement, Intraclass Correlation Coefficient (ICC) and within-subject Coefficient of Variation (CV). To evaluate performance of the slice selection visual inspection was performed. To evaluate segmentation Dice index was computed between the manual and automatic segmentations (0 = no overlap, 1 = perfect overlap).
Results: Included patients had a mean age of 81 ± 6 and 45% was female. The fully automatic method showed a bias and limits of agreement of -0.69 [-6.60 to 5.23] cm2, an ICC of 0.78 [95% CI: 0.74-0.82] and a within-subject CV of 11.2% [95% CI: 10.2-12.2]. For slice selection, 84% of the selections were on the same vertebra between methods, bias and limits of agreement was 3.4 [-24.5 to 31.4] mm. The Dice index for segmentation was 0.93 ± 0.04, bias and limits of agreement was -0.55 [1.71-2.80] cm2.
Conclusion: Fully automatic assessment of psoas muscle area demonstrates accurate performance at the L3 level in CT images. It is a reliable tool that offers great opportunities for analysis in large scale studies and in clinical applications.
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OBJECTIVES: Acute hospitalization may lead to a decrease in muscle measures, but limited studies are reporting on the changes after discharge. The aim of this study was to determine longitudinal changes in muscle mass, muscle strength, and physical performance in acutely hospitalized older adults from admission up to 3 months post-discharge.
DESIGN: A prospective observational cohort study was conducted.
SETTING AND PARTICIPANTS: This study included 401 participants aged ≥70 years who were acutely hospitalized in 6 hospitals. All variables were assessed at hospital admission, discharge, and 1 and 3 months post-discharge.
METHODS: Muscle mass in kilograms was assessed by multifrequency Bio-electrical Impedance Analysis (MF-BIA) (Bodystat; Quadscan 4000) and muscle strength by handgrip strength (JAMAR). Chair stand and gait speed test were assessed as part of the Short Physical Performance Battery (SPPB). Norm values were based on the consensus statement of the European Working Group on Sarcopenia in Older People.
RESULTS: A total of 343 acute hospitalized older adults were included in the analyses with a mean (SD) age of 79.3 (6.6) years, 49.3% were women. From admission up to 3 months post-discharge, muscle mass (-0.1 kg/m2; P = .03) decreased significantly and muscle strength (-0.5 kg; P = .08) decreased nonsignificantly. The chair stand (+0.7 points; P < .001) and gait speed test (+0.9 points; P < .001) improved significantly up to 3 months post-discharge. At 3 months post-discharge, 80%, 18%, and 43% of the older adults scored below the cutoff points for muscle mass, muscle strength, and physical performance, respectively.
CONCLUSIONS AND IMPLICATIONS: Physical performance improved during and after acute hospitalization, although muscle mass decreased, and muscle strength did not change. At 3 months post-discharge, muscle mass, muscle strength, and physical performance did not reach normative levels on a population level. Further research is needed to examine the role of exercise interventions for improving muscle measures and physical performance after hospitalization.
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Muscle health, encompassing muscle mass, composition, strength, physical performance and patient-reported outcomes, is a key determinant of clinical outcomes across the life course and a wide range of disease states. Despite growing recognition of its importance, muscle health remains insufficiently integrated into routine clinical nutrition practice, and nutritional recommendations often rely on population averages rather than individual muscle status, disease phase or metabolic context.This narrative review, developed by an international multidisciplinary expert group, synthesises current evidence on muscle health and clinical nutrition across major clinical domains, including ageing, cancer, metabolic disease, obesity, weight loss interventions and acute illness. We critically appraise methods for assessing muscle mass, function, and patient-reported outcomes, highlighting their strengths, limitations, and feasibility for clinical practice and research. In doing so, we highlight marked heterogeneity in metabolic and functional responses to nutrition and exercise interventions, underscoring the need for phenotyping, endotyping and precision nutrition to individualise protein and energy requirements.Beyond biological mechanisms, we address key implementation challenges limiting translation into practice, including inequities in access to dietetic and other rehabilitation services, variability in health system organisation and underuse of functional and patient-centred outcomes in trials and routine care. Finally, we propose a translational research agenda to harmonise outcome measures, improve trial design and support integration of muscle health assessment and personalised nutritional strategies into clinical care pathways.By positioning muscle health as a central and actionable outcome of clinical nutrition, this review supports a shift from uniform recommendations towards more personalised and effective nutrition care.
