ArticleDiagnostics (Basel, Switzerland)2022
Effects of Automatic Deep-Learning-Based Lung Analysis on Quantification of Interstitial Lung Disease: Correlation with Pulmonary Function Test Results and Prognosis.
Article in Diagnostics (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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15 citing papers in PubMed, 19 citations in OpenAlex.
- Pleuroparenchymal fibroelastosis-like findings identify an idiopathic pulmonary fibrosis subgroup with shortened telomeres and poor prognosis.ERJ open research · 2026Article
- Integrated phenotyping identifies reproducible prognostic subgroups in idiopathic pleuroparenchymal fibroelastosis.Respiratory research · 2026Observational
- Transbronchial lung cryobiopsy in fibrotic hypersensitivity pneumonitis: prognostic differences and intra-lobar variability.BMC pulmonary medicine · 2026Article
- Volume histogram analysis of whole-lung CT: differentiating usual from nonspecific interstitial pneumonias and predicting prognosis.Japanese journal of radiology · 2026Article
- Deep-learning-based 3D content-based image retrieval system on chest HRCT: Performance assessment for interstitial lung diseases and usual interstitial pneumonia.European journal of radiology open · 2025Article
- Quantitative analysis of pathological findings identified clinical heterogeneity in nonspecific interstitial pneumonia with organising pneumonia overlap.Scientific reports · 2025Article
- Interstitial lung disease associated with anti-aminoacyl-tRNA synthetase syndrome: quantitative evaluation of CT after initial treatment and long-term follow-up.Acta radiologica (Stockholm, Sweden : 1987) · 2024Article
- Correlation of CT-based radiomics analysis with pathological cellular infiltration in fibrosing interstitial lung diseases.Japanese journal of radiology · 2024Article
- The Role of Inflammation and Fibrosis in Interstitial Lung Disease Treatment Decisions.American journal of respiratory and critical care medicine · 2024Article
- Evaluation of Progressive Architectural Distortion in Idiopathic Pulmonary Fibrosis Using Deformable Registration of Sequential CT Images.Diagnostics (Basel, Switzerland) · 2024Article
- Longitudinal assessment of interstitial lung abnormalities on CT in patients with COPD using artificial intelligence-based segmentation: a prospective observational study.BMC pulmonary medicine · 2024Observational
- Advances in CT-based lung function imaging for thoracic radiotherapy.Frontiers in oncology · 2024Review
- Quantitative Analysis for Lung Disease on Thin-Section CT.Diagnostics (Basel, Switzerland) · 2023Review
- Semi-Supervised Segmentation of Interstitial Lung Disease Patterns from CT Images via Self-Training with Selective Re-Training.Bioengineering (Basel, Switzerland) · 2023Article
- Recent Advances of Artificial Intelligence Applications in Interstitial Lung Diseases.Diagnostics (Basel, Switzerland) · 2023Review
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Authors and funding
8 authors at 3 institutions in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
We investigated the feasibility of a new deep-learning (DL)-based lung analysis method for the evaluation of interstitial lung disease (ILD) by comparing it with evaluation using the traditional computer-aided diagnosis (CAD) system and patients’ clinical outcomes. We prospectively included 104 patients (84 with and 20 without ILD). An expert radiologist defined regions of interest in the typical areas of normal, ground-glass opacity, consolidation, consolidation with fibrosis (traction bronchiectasis), honeycombing, reticulation, traction bronchiectasis, and emphysema, and compared them with the CAD and DL-based analysis results. Next, we measured the extent of ILD lesions with the CAD and DL-based analysis and compared them. Finally, we compared the lesion extent on computed tomography (CT) images, as measured with the DL-based analysis, with pulmonary function tests results and patients’ overall survival. Pearson’s correlation analysis revealed a significant correlation between DL-based analysis and CAD results. Forced vital capacity was significantly correlated with DL-based analysis (r = 0.789, p < 0.001 for normal lung volume and r = −0.316, p = 0.001 for consolidation with fibrosis volume). Consolidation with fibrosis measured using DL-based analysis was independently associated with poor survival. The lesion extent measured using DL-based analysis showed a negative correlation with the pulmonary function test results and prognosis.
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