OBJECTIVES: Assessment of malnutrition-related muscle depletion with computed tomography (CT) using skeletal muscle index (SMI) and muscle radiation attenuation (MRA) at the third lumbar vertebra is well validated. However, SMI and MRA values at other vertebral locations and interchangeability as parameters in different types of cancer are less known. We aimed to investigate whether adult patients with different types of cancer show differences in SMI and MRA at all vertebral levels.METHODS: We retrospectively analyzed CT images from 203 patients:120 with head and neck cancer, esophageal cancer, or lung cancer (HNC/EC/LC) and 83 with melanoma (ME). Univariate and multivariate linear regression analyses determined the association between SMI (cm²/m 2) and MRA (Hounsfield units) and cancer type at each vertebral level (significance corrected for multiple tests, P ≤ 0.002). The multivariate analyses included age, sex, cancer stage, comorbidity, CT protocol, and body mass index (BMI) (MRA analyses). RESULTS: SMI was lower in the HNC/EC/LC group versus the ME group at all vertebral levels, except C4 through C6 in the multivariate analyses. Female sex was associated with lower SMI at almost all levels. MRA was similar at most vertebral levels in both cancer groups but was lower at C1 through C4, T7, and L5 in the multivariate analyses. Use of contrast fluid and BMI were associated with higher MRA at all vertebral levels except T8 to T9 and C1 to C2, respectively.CONCLUSIONS: SMI, but not MRA, was lower in HNC/EC/LC patients than in ME patients at most vertebral levels. This indicates that low muscle mass presents itself across the various vertebral muscle areas. MRA may less consistently mark muscle depletion in malnourished patients.
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Background & aims: Accurate diagnosis of sarcopenia requires evaluation of muscle quality, which refers to the amount of fat infiltration in muscle tissue. In this study, we aim to investigate whether we can independently predict mortality risk in transcatheter aortic valve implantation (TAVI) patients, using automatic deep learning algorithms to assess muscle quality on procedural computed tomography (CT) scans. Methods: This study included 1199 patients with severe aortic stenosis who underwent transcatheter aortic valve implantation (TAVI) between January 2010 and January 2020. A procedural CT scan was performed as part of the preprocedural-TAVI evaluation, and the scans were analyzed using deep-learning-based software to automatically determine skeletal muscle density (SMD) and intermuscular adipose tissue (IMAT). The association of SMD and IMAT with all-cause mortality was analyzed using a Cox regression model, adjusted for other known mortality predictors, including muscle mass. Results: The mean age of the participants was 80 ± 7 years, 53% were female. The median observation time was 1084 days, and the overall mortality rate was 39%. We found that the lowest tertile of muscle quality, as determined by SMD, was associated with an increased risk of mortality (HR 1.40 [95%CI: 1.15–1.70], p < 0.01). Similarly, low muscle quality as defined by high IMAT in the lowest tertile was also associated with increased mortality risk (HR 1.24 [95%CI: 1.01–1.52], p = 0.04). Conclusions: Our findings suggest that deep learning-assessed low muscle quality, as indicated by fat infiltration in muscle tissue, is a practical, useful and independent predictor of mortality after TAVI.
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INTRODUCTION: In patients with cancer, low muscle mass has been associated with a higher risk of fatigue, poorer treatment outcomes, and mortality. To determine body composition with computed tomography (CT), measuring the muscle quantity at the level of lumbar 3 (L3) is suggested. However, in patients with cancer, CT imaging of the L3 level is not always available. Thus far, little is known about the extent to which other vertebra levels could be useful for measuring muscle status. In this study, we aimed to assess the correlation of the muscle quantity and quality between any vertebra level and L3 level in patients with various tumor localizations.METHODS: Two hundred-twenty Positron Emission Tomography (PET)-CT images of patients with four different tumor localizations were included: 1. head and neck ( n = 34), 2. esophagus ( n = 45), 3. lung ( n = 54), and 4. melanoma ( n = 87). From the whole body scan, 24 slices were used, i.e., one for each vertebra level. Two examiners contoured the muscles independently. After contouring, muscle quantity was estimated by calculating skeletal muscle area (SMA) and skeletal muscle index (SMI). Muscle quality was assessed by calculating muscle radiation attenuation (MRA). Pearson correlation coefficient was used to determine whether the other vertebra levels correlate with L3 level. RESULTS: For SMA, strong correlations were found between C1-C3 and L3, and C7-L5 and L3 ( r = 0.72-0.95). For SMI, strong correlations were found between the levels C1-C2, C7-T5, T7-L5, and L3 ( r = 0.70-0.93), respectively. For MRA, strong correlations were found between T1-L5 and L3 ( r = 0.71-0.95). DISCUSSION: For muscle quantity, the correlations between the cervical, thoracic, and lumbar levels are good, except for the cervical levels in patients with esophageal cancer. For muscle quality, the correlations between the other levels and L3 are good, except for the cervical levels in patients with melanoma. If visualization of L3 on the CT scan is absent, the other thoracic and lumbar vertebra levels could serve as a proxy to measure muscle quantity and quality in patients with head and neck, esophageal, lung cancer, and melanoma, whereas the cervical levels may be less reliable as a proxy in some patient groups.
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