Association of computed tomography densitometry with disease progression and spatial heterogeneity in rheumatoid arthritis-associated interstitial lung disease.

OBJECTIVES

This study aimed to assess the efficacy of quantitative computed tomography (qCT) in distinguishing rheumatoid arthritis-associated interstitial lung disease (RA-ILD) and monitoring its progression.

METHODS

HRCT images of 138 RA-ILD patients (GAPI, n = 90; GAPII+III, n = 48) and 47 RA controls were retrospectively analyzed. The normal lung attenuation areas (NL%), the percentage of low attenuation areas (LAA%), and the percentage of high-attenuation areas (HAA%) were measured for each lung lobe. Correlations between qCT indices and pulmonary function tests were evaluated using Spearman's rank correlation. ROC curves tested the discriminative performance of qCT indices. Multivariable logistic regression assessed associations between qCT indices and RA-ILD.

RESULTS

The NL% decreased, while the LAA% and HAA% increased in the early and moderate-to-advanced stages of ILD, respectively (p < 0.05). Multivariate regression identified HAA% as an independent risk factor for ILD staging (OR: 1.737, 95% CI: 1.182-2.551, p = 0.005). When combining NL%, LAA%, and HAA%, the AUCs for early diagnosis and progression monitoring were 0.760 and 0.773, respectively (p < 0.05). RA-ILD exhibited spatial heterogeneity, with the lower lobes being primarily affected.

CONCLUSIONS

Quantitative parameters can effectively differentiate early-stage RA-ILD and monitor its progression. LAA% is significantly correlated with early diagnosis, whereas HAA% demonstrates higher specificity in later stages. Quantitative lung densitometry may prove to be a valuable tool for clinical decision-making.