Predicting Outcomes in Idiopathic Pulmonary Fibrosis Using Automated Computed Tomographic Analysis
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. To determine...
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| Published in | American journal of respiratory and critical care medicine Vol. 198; no. 6; pp. 767 - 776 |
|---|---|
| Main Authors | , , , , , , , , , , , , , , , , , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
United States
American Thoracic Society
15.09.2018
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| Subjects | |
| Online Access | Get full text |
| ISSN | 1073-449X 1535-4970 1535-4970 |
| DOI | 10.1164/rccm.201711-2174OC |
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| Abstract | 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.
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.
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.
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%.
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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| AbstractList | 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.RATIONALEQuantitative 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.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.OBJECTIVESTo 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.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.METHODSPatients 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.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%.MEASUREMENTS AND MAIN RESULTSIn 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%.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.CONCLUSIONSOur 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. [...]in our present study, we evaluated mortality prediction using pulmonary function tests (PFTs), composite indices, and visual and computer-based CT scoring in a discovery cohort of patients with IPF of varying disease severity. [...]for each subject, we estimated a 10% FVC loss within 12 months based on best linear unbiased predictions from the longitudinal mixed model (a minimum of 4 mo of follow-up data was required). [...]we examined patients with a DLCO less than 30% predicted in both the discovery (n = 84) and validation (n = 84) cohorts to evaluate the performance of computer tools in predicting the various study outcome measures in patients with severe disease. [...]our study shows that in IPF, computer analysis of CT imaging, in particular quantitation of pulmonary VRS, can strongly predict survival and likelihood of FVC decline with effects enhanced over functional indices in patients with less extensive disease. 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. 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. 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. 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. 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%. 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. |
| Author | Brun, Anne Laure van Moorsel, Coline H. M. Desai, Sujal van Es, Hendrik W. Struik, Marjolijn H. L. van Beek, Frouke T. Walsh, Simon L. F. Kokosi, Maria Barnett, Joseph Ourselin, Sebastien Bartholmai, Brian J. Rajagopalan, Srinivasan Nair, Arjun Karwoski, Ronald de Lauretis, Angelo Maher, Toby M. Renzoni, Elisabetta Wells, Athol U. Egashira, Ryoko Jacob, Joseph Cross, Gary Altmann, Andre Judge, Eoin P. |
| Author_xml | – sequence: 1 givenname: Joseph orcidid: 0000-0002-8054-2293 surname: Jacob fullname: Jacob, Joseph organization: Department of Respiratory Medicine, Centre for Medical Image Computing, and – sequence: 2 givenname: Brian J. surname: Bartholmai fullname: Bartholmai, Brian J. organization: Division of Radiology and – sequence: 3 givenname: Srinivasan surname: Rajagopalan fullname: Rajagopalan, Srinivasan organization: Division of Radiology and – sequence: 4 givenname: Coline H. M. surname: van Moorsel fullname: van Moorsel, Coline H. M. organization: St. Antonius ILD Center of Excellence, Department of Pulmonology, and, Division of Heart and Lungs, University Medical Center Utrecht, Utrecht, the Netherlands – sequence: 5 givenname: Hendrik W. surname: van Es fullname: van Es, Hendrik W. organization: Department of Radiology, St. Antonius Hospital, Nieuwegein, the Netherlands – sequence: 6 givenname: Frouke T. surname: van Beek fullname: van Beek, Frouke T. organization: St. Antonius ILD Center of Excellence, Department of Pulmonology, and – sequence: 7 givenname: Marjolijn H. L. surname: Struik fullname: Struik, Marjolijn H. L. organization: St. Antonius ILD Center of Excellence, Department of Pulmonology, and, Division of Heart and Lungs, University Medical Center Utrecht, Utrecht, the Netherlands – sequence: 8 givenname: Maria surname: Kokosi fullname: Kokosi, Maria organization: Interstitial Lung Disease Unit and – sequence: 9 givenname: Ryoko surname: Egashira fullname: Egashira, Ryoko organization: Department of Radiology, Faculty of Medicine, Saga University, Saga City, Japan – sequence: 10 givenname: Anne Laure surname: Brun fullname: Brun, Anne Laure organization: Imaging Department, Hôpital Cochin, Paris-Descartes University, Paris, France – sequence: 11 givenname: Arjun surname: Nair fullname: Nair, Arjun organization: Department of Radiology, University College London, London, United Kingdom – sequence: 12 givenname: Simon L. F. surname: Walsh fullname: Walsh, Simon L. F. organization: Department of Radiology, King’s College Hospital NHS Foundation Trust, London, United Kingdom – sequence: 13 givenname: Gary surname: Cross fullname: Cross, Gary organization: Department of Radiology, Royal Free Hospital NHS Foundation Trust, London, United Kingdom – sequence: 14 givenname: Joseph surname: Barnett fullname: Barnett, Joseph organization: Department of Radiology, Royal Free Hospital NHS Foundation Trust, London, United Kingdom – sequence: 15 givenname: Angelo surname: de Lauretis fullname: de Lauretis, Angelo organization: Division of Pneumology, “Guido Salvini” Hospital, Garbagnate Milanese, Italy – sequence: 16 givenname: Eoin P. surname: Judge fullname: Judge, Eoin P. organization: Department of Respiratory Medicine, Aintree University Hospital, Liverpool, United Kingdom; and – sequence: 17 givenname: Sujal surname: Desai fullname: Desai, Sujal organization: Department of Radiology, Royal Brompton Hospital, Royal Brompton and Harefield NHS Foundation Trust, London, United Kingdom – sequence: 18 givenname: Ronald surname: Karwoski fullname: Karwoski, Ronald organization: Department of Physiology and Biomedical Engineering, Mayo Clinic Rochester, Rochester, Minnesota – sequence: 19 givenname: Sebastien surname: Ourselin fullname: Ourselin, Sebastien organization: Translational Imaging Group, Centre for Medical Image Computing, University College London, London, United Kingdom – sequence: 20 givenname: Elisabetta surname: Renzoni fullname: Renzoni, Elisabetta organization: Interstitial Lung Disease Unit and – sequence: 21 givenname: Toby M. surname: Maher fullname: Maher, Toby M. organization: Interstitial Lung Disease Unit and – sequence: 22 givenname: Andre surname: Altmann fullname: Altmann, Andre organization: Centre for Medical Image Computing, and – sequence: 23 givenname: Athol U. surname: Wells fullname: Wells, Athol U. organization: Interstitial Lung Disease Unit and |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/29684284$$D View this record in MEDLINE/PubMed |
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| Copyright | Copyright American Thoracic Society Sep 15, 2018 Copyright © 2018 by the American Thoracic Society 2018 |
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| Snippet | Quantitative computed tomographic (CT) measures of baseline disease severity might identify patients with idiopathic pulmonary fibrosis (IPF) with an increased... [...]in our present study, we evaluated mortality prediction using pulmonary function tests (PFTs), composite indices, and visual and computer-based CT scoring... Rationale: Quantitative computed tomographic (CT) measures of baseline disease severity might identify patients with idiopathic pulmonary fibrosis (IPF) with... |
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| SubjectTerms | Aged Automation Biomarkers Female Humans Idiopathic Pulmonary Fibrosis - diagnosis Idiopathic Pulmonary Fibrosis - diagnostic imaging Idiopathic Pulmonary Fibrosis - mortality Idiopathic Pulmonary Fibrosis - physiopathology Informatics Lung diseases Male Medical imaging Medical prognosis Middle Aged Mortality Original Pathology Patients Prognosis Pulmonary fibrosis Respiratory Function Tests Survival analysis Tomography, X-Ray Computed - methods Vital Capacity |
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| Title | Predicting Outcomes in Idiopathic Pulmonary Fibrosis Using Automated Computed Tomographic Analysis |
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