ArticleQuantitative imaging in medicine and surgery2022
Quantitative analysis of high-resolution computed tomography features of idiopathic pulmonary fibrosis: a structure-function correlation study.
Article in Quantitative imaging in medicine and surgery, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.
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11 citing papers in PubMed, 1 synthesis or guideline pooled it, 13 citations in OpenAlex.
- A systematic review of the role of quantitative CT in the prognostication and disease monitoring of interstitial lung disease.European respiratory review : an official journal of the European Respiratory Society · 2025Pooled it
- Automated CT-Based Quantification of Pulmonary Fibrosis Using Deep Learning-Based Lung Segmentation.Diagnostics (Basel, Switzerland) · 2026Article
- Association of artificial intelligence-based high-resolution computed tomography parameters with all-cause mortality in patients with connective tissue disease-associated interstitial lung disease: a longitudinal cohort study.Journal of thoracic disease · 2026Article
- Radiomics and Artificial Intelligence in Pulmonary Fibrosis.Journal of imaging informatics in medicine · 2025Review
- Review
- Evaluation of respiratory muscle dysfunction in patients with idiopathic pulmonary fibrosis: a prospective observational study with magnetic resonance imaging.BMC pulmonary medicine · 2025Observational
- Automated AI-based image analysis for quantification and prediction of interstitial lung disease in systemic sclerosis patients.Respiratory research · 2025Article
- Assessment of lung deformation in patients with idiopathic pulmonary fibrosis with elastic registration technique on pulmonary three-dimensional ultrashort echo time MRI.Insights into imaging · 2024Article
- Radiological findings based comparison of functional status in patients who have post-covid lung injury or idiopathic pulmonary fibrosis.BMC pulmonary medicine · 2023Article
- Idiopathic pulmonary fibrosis disease progression: a dynamic quantitative chest computed tomography follow-up analysis.Quantitative imaging in medicine and surgery · 2023Article
- Sex-Specific Clinical Characteristics and Mortality Predictors in Patients With Usual Interstitial Pneumonia Pattern: A Retrospective Cohort Study Highlighting Male Health Risks.American journal of men's healthArticle
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8 authors at 5 institutions in 1 country.
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Abstract
Background: The quantitative analysis of high-resolution computed tomography (HRCT) is increasingly being used to quantify the severity and evaluate the prognosis of disease. Our aim was to quantify the HRCT features of idiopathic pulmonary fibrosis (IPF) and identify their association with pulmonary function tests. Methods: This was a retrospective, single-center, clinical research study. Patients with IPF were retrospectively included. Pulmonary segmentation was performed using the deep learning-based method. Radiologists manually segmented 4 findings of IPF, including honeycombing (HC), reticular pattern (RE), traction bronchiectasis (TRBR), and ground glass opacity (GGO). Pulmonary vessels were segmented with the automatic integration segmentation method. All segmentation results were quantified by the corresponding segmentation software. Correlations between the volume of the 4 findings on HRCT, volume of the lesions at different sites, pulmonary vascular-related parameters, and pulmonary function tests were analyzed. Results: A total of 101 IPF patients (93 males) with a median age of 63 years [interquartile range (IQR), 58 to 68 years] were included in this study. Total lesion extent demonstrated a stronger negative correlation with diffusion capacity for carbon monoxide (DLco) compared to HC, RE, and TRBR [total lesion ratio, correlation coefficient (r) =-0.67, P<0.001; HC, r=-0.45, P<0.001; RE, r=-0.41, P<0.001; TRBR, r=-0.25, P<0.05, respectively]. Correlations with lung function were similar among various lesion sites with r from -0.38 to -0.61 (P<0.001). Pulmonary artery volume (PAV) displayed a slightly increased positive association with the DLco compared to total pulmonary vascular volume (PVV); for PAV, r=0.41 and P<0.001 and for total PVV, r=0.36 and P<0.001. Additionally, total lesion extent, HC, and RE indicated a negative relationship with vascular-related parameters, and the strength of the correlations was independent of lesion site. Conclusions: Quantitative analysis of HRCT features of IPF indicated a decline in function and an aggravation of vascular destruction with increasing lesion extent. Furthermore, a positive correlation between vascular-related parameters and pulmonary function was confirmed. This co-linearity indicated the potential of vascular-related parameters as new objective markers for evaluating the severity of IPF.
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