Artigo Produção Nacional Revisado por pares

Quantitative CT Analysis in Chronic Hypersensitivity Pneumonitis: A Convolutional Neural Network Approach

2020; Elsevier BV; Volume: 29; Linguagem: Inglês

10.1016/j.acra.2020.10.009

ISSN

1878-4046

Autores

Lorenzo Aliboni, Olívia Meira Dias, Francesca Pennati, Bruno Guedes Baldi, Márcio Valente Yamada Sawamura, Rodrigo Caruso Chate, Carlos Roberto Ribeiro de Carvalho, André Luís Pereira de Albuquerque, Andréa Aliverti,

Tópico(s)

Inhalation and Respiratory Drug Delivery

Resumo

Chronic hypersensitivity pneumonitis (cHP) is a heterogeneous condition, where both small airway involvement and fibrosis may simultaneously occur. Computer-aided analysis of CT lung imaging is increasingly used to improve tissue characterization in interstitial lung diseases (ILD), quantifying disease extension, and progression. We aimed to quantify via a convolutional neural network (CNN) method the extent of different pathological classes in cHP, and to determine their correlation to pulmonary function tests (PFTs) and mosaic attenuation pattern.The extension of six textural features, including consolidation (C), ground glass opacity (GGO), fibrosis (F), low attenuation areas (LAA), reticulation (R) and healthy regions (H), was quantified in 27 cHP patients (age: 56 ± 11.5 years, forced vital capacity [FVC]% = 57 ± 17) acquired at full-inspiration via HRCT. Each class extent was correlated to PFTs and to mosaic attenuation pattern.H showed a positive correlation with FVC%, FEV1% (forced expiratory volume), total lung capacity%, and diffusion of carbon monoxide (DLCO)% (r = 0.74, r = 0.78, r = 0.73, and r = 0.60, respectively, p < 0.001). GGO, R and C negatively correlated with FVC% and FEV1% with the highest correlations found for R (r = -0.44, and r = -0.46 respectively, p < 0.05); F negatively correlated with DLCO% (r = -0.42, p < 0.05). Patients with mosaic attenuation pattern had significantly more H (p = 0.04) and lower R (p = 0.02) and C (p = 0.0009) areas, and more preserved lung function indices (higher FVC%; p = 0.04 and DLCO%; p = 0.05), but did not show more air trapping in lung function tests.CNN quantification of pathological tissue extent in cHP improves its characterization and shows correlation with PFTs. LAA can be overestimated by visual, qualitative CT assessment and mosaic attenuation pattern areas in cHP represents patchy ILD rather than small-airways disease.

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