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Background & aims: Optimal nutritional support during the acute phase of critical illness remains controversial. We hypothesized that patients with low skeletal muscle area and -density may specifically benefit from early high protein intake. Aim of the present study was to determine the association between early protein intake (day 2–4) and mortality in critically ill intensive care unit (ICU) patients with normal skeletal muscle area, low skeletal muscle area, or combined low skeletal muscle area and -density. Methods: Retrospective database study in mechanically ventilated, adult critically ill patients with an abdominal CT-scan suitable for skeletal muscle assessment around ICU admission, admitted from January 2004 to January 2016 (n = 739). Patients received protocolized nutrition with protein target 1.2–1.5 g/kg/day. Skeletal muscle area and -density were assessed on abdominal CT-scans at the 3rd lumbar vertebra level using previously defined cut-offs. Results: Of 739 included patients (mean age 58 years, 483 male (65%), APACHE II score 23), 294 (40%) were admitted with normal skeletal muscle area and 445 (60%) with low skeletal muscle area. Two hundred (45% of the low skeletal muscle area group) had combined low skeletal muscle area and -density. In the normal skeletal muscle area group, no significant associations were found. In the low skeletal muscle area group, higher early protein intake was associated with lower 60-day mortality (adjusted hazard ratio (HR) per 0.1 g/kg/day 0.82, 95%CI 0.73–0.94) and lower 6-month mortality (HR 0.88, 95%CI 0.79–0.98). Similar associations were found in the combined low skeletal muscle area and -density subgroup (HR 0.76, 95%CI 0.64–0.90 for 60-day mortality and HR 0.80, 95%CI 0.68–0.93 for 6-month mortality). Conclusions: Early high protein intake is associated with lower mortality in critically ill patients with low skeletal muscle area and -density, but not in patients with normal skeletal muscle area on admission. These findings may be a further step to personalized nutrition, although randomized studies are needed to assess causality.
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PURPOSE: In 2018, the SARCUS working group published a first article on the standardization of the use of ultrasound to assess muscle. Recommendations were made for patient positioning, system settings and components to be measured. Also, shortcomings in knowledge were mentioned. An important issue that still required standardization was the definition of anatomical landmarks for many muscles.
METHODS: A systematic search was performed in Medline, SCOPUS and Web of Sciences looking for all articles describing the use of ultrasound in the assessment of muscle not described in the first recommendations, published from 01/01/2018 until 31/01/2020. All relevant terms used for older people, ultrasound and muscles were used.
RESULTS: For 39 muscles, different approaches for ultrasound assessment were found that likely impact the values measured. Standardized anatomical landmarks and measuring points were proposed for all muscles/muscle groups. Besides the five already known muscle parameters (muscle thickness, cross-section area, pennation angle, fascicle length and echo-intensity), four new parameters are discussed (muscle volume, stiffness, contraction potential and microcirculation). The former SARCUS article recommendations are updated with this new information that includes new muscle groups.
CONCLUSIONS: The emerging field of ultrasound assessment of muscle mass only highlights the need for a standardization of measurement technique. In this article, guidelines are updated and broadened to provide standardization instructions for a large number of muscles.
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Background & aims:
Low muscle mass and -quality on ICU admission, as assessed by muscle area and -density on CT-scanning at lumbar level 3 (L3), are associated with increased mortality. However, CT-scan analysis is not feasible for standard care. Bioelectrical impedance analysis (BIA) assesses body composition by incorporating the raw measurements resistance, reactance, and phase angle in equations. Our purpose was to compare BIA- and CT-derived muscle mass, to determine whether BIA identified the patients with low skeletal muscle area on CT-scan, and to determine the relation between raw BIA and raw CT measurements.
Methods:
This prospective observational study included adult intensive care patients with an abdominal CT-scan. CT-scans were analysed at L3 level for skeletal muscle area (cm2) and skeletal muscle density (Hounsfield Units). Muscle area was converted to muscle mass (kg) using the Shen equation (MMCT). BIA was performed within 72 h of the CT-scan. BIA-derived muscle mass was calculated by three equations: Talluri (MMTalluri), Janssen (MMJanssen), and Kyle (MMKyle). To compare BIA- and CT-derived muscle mass correlations, bias, and limits of agreement were calculated. To test whether BIA identifies low skeletal muscle area on CT-scan, ROC-curves were constructed. Furthermore, raw BIA and CT measurements, were correlated and raw CT-measurements were compared between groups with normal and low phase angle.
Results:
110 patients were included. Mean age 59 ± 17 years, mean APACHE II score 17 (11–25); 68% male. MMTalluri and MMJanssen were significantly higher (36.0 ± 9.9 kg and 31.5 ± 7.8 kg, respectively) and MMKyle significantly lower (25.2 ± 5.6 kg) than MMCT (29.2 ± 6.7 kg). For all BIA-derived muscle mass equations, a proportional bias was apparent with increasing disagreement at higher muscle mass. MMTalluri correlated strongest with CT-derived muscle mass (r = 0.834, p < 0.001) and had good discriminative capacity to identify patients with low skeletal muscle area on CT-scan (AUC: 0.919 for males; 0.912 for females). Of the raw measurements, phase angle and skeletal muscle density correlated best (r = 0.701, p < 0.001). CT-derived skeletal muscle area and -density were significantly lower in patients with low compared to normal phase angle.
Conclusions:
Although correlated, absolute values of BIA- and CT-derived muscle mass disagree, especially in the high muscle mass range. However, BIA and CT identified the same critically ill population with low skeletal muscle area on CT-scan. Furthermore, low phase angle corresponded to low skeletal muscle area and -density.
