Quantitative CT Scan Analysis in Rheumatoid Arthritis-Related Interstitial Lung Disease.

Area of Science:

• Radiology
• Pulmonology
• Rheumatology

Background:

• Rheumatoid arthritis-related interstitial lung disease (RA-ILD) poses significant outcome prediction challenges.
• Quantitative CT imaging shows potential for assessing disease severity and progression in RA-ILD.

Purpose of the Study:

• To evaluate the utility of deep learning-based lung fibrosis quantitation on CT imaging.
• To assess disease severity, predict mortality, and identify progression in RA-ILD patients.

Main Methods:

• Utilized data-driven texture analysis (DTA) for quantitative CT fibrosis assessment.
• Analyzed primary (n=289) and validation (n=50) RA-ILD cohorts.
• Examined associations between fibrosis scores, pulmonary function, and survival.

Main Results:

• Baseline DTA fibrosis scores negatively correlated with FVC and diffusing capacity.
• Longitudinal DTA fibrosis score changes associated with pulmonary function decline.
• Higher baseline and increasing DTA fibrosis scores significantly predicted mortality risk.

Conclusions:

• Quantitative CT assessment of lung fibrosis in RA-ILD correlates with poorer lung function and increased mortality.
• CT-based fibrosis quantitation serves as a valuable tool for clinical and research outcome assessment in RA-ILD.