Observational studyClinical rheumatology2025
The potential of semi-quantitative and quantitative methods in predicting progression in rheumatoid arthritis-associated interstitial lung disease.
Observational study in Clinical rheumatology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Bibliometric Analysis of Pulmonary Fibrosis Imaging Research: Knowledge Graph Construction Based on the Web of Science Core Database.Malawi medical journal : the journal of Medical Association of Malawi · 2026Article
- Evolving landscape of imaging-based evaluation in systemic autoimmune rheumatic disease-associated interstitial lung disease: from visual assessment to quantitative artificial intelligence-assisted evaluation.Journal of rheumatic diseases · 2026Review
- A transfer learning-based multimodal model for early prediction of 90-day respiratory failure in dermatomyositis-associated interstitial lung disease.Frontiers in immunology · 2026Article
- Cluster analysis and risk prediction model construction for antisynthase syndrome-associated interstitial lung disease based on clinical, imaging, and antibody characteristics.Frontiers in medicine · 2026Article
- Targeting fibroblast activation protein in rheumatoid arthritis: from molecular imaging to precision therapeutics.Frontiers in immunology · 2025Review
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionRheumatoid arthritis-associated interstitial lung disease (RA-ILD) presents with variable severity and progression, highlighting the need for effective tools to identify patients at risk. Although CT imaging plays a vital role in the management of RA-ILD, there is a lack of objective methods to predict disease progression. This study investigates the association between semi-quantitative and quantitative CT scoring methods and disease progression in early-stage RA-ILD.
methodsThis observational study analyzed baseline and the first technically evaluable follow-up CT scans of patients who met the 2010 ACR/EULAR classification criteria for RA and were diagnosed with ILD. Only patients with ≤ 5 years between baseline and follow-up scans were included. Semi-quantitative assessments were conducted using the Goh and Warrick scoring systems, while quantitative analyses utilized Vitrea software to measure mean lung attenuation (MLA) and low-, medium-, and high-density lung volumes. Progression risk factors were evaluated using binary logistic regression, with progression defined by changes in CT parameters over time.
resultsA total of 77 RA-ILD patients (45 females, 32 males) were included, with a median follow-up period of 20 months (interquartile range: 7.4-46 months). Disease progression was observed in 34 patients (44.2%). Baseline medium-density volume (MDV), follow-up mean lung attenuation (MLA), and low-density volume (LDV) differed significantly between the progression and non-progression groups (p < 0.05). Quantitative CT parameters demonstrated strong correlations with both the Goh and Warrick scoring systems. Binary logistic regression analysis identified the usual interstitial pneumonia (UIP) pattern on baseline imaging as the only independent predictor of disease progression (odds ratio: 3.1; 95% confidence interval: 1.1-12.4).
conclusionIn this study of early-stage RA-ILD patients, only the usual interstitial pneumonia (UIP) pattern on baseline HRCT independently predicted disease progression. Neither semi-quantitative scores nor quantitative CT parameters were predictive of progression. However, quantitative CT metrics demonstrated strong correlations with traditional scoring systems, supporting their utility in objectively assessing disease extent.
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