Diagnosing sarcopenia and myosteatosis based on chest computed tomography images in healthy Chinese adults

Abstract Background Measuring muscle mass and muscle quality based on chest Computed Tomography (CT) images would facilitate sarcopenia and myosteatosis research. We aimed (1) to measure muscle mass and myosteatosis based on chest CT images at the 12th thoracic vertebra level and compare the relevant indicators with whole-body skeletal muscle mass (BSM) and whole-body fat mass (BFM) measured by bioelectrical impedance analysis; and (2) to determine the cut-off points of these indicators for diagnosing sarcopenia or myosteatosis in healthy Chinese adults. Methods Chest CT images were analyzed using a segmentation software. Skeletal muscle area (SMA), skeletal muscle radiodensity (SMD), and intermuscular adiposity tissue (IMAT) were measured. Skeletal muscle indices (SMIs) and IMAT/SMA ratio were calculated. Results We included 569 participants. SMA, SMA/height2, and SMA/BMI were strongly and positively correlated with BSM (r = 0.90, 0.72, and 0.69, respectively, all p < 0.001); whereas SMA/weight was moderately and positively correlated with BSM (r = 0.38, p < 0.001). IMAT and IMAT/SMA were strongly and positively correlated with BFM (r = 0.67 and 0.58, respectively, both p < 0.001). SMD was moderately and negatively correlated with BFM (r = − 0.40, p < 0.001). We suggest SMA/height2 (< 25.75 cm2/m2 in men and < 20.16 cm2/m2 in women) for diagnosing sarcopenia and SMD (< 37.42 HU in men and < 33.17 HU in women) or IMAT (> 8.72 cm2 in men and > 4.58 cm2 in women) for diagnosing myosteatosis. Conclusions Muscle mass indicators (SMA and SMIs) and muscle quality indicators (SMD, IMAT, and IMAT/SMA) measured by chest CT images are valuable for diagnosing sarcopenia and myosteatosis, respectively.

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Associations of ADL Disability With Trunk Muscle Mass and Muscle Quality Indicators Measured by Opportunistic Chest Computed Tomography Imaging Among Older Inpatients

Frontiers in Medicine ◽

10.3389/fmed.2021.743698 ◽

2021 ◽

Vol 8 ◽

Author(s):

Xiaofan Jing ◽

Lingling Tan ◽

Hongbo Fu ◽

Ling Yang ◽

Ming Yang

Keyword(s):

Skeletal Muscle ◽

Muscle Mass ◽

Quality Indicators ◽

Ct Images ◽

Trunk Muscle ◽

Chest Ct ◽

Muscle Quality ◽

Skeletal Muscle Index ◽

Older Inpatients ◽

Adl Disability

Objectives: Sarcopenia is an important predictor of dependence in activities of daily living (ADL disability); however, the association between muscle quality and ADL disability has not been established. We aimed (1) to assess the feasibility of measuring trunk muscle mass and muscle quality by chest CT images; and (2) to explore the possible associations of ADL disability with these muscle mass and muscle quality indicators among older inpatients.Methods: We included older patients in an acute care ward. ADL disability was defined as the Barthel Index (BI) score ≤ 60 points. Unenhanced chest CT images at the 12th thorax (T12) vertebral level were used to segment skeletal muscle area (SMA) and intermuscular adipose tissue (IMAT) and to measure the mean skeletal muscle radiodensity (SMD). Skeletal muscle index (SMI), the muscle mass indicator, was calculated by SMA (cm2)/body height squared (m2). The percentage of IMAT (IMAT%) was calculated using the equation: IMAT% = IMAT/(SMA+ IMAT) ×100%. Skeletal muscle radiodensity, IMAT, and IMAT% were the muscle quality indicators. Kendall's tau rank correlation coefficients (τ) were calculated to explore the correlations. Univariate and multivariate logistic regression models were performed to calculate odds ratios (OR) and 95% confidence interval (CI).Results: We included 212 participants. Skeletal muscle index and SMD were positively and significantly associated with the BI score (τ = 0.14 and 0.31, respectively, both P < 0.001); whereas IMAT and IMAT% were negatively and significantly associated with the BI score (τ = −0.21, P < 0.001; τ = −0.21, P < 0.012). After adjusting for confounders, SMI (adjusted OR 1.03, 95% CI 0.97–1.09) was not independently associated with ADL disability; however, SMD (adjusted OR 0.94, 95% CI 0.88–0.99), IMAT (adjusted OR 1.11, 95% CI 1.03–1.20), and IMAT% (adjusted OR 1.09, 95% CI 1.02–1.16) were independently associated with ADL disability. Subgroup analysis found similar results in men; however, none of these indicators were independently associated with ADL disability in women.Conclusion: Trunk muscle quality indicators (SMD, IMAT, and IMAT%) measured by chest CT images, but not SMI, are independently associated with ADL disability in a single-center study population of older inpatients, especially in men. Further research is necessary to validate our findings.

