Impact of Elexacaftor-Tezacaftor-Ivacaftor on Muscle Composition in Cystic Fibrosis: An AI-Assisted Chest CT-Based Body Composition Analysis.

ABSTRACT:

Background

This study aimed to investigate longitudinal changes in muscle mass, quality, and composition (sarcopenia and myosteatosis) in adult people with cystic fibrosis (pwCF) using artificial intelligence (AI)-assisted body composition analysis (BCA) with chest computed tomography (CT) at the T12 level and to examine the influence of CFTR modulator therapy with elexacaftor/tezacaftor/ivacaftor (ETI).

Methods

A retrospective observational study was conducted on 102 adult pwCF (42 females (41%), mean age 33.9 ± 11.1 years) who underwent routine chest CT scans with a minimum of six months between scans. PwCF were categorized into ETI and no ETI groups. AI-assisted BCA was performed on chest CT images at the T12 level to measure skeletal muscle area (SMA), inter- and intramu

SUBMITTER: Welsner M 

PROVIDER: S-EPMC12734936 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature