ArticleBMC pulmonary medicine2024
Quantitative CT analysis of idiopathic pulmonary fibrosis and correlation with lung function study.
Article in BMC pulmonary medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed.
- Correlations between quantitative computed tomography metrics with serum fibrosis biomarkers, pulmonary function, and mortality risk in patients with idiopathic pulmonary fibrosis: a prospective cohort study.Journal of thoracic disease · 2026Article
- Association of CYFRA 21-1 with quantitative CT-defined fibrotic progression in idiopathic pulmonary fibrosis.BMC pulmonary medicine · 2026Article
- Exploratory evaluation of earlyEuropean journal of nuclear medicine and molecular imaging · 2026Article
- Strain analysis based on dynamic ventilation computed tomography in fibrotic interstitial lung disease and its correlation with pulmonary function tests.Quantitative imaging in medicine and surgery · 2026Article
- Fibroblast activation protein inhibitor (FAPI) PET imaging in pulmonary fibrosis: pathophysiology, clinical utility, and emerging theranostic applications.Respiratory research · 2026Review
- Multidimensional lung imaging: integrated preclinical platforms enabling the identification of translational biomarkers for pulmonary research.Respiratory research · 2026Review
- Association of dual-energy CT-derived quantitative parameters with hydroxyproline levels and pulmonary function in nonspecific interstitial pneumonia.Frontiers in immunology · 2026Article
- Simultaneous inhibition of ID1 and ID3 mitigates fibroblast activation via cell cycle and MEK/ERK pathways in pulmonary fibrosis.Theranostics · 2026Article
- The characteristics of pulmonary fibrosis in a neonatal rat model of chronic hyperoxia lung injury.Translational pediatrics · 2025Article
- Predictors of Disease Progression in Idiopathic Pulmonary Fibrosis Under Antifibrotic Therapy: A Retrospective Study.Cureus · 2025Article
- Ejection fraction quantification from ungated chest CT by AI.medRxiv : the preprint server for health sciences · 2025Article
- Exploring diagnostic gene markers and immune infiltration in idiopathic pulmonary fibrosis.Journal of thoracic disease · 2025Article
- What role does artificial intelligence-driven quantitative analysis of chest computed tomography play in providing pulmonary function for idiopathic pulmonary fibrosis patients undergoing pirfenidone treatment?Quantitative imaging in medicine and surgery · 2025Article
- Article
- Prediction of pulmonary function decline in fibrous interstitial lung abnormalities based on quantitative chest CT parameters.BMC medical imaging · 2025Article
- Review
- Artificial Intelligence Unveils the Unseen: Mapping Novel Lung Patterns in Bronchiectasis via Texture Analysis.Diagnostics (Basel, Switzerland) · 2024Article
- Compatibility analysis of total lung capacity values measured by segmentation with computed tomography and helium dilution method.Annals of thoracic medicineArticle
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6 authors.
Funding
Abstract
backgroundIdiopathic Pulmonary Fibrosis (IPF) is a progressive fibrotic lung disease. However, the field of quantitative CT scan analysis in conjunction with pulmonary function test for IPF patients remains relatively understudied. In this study, we evaluated the diagnostic value of features derived high-resolution computed tomography (HRCT) for patients with IPF and correlated them with pulmonary function tests.
methodsWe retrospectively analyzed the chest HRCT images and pulmonary function test results of 52 patients with IPF during the same period (1 week) and selected 52 healthy individuals, matched for sex, age, and body mass index (BMI) and with normal chest HRCT as controls. HRCT scans were performed using a Philips 256-row Brilliance iCT scanner with standardized parameters. Lung function tests were performed using a Jaeger volumetric tracer for forced vital capacity (FVC), total lung capacity (TLC), forced expiratory volume in first second (FEV1), FEV1/FVC, carbon monoxide diffusing capacity (DLCO), and maximum ventilation volume (MVV) metrics. CT quantitative analysis, including tissue segmentation and threshold-based quantification of lung abnormalities, was performed using 3D-Slicer software to calculate the percentage of normal lung areas (NL%), percentage of ground-glass opacity areas (GGO%), percentage of fibrotic area (F%) and abnormal lesion area percentage (AA%). Semi-quantitative analyses were performed by two experienced radiologists to assess disease progression. The aortic-to-sternal distance (ASD) was measured on axial images as a standardized parameter. Spearman or Pearson correlation analysis and multivariate stepwise linear regression were used to analyze the relationship between the data in each group, and the ROC curve was used to determine the optimal quantitative CT metrics for identifying IPF and controls.
resultsROC curve analysis showed that F% distinguished the IPF patient group from the control group with the largest area under the curve (AUC) of 0.962 (95% confidence interval: 0.85-0.96). Additionally, with F% = 4.05% as the threshold, the Youden's J statistic was 0.827, with a sensitivity of 92.3% and a specificity of 90.4%. The ASD was significantly lower in the late stage of progression than in the early stage (t = 5.691, P < 0.001), with a mean reduction of 2.45% per month. Quantitative CT indices correlated with all pulmonary function parameters except FEV1/FVC, with the highest correlation coefficients observed for F% and TLC%, FEV1%, FVC%, MVV% (r = - 0.571, - 0.520, - 0.521, - 0.555, respectively, all P-values < 0.001), and GGO% was significantly correlated with DLCO% (r = - 0.600, P < 0.001). Multiple stepwise linear regression analysis showed that F% was the best predictor of TLC%, FEV1%, FVC%, and MVV% (R
conclusionsQuantitative CT analysis can be used to diagnose IPF and assess lung function impairment. A decrease in the ASD may indicate disease progression.
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