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Predicting Outcomes in Idiopathic Pulmonary Fibrosis Using Automated Computed Tomographic Analysis.
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.
Afiliación
  • Jacob J; 1 Department of Respiratory Medicine.
  • Bartholmai BJ; 2 Centre for Medical Image Computing, and.
  • Rajagopalan S; 3 Division of Radiology and.
  • van Moorsel CHM; 3 Division of Radiology and.
  • van Es HW; 4 St. Antonius ILD Center of Excellence, Department of Pulmonology, and.
  • van Beek FT; 5 Division of Heart and Lungs, University Medical Center Utrecht, Utrecht, the Netherlands.
  • Struik MHL; 6 Department of Radiology, St. Antonius Hospital, Nieuwegein, the Netherlands.
  • Kokosi M; 4 St. Antonius ILD Center of Excellence, Department of Pulmonology, and.
  • Egashira R; 4 St. Antonius ILD Center of Excellence, Department of Pulmonology, and.
  • Brun AL; 5 Division of Heart and Lungs, University Medical Center Utrecht, Utrecht, the Netherlands.
  • Nair A; 7 Interstitial Lung Disease Unit and.
  • Walsh SLF; 8 Department of Radiology, Faculty of Medicine, Saga University, Saga City, Japan.
  • Cross G; 9 Imaging Department, Hôpital Cochin, Paris-Descartes University, Paris, France.
  • Barnett J; 10 Department of Radiology, University College London, London, United Kingdom.
  • de Lauretis A; 11 Department of Radiology, King's College Hospital NHS Foundation Trust, London, United Kingdom.
  • Judge EP; 12 Department of Radiology, Royal Free Hospital NHS Foundation Trust, London, United Kingdom.
  • Desai S; 12 Department of Radiology, Royal Free Hospital NHS Foundation Trust, London, United Kingdom.
  • Karwoski R; 13 Division of Pneumology, "Guido Salvini" Hospital, Garbagnate Milanese, Italy.
  • Ourselin S; 14 Department of Respiratory Medicine, Aintree University Hospital, Liverpool, United Kingdom; and.
  • Renzoni E; 15 Department of Radiology, Royal Brompton Hospital, Royal Brompton and Harefield NHS Foundation Trust, London, United Kingdom.
  • Maher TM; 16 Department of Physiology and Biomedical Engineering, Mayo Clinic Rochester, Rochester, Minnesota.
  • Altmann A; 17 Translational Imaging Group, Centre for Medical Image Computing, University College London, London, United Kingdom.
  • Wells AU; 7 Interstitial Lung Disease Unit and.
Am J Respir Crit Care Med ; 198(6): 767-776, 2018 09 15.
Article en En | MEDLINE | ID: mdl-29684284
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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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Tomografía Computarizada por Rayos X / Fibrosis Pulmonar Idiopática Tipo de estudio: Diagnostic_studies / Prognostic_studies / Risk_factors_studies Límite: Aged / Female / Humans / Male / Middle aged Idioma: En Revista: Am J Respir Crit Care Med Asunto de la revista: TERAPIA INTENSIVA Año: 2018 Tipo del documento: Article

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Tomografía Computarizada por Rayos X / Fibrosis Pulmonar Idiopática Tipo de estudio: Diagnostic_studies / Prognostic_studies / Risk_factors_studies Límite: Aged / Female / Humans / Male / Middle aged Idioma: En Revista: Am J Respir Crit Care Med Asunto de la revista: TERAPIA INTENSIVA Año: 2018 Tipo del documento: Article