Automated AI-based image analysis for quantification and prediction of interstitial lung disease in systemic sclerosis patients.

ABSTRACT:

Background

Systemic sclerosis (SSc) is a rare connective tissue disease associated with rapidly evolving interstitial lung disease (ILD), driving its mortality. Specific imaging-based biomarkers associated with the evolution of lung disease are needed to help predict and quantify ILD.

Methods

We evaluated the potential of an automated ILD quantification system (icolung^®) from chest CT scans, to help in quantification and prediction of ILD progression in SSc-ILD. We used a retrospective cohort of 75 SSc-ILD patients to evaluate the potential of the AI-based quantification tool and to correlate image-based quantification with pulmonary function tests and their evolution over time.

Results

We evaluated a group of 75 patients suffering from SSc-ILD, either limi

SUBMITTER: Guiot J 

PROVIDER: S-EPMC11762107 | biostudies-literature | 2025 Jan

REPOSITORIES: biostudies-literature