Automatic quantitative evaluation of high-resolution computed tomography scans of patients with interstitial lung diseases.

PURPOSE: High-resolution computed tomography (HRCT) is essential in clinical evaluation and management of interstitial lung diseases (ILDs). Quantitative analysis can assist in both accurate diagnosis and longitudinal assessment. The aim was to verify the role of automatic quantitative analysis of HRCT images in the diagnosis and classification of ILD.

METHODS

Retrospective single-center study evaluating patients undergoing investigation for fibrosing ILD between 2010 and 2019. HRCT images were re-evaluated, ILD patterns were classified according to the 2018 ATS/ERS/JRS/ALAT consensus. Demographic and clinical variables, distribution of fibrosis and honeycombing pattern, and variables obtained from the quantitative analysis performed by YACTA scientific program were compared between ILD groups according to the 2018 ATS/ERS/JRS/ALAT consensus and to the radiological patterns of idiopathic interstitial pneumonia (IIP), using ANOVA, Kruskal-Wallis H test or Pearson's chi-squared test.

RESULTS

481 patients (mean age 57.7 ± 14 years, 277 women, 204 men) were evaluated. Patients with radiological pattern of usual interstitial pneumonia (UIP) exhibited lower lung volumes, higher mean lung densities (UIP group, -698.8 ± 66.3; probable UIP group, -743.8 ± 47.9; alternative diagnosis to UIP, -712.7 ± 73.7; p = 0.01), and higher absolute vascular lung volumes. Among tomographic patterns of IIP, bronchiolocentric interstitial pneumonia demonstrated smaller lung volume and higher lung density. Collagen vascular disease was the most prevalent.

CONCLUSION

This study demonstrated that, in a large dataset of exams, the fully automated quantitative analysis of HRCTs is an objective method, which can help in the diagnostic workup of ILDs.