Trial registration:
ClinicalTrials.gov (NCT02555670).
DOCUMENT
Generalized loss of muscle mass is associated with increased morbidity and mortality in patients with cancer. The gold standard to measure muscle mass is by using computed tomography (CT). However, the aim of this prospective observational cohort study was to determine whether point-of-care ultrasound (POCUS) could be an easy-to-use, bedside measurement alternative to evaluate muscle status. Patients scheduled for major abdominal cancer surgery with a recent preoperative CT scan available were included. POCUS was used to measure the muscle thickness of mm. biceps brachii, mm. recti femoris, and mm. vasti intermedius 1 day prior to surgery. The total skeletal muscle index (SMI) was derived from patients’ abdominal CT scan at the third lumbar level. Muscle force of the upper and lower extremities was measured using a handheld dynamometer. A total of 165 patients were included (55% male; 65 ± 12 years). All POCUS measurements of muscle thickness had a statistically significant correlation with CT-derived SMI (r ≥ 0.48; p < 0.001). The strongest correlation between POCUS muscle measurements and SMI was observed when all POCUS muscle groups were added together (r = 0.73; p < 0.001). Muscle strength had a stronger correlation with POCUS-measured muscle thickness than with CT-derived SMI. To conclude, this study indicated a strong correlation between combined muscle thickness measurements performed by POCUS- and CT-derived SMI and measurements of muscle strength. These results suggest that handheld ultrasound is a valid tool for the assessment of skeletal muscle status.
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Rationale: Currently use of muscle thickness measured with ultrasound is suggested as an indicator for overall muscle mass in nutritional assessment. However, not much is known about how the muscle thickness measured in patients with chronic obstructive pulmonary disease (COPD) compares to the muscle thickness in healthy persons. This study explores body mass index (BMI) and rectus femoris (RF) muscle thickness in patients with advanced COPD matched with healthy controls. Methods: Patients with advanced COPD at the start of a pulmonary rehabilitation program were matched for age (5 years difference tolerance), sex (exact match), and stature (0.1 m difference tolerance) with healthy controls in a 1:4 case control ratio. BMI (kg/m2) was calculated and muscle thickness (mm) of the RF was measured with a Bodymetrix device. Paired sample t-tests were performed. BMI and RF muscle thickness of the cases were paired with the average BMI and RF of their controls. A p-level of <0.05 was considered significant and 95% CI were presented for the mean difference. Results: In total, 21 cases (median GOLD score 3 [interquartile range 3-4]; age 64.5±6.4y; female 62%; height 1.68±0.07m; BMI 26.9±6.1 kg/m2; RF 12.4±3.4mm) and 84 controls (age 64.5±6.4y; female 62%; height 1.71±0.09 m; BMI 25.8±4.5; RF 14.6±4.5mm) were included in the analyses. In the paired test, BMI was not significantly different between cases and controls (p=0.645, mean difference 0.95 kg/m2 [CI:-2.12 – 4.01]), whereas RF muscle thickness of cases was significantly lower (p=0.003, mean difference -2.33 mm [CI:-3.73 - -0.92]). Conclusion: In this limited sample of patients with COPD, RF muscle thickness in cases was significantly lower than RF muscle thickness in matched controls. Research in bigger samples is needed to confirm whether RF muscle thickness measured with US provides more useful information about body composition for clinicians than BMI in patients with COPD.
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Background and Purpose: Decreased muscle mass and muscle strength are independent predictors of poor postoperative recov- ery in patients with esophageal cancer. If there is an association between muscle mass and muscle strength, physiotherapists are able to measure muscle strength as an early predictor for poor postoperative recovery due to decreased muscle mass. Therefore, in this cross-sectional study, we aimed to investigate the association between muscle mass and muscle strength in predominantly older patients with esophageal cancer awaiting esophagectomy prior to neoadjuvant chemoradiation. Methods: In patients with resectable esophageal cancer eligible for surgery between March 2012 and October 2015, we used computed tomographic scans to assess muscle mass and compared them with muscle strength measures (hand- grip strength, inspiratory and expiratory muscle strength, 30 seconds chair stands test). We calculated Pearson correla- tion coefficients and determined associations by multivariate linear regression analysis. Results and Discussion: A tertiary referral center referred 125 individuals to physiotherapy who were eligible for the study; we finally included 93 individuals for statistical analysis. Mul- tiple backward regression analysis showed that gender (95% confidence interval [CI], 2.05-33.82), weight (95% CI, 0.39- 1.02), age (95% CI, −0.91 to −0.04), left handgrip strength (95% CI, 0.14-1.44), and inspiratory muscle strength (95% CI, 0.08-0.38) were all independently associated with muscle surface area at L3. All these variables together explained 66% of the variability (R2) in muscle surface area at L3 (P < .01). Conclusions: This study shows an independent association between aspects of muscle strength and muscle mass in patients with esophageal cancer awaiting surgery, and phys- iotherapists could use the results to predict muscle mass on the basis of muscle strength in preoperative patients with esophageal cancer.
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