Feasibility of using chest computed tomography (CT) imaging at the first lumbar vertebra (L1) level to assess skeletal muscle mass: a retrospective study

Author:

Liu Shaohua12ORCID,Han Xia3,Li Jianjun4,Xie Xia5,Yang Yunkai6,Jiang Wangyan12,Liu Li12,Liu Zhelong12

Affiliation:

1. Department of Endocrinology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China

2. Branch of National Clinical Research Center for Metabolic Diseases, Wuhan, Hubei, China

3. Wuhan Wuchang Hospital, Wuhan, China

4. Department of Radiology, Tongji Hospital, Tongji Medical College; Huazhong University of Science and Technology, Wuhan, China

5. School of Computer Science and Technology, Hainan University, Haikou, China

6. Eight-year Program of Clinical Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China

Abstract

Background Skeletal muscle mass is an essential parameter for diagnosing sarcopenia. The gold standard for assessing skeletal muscle mass is using computed tomography (CT) to measure skeletal muscle area at the third lumbar vertebra (L3) level. This study aims to investigate whether skeletal muscle mass could be evaluated at the first lumbar vertebra (L1) level using images obtained from routine chest CT scans. Methods Skeletal muscle index (SMI, cm2/m2) and skeletal muscle density (SMD, HU) are commonly used to measure relative muscle mass and the degree of fat infiltration. This study used CT images at the L1 level to measure the skeletal muscle area (SMA, cm2) in 815 subjects from the health examination center. Linear regression analysis was used to explore the association between L1 and L3 measurements. The receiver operating characteristic (ROC) analysis was used to assess the predictive performance of L1 SMI for sarcopenia. The sex-specific cut-off values for low skeletal muscle mass in patients under the age of 60 were determined using the following formula: “mean − 1.28 × standard deviation.” A multivariate linear regression model was established. Results A significantly higher SMI at the L1 level was found in males than in females (43.88 ± 6.33 cm2/m2 vs 33.68 ± 5.03 cm2/m2; P < 0.001). There were strong correlations between measures at the L1 and L3 levels in both the total subject and sex-specific analyses. A negative association was found between age and L3 SMI in males (r = −0.231, P = 0.038). Both body mass index (BMI) and body surface area (BSA) were positively associated with L1 SMI in both males and females. A multivariate analysis was used to establish a prediction rule to predict SMI at the L3 level. The assessment of consistency and interchangeability between predicted and actual SMI at the L3 level yielded moderately good results. Considering the significant differences observed between male and female participants, the sex-specific cut-off values of the L1 SMI for defining low skeletal muscle mass were 36.52 cm2/m2 in males and 27.29 cm2/m2 in females. Conclusions Based on a population from central China, the correlated indicators obtained at the L1 level from routine chest CT scans may serve as effective surrogate markers for those at the L3 level in assessing overall skeletal muscle mass.

Funder

Teaching Research Fund of Huazhong University of Science and Technology

Sen-Mei China Diabetes Research Fund

Publisher

PeerJ

Subject

General Agricultural and Biological Sciences,General Biochemistry, Genetics and Molecular Biology,General Medicine,General Neuroscience

Reference39 articles.

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