Age-related changes in muscle quality and development of diagnostic cutoff points for myosteatosis in lumbar skeletal muscles measured by CT scan

Lee

et al. 2021

Obesity

Self Cite

Studies performed over the past decades clearly showed that body fat distribution, especially visceral fat accumulation, plays a major role in the pathogenesis of insulin resistance and a metabolically unhealthy phenotype (1-3). However, previous studies showed conflicting results on the contribution of lean body mass or skeletal muscle mass to the pathogenesis and development of insulin resistance and a metabolically unhealthy phenotype (2,(4)(5)(6)(7)(8)(9)(10)(11)(12). Although many studies showed that high lean body mass or skeletal muscle mass was associated with high levels of insulin sensitivity and/or metabolic health (4)(5)(6)12,13), many other studies also consistently reported that high lean body mass was associated with a metabolically unhealthy phenotype (1,2,7-11).

Section: Discussionmentioning

confidence: 97%

Section: Discussionmentioning

confidence: 99%

mentioning

confidence: 99%

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Comparison of muscle mass and quality between metabolically healthy and unhealthy phenotypes

Lee

et al. 2021

Obesity

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“…In cases of lower SMD, there will be a larger percentage of IntraMAT (22), indicating the lower quality of skeletal muscle (23). Moreover, IMAT was assessed by identifying visible adipose tissue within muscle fascia at the T12 vertebral level according to fat tissue thresholds (−30 to−190 HU) (24,25). Higher IMAT indicates poorer muscle quality.…”

Section: Measurements Of Muscle Mass and Muscle Quality Indicatorsmentioning

confidence: 99%

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

Jing

et al. 2021

Front. Med.

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.

BMC Musculoskelet Disord

“…The abdominopelvic CT is widely used as a standard diagnostic tool in many clinical settings for procedures such as cancer treatment, major surgery, and assessment of vascular disease [ 16 , 17 ]. Thus, the body composition analysis in clinically acquired abdominopelvic CT scans is useful for patients who have required CT scans for their disease management [ 18 ].…”

Section: Introductionmentioning

confidence: 99%

A reliable and robust method for the upper thigh muscle quantification on computed tomography: toward a quantitative biomarker for sarcopenia

Shin

Sung

et al. 2022

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Background We aimed to evaluate the feasibility of the upper thigh level as a landmark to measure muscle area for sarcopenia assessment on computed tomography (CT). Methods In the 116 healthy subjects who performed CT scans covering from mid-abdomen to feet, the skeletal muscle area in the upper thigh level at the inferior tip of ischial tuberosity (SMAUT), the mid-thigh level (SMAMT), and L3 inferior endplate level (SMAL3) were measured by two independent readers. Pearson correlation coefficients between SMAUT, SMAMT, and SMAL3 were calculated. Inter-reader agreement between the two readers were evaluated using intraclass correlation coefficient (ICC) and Bland-Altman plots with 95% limit of agreement (LOA). Results In readers 1 and 2, very high positive correlations were observed between SMAUT and SMAMT (r = 0.91 and 0.92, respectively) and between SMAUT and SMAL3 (r = 0.90 and 0.91, respectively), while high positive correlation were observed between SMAMT and SMAL3 (r = 0.87 and 0.87, respectively). Based on ICC values, the inter-reader agreement was the best in the SMAUT (0.999), followed by the SMAL3 (0.990) and SMAMT (0.956). The 95% LOAs in the Bland-Altman plots indicated that the inter-reader agreement of the SMAUT (− 0.462 to 1.513) was the best, followed by the SMAL3 (− 9.949 to 7.636) and SMAMT (− 12.105 to 14.605). Conclusion Muscle area measurement at the upper thigh level correlates well with those with the mid-thigh and L3 inferior endpoint level and shows the highest inter-reader agreement. Thus, the upper thigh level might be an excellent landmark enabling SMAUT as a reliable and robust biomarker for muscle area measurement for sarcopenia assessment.