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Reference Values for Skeletal Muscle Mass – Current Concepts and Methodological Considerations

Nutrients ◽

10.3390/nu12030755 ◽

2020 ◽

Vol 12 (3) ◽

pp. 755 ◽

Cited By ~ 6

Author(s):

Carina O. Walowski ◽

Wiebke Braun ◽

Michael J. Maisch ◽

Björn Jensen ◽

Sven Peine ◽

...

Keyword(s):

Skeletal Muscle ◽

Muscle Mass ◽

Reference Values ◽

Skeletal Muscle Mass ◽

Bioelectrical Impedance ◽

Reference Population ◽

Muscle Quality ◽

Whole Body ◽

Whole Body Imaging ◽

Cross Sectional

Assessment of a low skeletal muscle mass (SM) is important for diagnosis of ageing and disease-associated sarcopenia and is hindered by heterogeneous methods and terminologies that lead to differences in diagnostic criteria among studies and even among consensus definitions. The aim of this review was to analyze and summarize previously published cut-offs for SM applied in clinical and research settings and to facilitate comparison of results between studies. Multiple published reference values for discrepant parameters of SM were identified from 64 studies and the underlying methodological assumptions and limitations are compared including different concepts for normalization of SM for body size and fat mass (FM). Single computed tomography or magnetic resonance imaging images and appendicular lean soft tissue by dual X-ray absorptiometry (DXA) or bioelectrical impedance analysis (BIA) are taken as a valid substitute of total SM because they show a high correlation with results from whole body imaging in cross-sectional and longitudinal analyses. However, the random error of these methods limits the applicability of these substitutes in the assessment of individual cases and together with the systematic error limits the accurate detection of changes in SM. Adverse effects of obesity on muscle quality and function may lead to an underestimation of sarcopenia in obesity and may justify normalization of SM for FM. In conclusion, results for SM can only be compared with reference values using the same method, BIA- or DXA-device and an appropriate reference population. Limitations of proxies for total SM as well as normalization of SM for FM are important content-related issues that need to be considered in longitudinal studies, populations with obesity or older subjects.

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Chest CT Images for COVID-19: Radiologists and Computer-based detection

10.1101/2020.06.27.20141531 ◽

2020 ◽

Author(s):

Qingli Dou ◽

Jiangping Liu ◽

Wenwu Zhang ◽

Yanan Gu ◽

Wan-Ting Hsu ◽

...

Keyword(s):

