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Predicting Outcomes in Idiopathic Pulmonary Fibrosis Using Automated Computed Tomographic Analysis

Authors
  • Jacob, Joseph1, 2
  • Bartholmai, Brian J.3
  • Rajagopalan, Srinivasan3
  • van Moorsel, Coline H. M.4, 5
  • van Es, Hendrik W.6
  • van Beek, Frouke T.4
  • Struik, Marjolijn H. L.4, 5
  • Kokosi, Maria7
  • Egashira, Ryoko8
  • Brun, Anne Laure9
  • Nair, Arjun10
  • Walsh, Simon L. F.11
  • Cross, Gary12
  • Barnett, Joseph12
  • de Lauretis, Angelo13
  • Judge, Eoin P.14
  • Desai, Sujal15
  • Karwoski, Ronald16
  • Ourselin, Sebastien17
  • Renzoni, Elisabetta7
  • And 3 more
  • 1 Department of Respiratory Medicine
  • 2 Centre for Medical Image Computing, and
  • 3 Division of Radiology and
  • 4 St. Antonius ILD Center of Excellence, Department of Pulmonology, and
  • 5 Division of Heart and Lungs, University Medical Center Utrecht, Utrecht, the Netherlands
  • 6 Department of Radiology, St. Antonius Hospital, Nieuwegein, the Netherlands
  • 7 Interstitial Lung Disease Unit and
  • 8 Department of Radiology, Faculty of Medicine, Saga University, Saga City, Japan
  • 9 Imaging Department, Hôpital Cochin, Paris-Descartes University, Paris, France
  • 10 Department of Radiology, University College London, London, United Kingdom
  • 11 Department of Radiology, King’s College Hospital NHS Foundation Trust, London, United Kingdom
  • 12 Department of Radiology, Royal Free Hospital NHS Foundation Trust, London, United Kingdom
  • 13 Division of Pneumology, “Guido Salvini” Hospital, Garbagnate Milanese, Italy
  • 14 Department of Respiratory Medicine, Aintree University Hospital, Liverpool, United Kingdom; and
  • 15 Department of Radiology, Royal Brompton Hospital, Royal Brompton and Harefield NHS Foundation Trust, London, United Kingdom
  • 16 Department of Physiology and Biomedical Engineering, Mayo Clinic Rochester, Rochester, Minnesota
  • 17 Translational Imaging Group, Centre for Medical Image Computing, University College London, London, United Kingdom
Type
Published Article
Journal
American Journal of Respiratory and Critical Care Medicine
Publisher
American Thoracic Society
Publication Date
Sep 15, 2018
Volume
198
Issue
6
Pages
767–776
Identifiers
DOI: 10.1164/rccm.201711-2174OC
PMID: 29684284
PMCID: PMC6222463
Source
PubMed Central
Keywords
License
Unknown

Abstract

Rationale: Quantitative computed tomographic (CT) measures of baseline disease severity might identify patients with idiopathic pulmonary fibrosis (IPF) with an increased mortality risk. We evaluated whether quantitative CT variables could act as a cohort enrichment tool in future IPF drug trials. Objectives: To determine whether computer-derived CT measures, specifically measures of pulmonary vessel–related structures (VRSs), can better predict functional decline and survival in IPF and reduce requisite sample sizes in drug trial populations. Methods: Patients with IPF undergoing volumetric noncontrast CT imaging at the Royal Brompton Hospital, London, and St. Antonius Hospital, Utrecht, were examined to identify pulmonary function measures (including FVC) and visual and computer-derived (CALIPER [Computer-Aided Lung Informatics for Pathology Evaluation and Rating] software) CT features predictive of mortality and FVC decline. The discovery cohort comprised 247 consecutive patients, with validation of results conducted in a separate cohort of 284 patients, all fulfilling drug trial entry criteria. Measurements and Main Results: In the discovery and validation cohorts, CALIPER-derived features, particularly VRS scores, were among the strongest predictors of survival and FVC decline. CALIPER results were accentuated in patients with less extensive disease, outperforming pulmonary function measures. When used as a cohort enrichment tool, a CALIPER VRS score greater than 4.4% of the lung was able to reduce the requisite sample size of an IPF drug trial by 26%. Conclusions: Our study has validated a new quantitative CT measure in patients with IPF fulfilling drug trial entry criteria—the VRS score—that outperformed current gold standard measures of outcome. When used for cohort enrichment in an IPF drug trial setting, VRS threshold scores can reduce a required IPF drug trial population size by 25%, thereby limiting prohibitive trial costs. Importantly, VRS scores identify patients in whom antifibrotic medication prolongs life and reduces FVC decline.

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