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 inAmerican journal of respiratory and critical care medicine Vol. 198; no. 6; pp. 767 - 776
Main Authors Jacob, Joseph, Bartholmai, Brian J., Rajagopalan, Srinivasan, van Moorsel, Coline H. M., van Es, Hendrik W., van Beek, Frouke T., Struik, Marjolijn H. L., Kokosi, Maria, Egashira, Ryoko, Brun, Anne Laure, Nair, Arjun, Walsh, Simon L. F., Cross, Gary, Barnett, Joseph, de Lauretis, Angelo, Judge, Eoin P., Desai, Sujal, Karwoski, Ronald, Ourselin, Sebastien, Renzoni, Elisabetta, Maher, Toby M., Altmann, Andre, Wells, Athol U.
Format Journal Article
LanguageEnglish
Published United States American Thoracic Society 15.09.2018
Subjects
Online AccessGet full text
ISSN1073-449X
1535-4970
1535-4970
DOI10.1164/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.
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.
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  orcidid: 0000-0002-8054-2293
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  givenname: Brian J.
  surname: Bartholmai
  fullname: Bartholmai, Brian J.
  organization: Division of Radiology and
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  givenname: Srinivasan
  surname: Rajagopalan
  fullname: Rajagopalan, Srinivasan
  organization: Division of Radiology and
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  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
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  givenname: Hendrik W.
  surname: van Es
  fullname: van Es, Hendrik W.
  organization: Department of Radiology, St. Antonius Hospital, Nieuwegein, the Netherlands
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  fullname: van Beek, Frouke T.
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  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
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  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
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  givenname: Sujal
  surname: Desai
  fullname: Desai, Sujal
  organization: Department of Radiology, Royal Brompton Hospital, Royal Brompton and Harefield NHS Foundation Trust, London, United Kingdom
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  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
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  givenname: Andre
  surname: Altmann
  fullname: Altmann, Andre
  organization: Centre for Medical Image Computing, and
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  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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ContentType Journal Article
Copyright Copyright American Thoracic Society Sep 15, 2018
Copyright © 2018 by the American Thoracic Society 2018
Copyright_xml – notice: Copyright American Thoracic Society Sep 15, 2018
– notice: Copyright © 2018 by the American Thoracic Society 2018
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29708398 - Am J Respir Crit Care Med. 2018 Sep 15;198(6):701-702. doi: 10.1164/rccm.201804-0657ED.
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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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