Percentile-based averaging and skeletal muscle gauge improve body composition analysis: validation at multiple vertebral levels.
Skeletal muscle metrics on computed tomography (CT) correlate with clinical and patient-reported outcomes. We hypothesize that aggregating skeletal muscle measurements from multiple vertebral levels and skeletal muscle gauge (SMG) better predict outcomes than skeletal muscle radioattenuation (SMRA) or -index (SMI) at a single vertebral level.
We performed a secondary analysis of prospectively collected clinical (overall survival, hospital readmission, time to unplanned hospital readmission or death, and readmission or death within 90 days) and patient-reported outcomes (physical and psychological symptom burden captured as Edmonton Symptom Assessment Scale and Patient Health Questionnaire) of patients with advanced cancer who experienced an unplanned admission to Massachusetts General Hospital from 2014 to 2016. First, we assessed the correlation of skeletal muscle cross-sectional area, SMRA, SMI, and SMG at one or more of the following thoracic (T) or lumbar (L) vertebral levels: T5, T8, T10, and L3 on CT scans obtained ≤50 days before index assessment. Second, we aggregated measurements across all available vertebral levels using percentile-based averaging (PBA) to create the average percentile. Third, we constructed one regression model adjusted for age, sex, sociodemographic factors, cancer type, body mass index, and intravenous contrast for each combination of (i) vertebral level and average percentile, (ii) muscle metrics (SMRA, SMI, & SMG), and (iii) clinical and patient-reported outcomes. Fourth, we compared the performance of vertebral levels and muscle metrics by ranking otherwise identical models by concordance statistic, number of included patients, coefficient of determination, and significance of muscle metric.
We included 846 patients (mean age: 63.5 ± 12.9 years, 50.5% males) with advanced cancer [predominantly gastrointestinal (32.9%) or lung (18.9%)]. The correlation of muscle measurements between vertebral levels ranged from 0.71 to 0.84 for SMRA and 0.67 to 0.81 for SMI. The correlation of individual levels with the average percentile was 0.90-0.93 for SMRA and 0.86-0.92 for SMI. The intrapatient correlation of SMRA with SMI was 0.21-0.40. PBA allowed for inclusion of 8-47% more patients than any single-level analysis. PBA outperformed single-level analyses across all comparisons with average ranks 2.6, 2.9, and 1.6 for concordance statistic, coefficient of determination, and significance (range 1-5, μ = 3), respectively. On average, SMG outperformed SMRA and SMI across outcomes and vertebral levels: the average rank of SMG was 1.4, 1.4, and 1.4 for concordance statistic, coefficient of determination, and significance (range 1-3, μ = 2), respectively.
Multivertebral level skeletal muscle analyses using PBA and SMG independently and additively outperform analyses using individual levels and SMRA or SMI.
Marquardt JP
，Roeland EJ
，Van Seventer EE
，Best TD
，Horick NK
，Nipp RD
，Fintelmann FJ
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Assessment of muscle mass using chest computed tomography-based quantitative and qualitative measurements in patients with systemic sclerosis: A retrospective study with cross-sectional and longitudinal analyses.
Sarcopenia has been increasingly studied in systemic sclerosis (SSc), which is one of the most lethal autoimmune diseases, mainly due to lung involvement. Our objective was to study the associations of myopenia and/or myosteatosis with clinical features of SSc and subsequent adverse outcomes.
This is a retrospective study with cross-sectional and longitudinal analyses, in which patients with SSc were consecutively included in the outpatient clinic of a tertiary university hospital between 2012 and 2021. Clinical and laboratory parameters of patients with SSc were collected from their medical records. Skeletal muscle mass was assessed on chest computed tomography (CT) at the level of the first lumbar vertebra (L1) by skeletal muscle area (SMA), skeletal muscle index ([SMI] SMA/height2), and skeletal muscle radiation attenuation (SMRA). Cut-off values for myopenia in women and men were SMA <70.1 cm² and <110.4 cm², and SMI <25.9 cm²/m² and <34.6 cm²/m², respectively; values for myosteatosis in women and men were SMRA <29.8 HU and <36.3 HU, respectively. In a subgroup of 31 patients followed-up between 2017 and 2019, the diagnostic properties of SMA, SMI, and SMRA by CT were compared with the appendicular skeletal muscle mass index (ASMI) by dual-energy X-ray absorptiometry (DXA). Low muscle quantity was defined according to the European Working Group on Sarcopenia in Older People 2: ASMI <5.5 kg/m2 in women and <7.0 kg/m2 in men. Afterwards, a better tomographic index was used for correlating with clinical and laboratory parameters.
