ArticleMultidisciplinary respiratory medicine2018
Assessment of survival in patients with idiopathic pulmonary fibrosis using quantitative HRCT indexes.
Article in Multidisciplinary respiratory medicine, 2018. 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.
- Assessment of fibrosing interstitial lung disease progression: CT visual score on radiological progressive pulmonary fibrosis criteria versus 3D-CT volume-histogram analysis.Japanese journal of radiology · 2026Article
- Quantitative HRCT-Derived Fibrosis Burden as an Independent Predictor of Mortality in Patients with Idiopathic Pulmonary Fibrosis: A Retrospective Observational Study.Journal of clinical medicine · 2026Article
- Scoring Pulmonary Fibrosis Following COVID-19 Pneumonia with Quantitative HRCT: Relationship with Clinical Parameters, Mean Platelet Volume and Lymphocyte/Monocyte RatioThoracic research and practice · 2025Article
- Integrating Radiomics Signature into Clinical Pathway for Patients with Progressive Pulmonary Fibrosis.Diagnostics (Basel, Switzerland) · 2025Review
- Biomarkers reflecting the pathogenesis, clinical manifestations, and guide therapeutic approach in systemic sclerosis: a narrative review.Clinical rheumatology · 2024Review
- Volume changes of diseased and normal areas in progressive fibrosing interstitial lung disease on inspiratory and expiratory computed tomography.Japanese journal of radiology · 2024Article
- Biodistribution Assessment of a NovelLife (Basel, Switzerland) · 2024Article
- A Critical Analysis of the Robustness of Radiomics to Variations in Segmentation Methods inDiagnostics (Basel, Switzerland) · 2023Article
- Histogram-based analysis in progressive pulmonary fibrosis: relationships between pulmonary functional tests and HRCT indexes.The British journal of radiology · 2023Article
- Idiopathic pulmonary fibrosis disease progression: a dynamic quantitative chest computed tomography follow-up analysis.Quantitative imaging in medicine and surgery · 2023Article
- Quantitative analysis of high-resolution computed tomography features of idiopathic pulmonary fibrosis: a structure-function correlation study.Quantitative imaging in medicine and surgery · 2022Article
- Customized Efficient Neural Network for COVID-19 Infected Region Identification in CT Images.Journal of imaging · 2021Article
- Several specific high-resolution computed tomography patterns correlate with survival in patients with idiopathic pulmonary fibrosis.Journal of thoracic disease · 2021Article
- Quantitative Evaluation of Fibrosis in IPF Patients: Meaning of Diffuse Pulmonary Ossification.Diagnostics (Basel, Switzerland) · 2021Article
- Quantitative CT in mortality prediction in pulmonary fibrosis with or without emphysema.Sarcoidosis, vasculitis, and diffuse lung diseases : official journal of WASOG · 2021Article
- Lung Segmentation on High-Resolution Computerized Tomography Images Using Deep Learning: A Preliminary Step for Radiomics Studies.Journal of imaging · 2020Article
- Performance of Radiomics Features in the Quantification of Idiopathic Pulmonary Fibrosis from HRCT.Diagnostics (Basel, Switzerland) · 2020Article
- Research highlights from the 2018 ERS International Congress: interstitial lung diseases.ERJ open research · 2019Review
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15 authors.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundThe assessment of Idiopathic Pulmonary Fibrosis (IPF) using HRCT requires great experience and is limited by a significant inter-observer variability, even between trained radiologists. The evaluation of HRCT through automated quantitative analysis may hopefully solve this problem. The accuracy of CT-histogram derived indexes in the assessment of survival in IPF patients has been poorly studied.
methodsForty-two patients with a diagnosis of IPF and a follow up time of 3 years were retrospectively collected; HRCT and Pulmonary Function Tests (PFTs) performed at diagnosis time were analysed; the extent of fibrotic disease was quantified on HRCT using kurtosis, skewness, Mean Lung Density (MLD), High attenuation areas (HAA%) and Fibrotic Areas (FA%). Univariate Cox regression was performed to assess hazard ratios for the explored variables and a multivariate model considering skewness, FVC, DL
resultsKurtosis, skewness, MLD, HAA% and FA% were good predictors of mortality (HR 0.44, 0.74, 1.01, 1.12, 1.06;
conclusionsCT-histogram derived indexes may provide an accurate estimation of survival in IPF patients. They demonstrate a correlation with PFTs, highlighting their possible use in clinical practice.
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