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 intramuscular adipose tissue (IMAT), and low-attenuation muscle area (LAMA). IMAT/SMA ratio and height- and weight-related skeletal muscle indices (SMI) were calculated.

Results: The ETI group showed a significant increase in SMA over time (p < 0.001), whereas the IMAT, LAMA, and IMAT/SMA ratio increased in both groups (all p < 0.05). SMI showed alterations only in the ETI group, with an increase in SMA/m² (p < 0.001) and a decrease in SMA/kg (p = 0.003) and SMA/BMI (p = 0.006). Sex-specific analysis showed that SMA and myosteatosis increased regardless of sex (all p < 0.05). Weight-adjusted SMI decreased only in females receiving ETI therapy (p < 0.05).

Conclusions: Adult pwCF, particularly those undergoing ETI therapy, experience significant changes in body composition, including increased muscle mass and myosteatosis. Trends in the development of sarcopenic obesity have been observed, particularly in female pwCF. These findings emphasize the importance of comprehensive body composition assessments and targeted interventions in pwCF treated with ETI to optimize muscle mass and quality while managing adipose tissue accumulation.