Computed Tomography ◽

Image Analysis ◽

Ct Images ◽

Chest Ct ◽

Image Analysis System ◽

Ct Image ◽

Chest Computed Tomography ◽

Computer Based ◽

Analysis System ◽

Novel Coronavirus

ABSTRACTBackgroundCharacteristic chest computed tomography (CT) manifestation of 2019 novel coronavirus (COVID-19) was added as a diagnostic criterion in the Chinese National COVID-19 management guideline. Whether the characteristic findings of Chest CT could differentiate confirmed COVID-19 cases from other positive nucleic acid test (NAT)-negative patients has not been rigorously evaluated.PurposeWe aim to test whether chest computed tomography (CT) manifestation of 2019 novel coronavirus (COVID-19) can be differentiated by a radiologist or a computer-based CT image analysis system.MethodsWe conducted a retrospective case-control study that included 52 laboratory-confirmed COVID-19 patients and 80 non-COVID-19 viral pneumonia patients between 20 December, 2019 and 10 February, 2020. The chest CT images were evaluated by radiologists in a double blind fashion. A computer-based image analysis system (uAI system, Lianying Inc., Shanghai, China) detected the lesions in 18 lung segments defined by Boyden classification system and calculated the infected volume in each segment. The number and volume of lesions detected by radiologist and computer system was compared with Chi-square test or Mann-Whitney U test as appropriate.ResultsThe main CT manifestations of COVID-19 were multi-lobar/segmental peripheral ground-glass opacities and patchy air space infiltrates. The case and control groups were similar in demographics, comorbidity, and clinical manifestations. There was no significant difference in eight radiologist identified CT image features between the two groups of patients. There was also no difference in the absolute and relative volume of infected regions in each lung segment.ConclusionsWe documented the non-differentiating nature of initial chest CT image between COVID-19 and other viral pneumonia with suspected symptoms. Our results do not support CT findings replacing microbiological diagnosis as a critical criterion for COVID-19 diagnosis. Our findings may prompt re-evaluation of isolated patients without laboratory confirmation.

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Use of prediction equations to determine the accuracy of whole-body fat and fat-free mass and appendicular skeletal muscle mass measurements from a single abdominal image using computed tomography in advanced cancer patients

Applied Physiology Nutrition and Metabolism ◽

10.1139/apnm-2015-0068 ◽

2016 ◽

Vol 41 (1) ◽

pp. 70-75 ◽

Cited By ~ 7

Author(s):

Robert D. Kilgour ◽

Katrina Cardiff ◽

Leonard Rosenthall ◽

Enriqueta Lucar ◽

Barbara Trutschnigg ◽

...

Keyword(s):

Computed Tomography ◽

Skeletal Muscle ◽

Body Fat ◽

Ct Images ◽

Fat Free Mass ◽

Whole Body ◽

Prediction Equations ◽

Advanced Cancer Patients ◽

Abdominal Ct ◽

Appendicular Skeletal Muscle

Measurements of body composition using dual-energy X-ray absorptiometry (DXA) and single abdominal images from computed tomography (CT) in advanced cancer patients (ACP) have important diagnostic and prognostic value. The question arises as to whether CT scans can serve as surrogates for DXA in terms of whole-body fat-free mass (FFM), whole-body fat mass (FM), and appendicular skeletal muscle (ASM) mass. Predictive equations to estimate body composition for ACP from CT images have been proposed (Mourtzakis et al. 2008; Appl. Physiol. Nutr. Metabol. 33(5): 997–1006); however, these equations have yet to be validated in an independent cohort of ACP. Thus, this study evaluated the accuracy of these equations in estimating FFM, FM, and ASM mass using CT images at the level of the third lumbar vertebrae and compared these values with DXA measurements. FFM, FM, and ASM mass were estimated from the prediction equations proposed by Mourtzakis and colleagues (2008) using single abdominal CT images from 43 ACP and were compared with whole-body DXA scans using Spearman correlations and Bland–Altman analyses. Despite a moderate to high correlation between the actual (DXA) and predicted (CT) values for FM (rho = 0.93; p ≤ 0.001), FFM (rho = 0.78; p ≤ 0.001), and ASM mass (rho = 0.70; p ≤ 0.001), Bland–Altman analyses revealed large range-of-agreement differences between the 2 methods (29.39 kg for FFM, 15.47 kg for FM, and 3.99 kg for ASM mass). Based on the magnitude of these differences, we concluded that prediction equations using single abdominal CT images have poor accuracy, cannot be considered as surrogates for DXA, and may have limited clinical utility.

