Automated muscle measurement on chest CT predicts all-cause mortality in older adults from the National Lung Screening Trial

Leon Lenchik, Ryan Barnard, Robert D. Boutin, Stephen B. Kritchevsky, Haiying Chen, Josh Tan, Peggy M. Cawthon, Ashley A. Weaver, Fang Chi Hsu

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

Background: Muscle metrics derived from computed tomography (CT) are associated with adverse health events in older persons, but obtaining these metrics using current methods is not practical for large datasets. We developed a fully automated method for muscle measurement on CT images. This study aimed to determine the relationship between muscle measurements on CT with survival in a large multicenter trial of older adults. Method: The relationship between baseline paraspinous skeletal muscle area (SMA) and skeletal muscle density (SMD) and survival over 6 years was determined in 6,803 men and 4,558 women (baseline age: 60-69 years) in the National Lung Screening Trial (NLST). The automated machine learning pipeline selected appropriate CT series, chose a single image at T12, and segmented left paraspinous muscle, recording cross-sectional area and density. Associations between SMA and SMD with all-cause mortality were determined using sex-stratified Cox proportional hazards models, adjusted for age, race, height, weight, pack-years of smoking, and presence of diabetes, chronic lung disease, cardiovascular disease, and cancer at enrollment. Results: After a mean 6.44 ± 1.06 years of follow-up, 635 (9.33%) men and 265 (5.81%) women died. In men, higher SMA and SMD were associated with a lower risk of all-cause mortality, in fully adjusted models. A one-unit standard deviation increase was associated with a hazard ratio (HR) = 0.85 (95% confidence interval [CI] = 0.79, 0.91; p <. 001) for SMA and HR = 0.91 (95% CI = 0.84, 0.98; p =. 012) for SMD. In women, the associations did not reach significance. Conclusion: Higher paraspinous SMA and SMD, automatically derived from CT exams, were associated with better survival in a large multicenter cohort of community-dwelling older men.

Original languageEnglish (US)
Pages (from-to)277-285
Number of pages9
JournalJournals of Gerontology - Series A Biological Sciences and Medical Sciences
Volume76
Issue number2
DOIs
StatePublished - Feb 1 2021
Externally publishedYes

Keywords

  • Computed tomography
  • Machine learning
  • Mortality
  • Myosteatosis
  • Sarcopenia

ASJC Scopus subject areas

  • Aging
  • Geriatrics and Gerontology

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