Myopenia and/or myosteatosis were present in 75.7 % of patients with SSc. The prevalence rates according to each index were SMA 25.2%, SMI 12.1%, and SMRA 69.2%. In 73% of the patients with overweight/obesity (body mass index [BMI] ≥25 kg/m²), only SMRA was reduced. Considering ASMI as the gold standard, the sensitivity, specificity, positive and negative predictive values for SMA were 60%, 96.2%, 75% and 92.6%, respectively; for SMI, they were 40%, 96.2%, 66.7%, and 89.3%, respectively; for SMRA, these values were 60%, 34.6%, 15%, and 81.8%. Pearson's correlation coefficients were 0.73, 0.74, and 0.10 for SMA, SMI, and SMRA, respectively, and ASMI significantly agreed with SMA (kappa 0.611, p < 0.001) and SMI (kappa 0.431, p = 0.012). After adjustments in a multivariate model, BMI (p < 0.001) and female sex (p < 0.001) remained significantly associated with myopenia by SMA; BMI (p =0.010) remained significantly associated with low muscle mass by ASMI.
The SMA index at L1 level on chest CT was demonstrated to be an accurate measure that is useful for detecting myopenia in patients with SSc. BMI and male sex predicted low SMA and BMI was associated with low ASMI on DXA.
In recent years, great advances have been made in sarcopenia-related research, resulting in broader knowledge on its definition, causes, diagnosis, and treatment options. Regarding the techniques used for assessing muscle composition, computed tomography (CT) was demonstrated by many studies to be an efficient and easy-to-use method that can be employed by professionals of different specialties, including rheumatologists. This study was able to demonstrate that although the L3 image was not present on CT, the analysis of SMA at the L1 level on chest CT proved to be an accurate and useful measure to detect myopenia in patients with SSc. This study identified some associated factors of myopenia and/or myosteatosis according to each method employed for assessing muscle composition. Reduced BMI and male sex were associated factors of myopenia when using SMA, and reduced BMI was associated with myopenia when employing ASMI by DXA. Finally, we highlight the need not to generalize the term "sarcopenia" in clinical studies assessing imaging parameters of body composition. The use of the terms myopenia and/or myosteatosis would be more adequate, because CT allows the assessment of muscle composition and not strength or physical performance.
da Rocha DS
，Tessari JA
，Mainardi NB
，Hax V
，Gasparin AA
，de Oliveira CAV
，Garcia TS
，Xavier RM
，Chakr RMDS
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Muscle Reference Values From Thoracic and Abdominal CT for Sarcopenia Assessment: The Framingham Heart Study.
Loss of muscle mass is a known feature of sarcopenia and predicts poor clinical outcomes. Although muscle metrics can be derived from routine computed tomography (CT) images, sex-specific reference values at multiple vertebral levels over a wide age range are lacking.
The aim of this study was to provide reference values for skeletal muscle mass and attenuation on thoracic and abdominal CT scans in the community-based Framingham Heart Study cohort to aid in the identification of sarcopenia.
This secondary analysis of a prospective trial describes muscle metrics by age and sex for participants from the Framingham Heart Study without prior history of cancer who underwent at least 1 CT scan between 2002 and 2011. Using 2 previously validated machine learning algorithms followed by human quality assurance, skeletal muscle was analyzed on a single axial CT image per level at the 5th, 8th, 10th thoracic, and 3rd lumbar vertebral body (T5, T8, T10, L3). Cross-sectional muscle area (cm 2 ), mean skeletal muscle radioattenuation (SMRA, in Hounsfield units), skeletal muscle index (SMI, in cm 2 /m 2 ), and skeletal muscle gauge (SMRA·SMI) were calculated. Measurements were summarized by age group (<45, 45-54, 55-64, 65-74, ≥75 years), sex, and vertebral level. Models enabling the calculation of age-, sex-, and vertebral-level-specific reference values were created and embedded into an open access online Web application.
The cohort consisted of 3804 participants (1917 [50.4%] males; mean age, 55.6 ± 11.8 years; range, 33-92 years) and 7162 CT scans. Muscle metrics qualitatively decreased with increasing age and female sex.
This study established age- and sex-specific reference values for CT-based muscle metrics at thoracic and lumbar vertebral levels. These values may be used in future research investigating the role of muscle mass and attenuation in health and disease, and to identify sarcopenia.
Tonnesen PE
，Mercaldo ND
，Tahir I
，Dietrich AW
，Amayri W
，Graur A
，Allaire B
，Bouxsein ML
，Samelson EJ
，Kiel DP
，Fintelmann FJ
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ResearchGate
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