Please use this identifier to cite or link to this item: https://ahro.austin.org.au/austinjspui/handle/1/30649
Title: Quantitative computed tomography predicts outcomes in idiopathic pulmonary fibrosis.
Austin Authors: Humphries, Stephen M;Mackintosh, John A;Jo, Helen E;Walsh, Simon L F;Silva, Mario;Calandriello, Lucio;Chapman, Sally;Ellis, Samantha;Glaspole, Ian;Goh, Nicole S L ;Grainge, Christopher;Hopkins, Peter M A;Keir, Gregory J;Moodley, Yuben;Reynolds, Paul N;Walters, E Haydn;Baraghoshi, David;Wells, Athol U;Lynch, David A;Corte, Tamera J
Affiliation: Department of Medicine, University of Tasmania, Hobart, Tasmania, Australia..
Department of Radiology, National Jewish Health, Denver, Colorado, USA..
Department of Thoracic Medicine, The Prince Charles Hospital, Brisbane, Queensland, Australia..
NHMRC Centre of Research Excellence in Pulmonary Fibrosis, Camperdown, New South Wales, Australia..
Department of Respiratory Medicine, Royal Prince Alfred Hospital, Sydney, New South Wales, Australia..
Respiratory Consultants, Adelaide, South Australia, Australia..
Department of Radiology, Alfred Health, Melbourne, Victoria, Australia..
Department of Allergy and Respiratory Medicine, Alfred Hospital, Melbourne, Victoria, Australia..
Respiratory and Sleep Medicine
Department of Respiratory Medicine, John Hunter Hospital, Newcastle, New South Wales, Australia..
Faculty of Medicine, The University of Queensland, Brisbane, Queensland, Australia..
Department of Respiratory Medicine, Princess Alexandra Hospital, Brisbane, Queensland, Australia..
School of Medicine & Pharmacology, University of Western Australia, Perth, Western Australia, Australia..
Department of Thoracic Medicine, Royal Adelaide Hospital, Adelaide, South Australia, Australia..
Department of Radiology, King's College Hospital Foundation Trust, London, UK..
Section of "Scienze Radiologiche", Department of Medicine and Surgery (DiMeC), University of Parma, Parma, Italy..
Dipartimento di Diagnostica per immagini, Radioterapia, Oncologia ed Ematologia, Fondazione Policlinico Universitario A. Gemelli, IRCCS, Rome, Italy..
Division of Biostatistics, National Jewish Health, Denver, Colorado, USA..
Royal Brompton and Harefield NHS Foundation Trust, London, UK.. National Heart and Lung Institute, Imperial College London, London, UK..
Department of Radiology, National Jewish Health, Denver, Colorado, USA..
Department of Radiology, University of Massachusetts Medical School, UMass Memorial Health Care, Worcester, Massachusetts, USA..
Issue Date: 25-Jul-2022
Date: 2022
Publication information: Respirology (Carlton, Vic.) 2022; 27(12)
Abstract: Prediction of disease course in patients with progressive pulmonary fibrosis remains challenging. The purpose of this study was to assess the prognostic value of lung fibrosis extent quantified at computed tomography (CT) using data-driven texture analysis (DTA) in a large cohort of well-characterized patients with idiopathic pulmonary fibrosis (IPF) enrolled in a national registry. This retrospective analysis included participants in the Australian IPF Registry with available CT between 2007 and 2016. CT scans were analysed using the DTA method to quantify the extent of lung fibrosis. Demographics, longitudinal pulmonary function and quantitative CT metrics were compared using descriptive statistics. Linear mixed models, and Cox analyses adjusted for age, gender, BMI, smoking history and treatment with anti-fibrotics were performed to assess the relationships between baseline DTA, pulmonary function metrics and outcomes. CT scans of 393 participants were analysed, 221 of which had available pulmonary function testing obtained within 90 days of CT. Linear mixed-effect modelling showed that baseline DTA score was significantly associated with annual rate of decline in forced vital capacity and diffusing capacity of carbon monoxide. In multivariable Cox proportional hazard models, greater extent of lung fibrosis was associated with poorer transplant-free survival (hazard ratio [HR] 1.20, p < 0.0001) and progression-free survival (HR 1.14, p < 0.0001). In a multi-centre observational registry of patients with IPF, the extent of fibrotic abnormality on baseline CT quantified using DTA is associated with outcomes independent of pulmonary function.
URI: https://ahro.austin.org.au/austinjspui/handle/1/30649
DOI: 10.1111/resp.14333
ORCID: 0000-0002-5113-4530
0000-0002-5254-4144
0000-0003-2065-4346
0000-0002-6565-9928
0000-0001-9979-8726
0000-0002-0777-1196
0000-0002-2273-1774
0000-0003-2108-6248
0000-0002-7096-9365
Journal: Respirology (Carlton, Vic.)
PubMed URL: 35875881
PubMed URL: https://pubmed.ncbi.nlm.nih.gov/35875881/
Type: Journal Article
Subjects: data-driven texture analysis
idiopathic pulmonary fibrosis
pulmonary function
quantitative computed tomography
Appears in Collections:Journal articles

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