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The use of alternate vertebral levels to L3 in computed tomography scans for skeletal muscle mass evaluation and sarcopenia assessment in patients with cancer: a systematic review

British Journal Of Nutrition ◽

10.1017/s0007114521001446 ◽

2021 ◽

pp. 1-49

Author(s):

Belinda Vangelov ◽

Judy Bauer ◽

Damian Kotevski ◽

Robert I. Smee

Keyword(s):

Computed Tomography ◽

Skeletal Muscle ◽

Ct Scan ◽

Cancer Patients ◽

Muscle Mass ◽

Skeletal Muscle Mass ◽

Whole Body ◽

Ct Scans ◽

Cross Sectional ◽

Patients With Cancer

ABSTRACT Body composition measurement using diagnostic computed tomography (CT) scans has emerged as a method to assess sarcopenia (low muscle mass) in oncology patients. Assessment of skeletal muscle mass (SMM) using the cross-sectional area (CSA) of a single vertebral slice (at lumbar L3) in a CT scan is correlated to whole body skeletal muscle volume. This method is used to assess CT-defined sarcopenia in patients with cancer, with low SMM effecting outcomes. However, as diagnostic scans are based on tumour location, not all include L3. We evaluated the evidence for the use of alternate vertebral CT slices for SMM evaluation when L3 is not available. Five electronic databases were searched from Jan 1996-April 2020 for studies using CT scan vertebral slices above L3 for SM measurement in adults with cancer (solid tumours). Validation with whole body SMM, rationale for the chosen slice, and sarcopenia cut-off values were investigated. Thirty-two studies were included, all retrospective and cross-sectional in design. Cervical, thoracic, and lumbar slices were used (from C3-L1), with no validation of whole body SMM using CT scans. Alternate slices were used in lung, and head and neck cancer patients. Sarcopenia cut-off values were reported in 75% of studies, with differing methods, with or without sex-specific values, and a lack of consensus. Current evidence is inadequate to provide definitive recommendations for alternate vertebral slice use for SMM evaluation in cancer patients. Variation in sarcopenia cut-offs warrants more robust investigation, in order for risk stratification to be applied to all patients with cancer.

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More than six weeks to resolve from CT manifestations in COVID-19 patient: A case report

10.21203/rs.3.rs-20188/v1 ◽

2020 ◽

Author(s):

Wenxiong Xu ◽

Ziying Lei ◽

Dabiao Chen ◽

Xuejun Li ◽

Zhanlian Huang ◽

...

Keyword(s):

Computed Tomography ◽

Health Care Providers ◽

Ct Images ◽

Ct Imaging ◽

Chest Ct ◽

Care Providers ◽

Case Presentation ◽

Chest Computed Tomography ◽

Guangzhou City

Abstract Background: Coronavirus Disease 2019 (COVID-19) outbroke in Wuhan and spread to the world recently. But there were little studies on how long it took to recover from treatment beginning and resolve from chest computed tomography (CT) imaging so far.Case presentation: A patient diagnosed with severe type of COVID-19 was reported in this study. He was the first patient recovered and discharged from our hospital located in Guangzhou city. Initial chest computed tomography (CT) images of him showed bilateral multiple lobular peripheral ground-glass opacities without consolidation. Features and changes of his chest CT images from admission to discharge and follow-up were demonstrated. It took more than six weeks for lesion resolution in CT manifestations although the symptoms improved for a period of time after proper treatment. Conclusions: Repeated chest CT imaging for a period of more than six weeks in patients of COVID-19 is necessary to ascertain the lesion resolution and completely recovery. The result could be supplementary data to COVID-19 and help health care providers manage the COVID-19 patients.

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Association between hand muscle thickness and whole-body skeletal muscle mass in healthy adults: a pilot study

Journal of Physical Therapy Science ◽

10.1589/jpts.29.1644 ◽

2017 ◽

Vol 29 (9) ◽

pp. 1644-1648 ◽

Cited By ~ 6

Author(s):

Akio Morimoto ◽

Tadashi Suga ◽

Nobuaki Tottori ◽

Michio Wachi ◽

Jun Misaki ◽

...

Keyword(s):

Skeletal Muscle ◽

Pilot Study ◽

Muscle Mass ◽

Skeletal Muscle Mass ◽

Muscle Thickness ◽

Healthy Adults ◽

Whole Body ◽

Hand Muscle

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Correlation between age, sex, and severity of Coronavirus disease-19 based on chest computed tomography severity scoring system

Egyptian Journal of Radiology and Nuclear Medicine ◽

10.1186/s43055-021-00408-1 ◽

2021 ◽

Vol 52 (1) ◽

Author(s):

Shimaa Farghaly ◽

Marwa Makboul

Keyword(s):

Computed Tomography ◽

Scoring System ◽

Fatal Outcome ◽

Age Groups ◽

Significant Risk ◽

Chest Ct ◽

Age Group ◽

Severity Scoring ◽

Chest Computed Tomography ◽

Severity Of The Disease

Abstract Background Coronavirus disease 2019 (COVID-19) is the most recent global health emergency; early diagnosis of COVID-19 is very important for rapid clinical interventions and patient isolation; chest computed tomography (CT) plays an important role in screening, diagnosis, and evaluating the progress of the disease. According to the results of different studies, due to high severity of the disease, clinicians should be aware of the different potential risk factors associated with the fatal outcome, so chest CT severity scoring system was designed for semi-quantitative assessment of the severity of lung disease in COVID-19 patients, ranking the pulmonary involvement on 25 points severity scale according to extent of lung abnormalities; this study aims to evaluate retrospectively the relationship between age and severity of COVID-19 in both sexes based on chest CT severity scoring system. Results Age group C (40–49 year) was the commonest age group that was affected by COVID-19 by 21.3%, while the least affected group was group F (≥ 70 years) by only 6.4%. As regards COVID-RADS classification, COVID-RADS-3 was the most commonly presented at both sexes in all different age groups. Total CT severity lung score had a positive strong significant correlation with the age of the patient (r = 0.64, P < 0.001). Also, a positive strong significant correlation was observed between CT severity lung score and age in both males and females (r = 0.59, P < 0.001) and (r = 0.69, P < 0.001) respectively. Conclusion We concluded that age can be considered as a significant risk factor for the severity of COVID-19 in both sexes. Also, CT can be used as a significant diagnostic tool for the diagnosis of COVID-19 and evaluation of the progression and severity of the disease.

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Leg and arm lactate and substrate kinetics during exercise

AJP Endocrinology and Metabolism ◽

10.1152/ajpendo.00273.2002 ◽

2003 ◽

Vol 284 (1) ◽

pp. E193-E205 ◽

Cited By ~ 107

Author(s):

G. van Hall ◽

M. Jensen-Urstad ◽

H. Rosdahl ◽

H.-C. Holmberg ◽

B. Saltin ◽

...

Keyword(s):

Skeletal Muscle ◽

Glucose Uptake ◽

Muscle Mass ◽

Lactate Concentration ◽

Whole Body ◽

Glucose Turnover ◽

Lactate Oxidation ◽

Arterial Lactate ◽

Lactate Uptake ◽

High Lactate

To study the role of muscle mass and muscle activity on lactate and energy kinetics during exercise, whole body and limb lactate, glucose, and fatty acid fluxes were determined in six elite cross-country skiers during roller-skiing for 40 min with the diagonal stride (Continuous Arm + Leg) followed by 10 min of double poling and diagonal stride at 72–76% maximal O2 uptake. A high lactate appearance rate (Ra, 184 ± 17 μmol · kg−1 · min−1) but a low arterial lactate concentration (∼2.5 mmol/l) were observed during Continuous Arm + Leg despite a substantial net lactate release by the arm of ∼2.1 mmol/min, which was balanced by a similar net lactate uptake by the leg. Whole body and limb lactate oxidation during Continuous Arm + Leg was ∼45% at rest and ∼95% of disappearance rate and limb lactate uptake, respectively. Limb lactate kinetics changed multiple times when exercise mode was changed. Whole body glucose and glycerol turnover was unchanged during the different skiing modes; however, limb net glucose uptake changed severalfold. In conclusion, the arterial lactate concentration can be maintained at a relatively low level despite high lactate Ra during exercise with a large muscle mass because of the large capacity of active skeletal muscle to take up lactate, which is tightly correlated with lactate delivery. The limb lactate uptake during exercise is oxidized at rates far above resting oxygen consumption, implying that lactate uptake and subsequent oxidation are also dependent on an elevated metabolic rate. The relative contribution of whole body and limb lactate oxidation is between 20 and 30% of total carbohydrate oxidation at rest and during exercise under the various conditions. Skeletal muscle can change its limb net glucose uptake severalfold within minutes, causing a redistribution of the available glucose because whole body glucose turnover was unchanged.

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