Benjamin Loeh1, Lukas T Brylski1, Daniel von der Beck1, Werner Seeger2, Ekaterina Krauss3, Philippe Bonniaud4, Bruno Crestani5, Carlo Vancheri6, Athol U Wells7, Philipp Markart8, Andreas Breithecker9, Andreas Guenther10. 1. Department of Internal Medicine, Universities of Giessen and Marburg Lung Center, Giessen, Germany. 2. Department of Internal Medicine, Universities of Giessen and Marburg Lung Center, Giessen, Germany; German Center for Lung Research; European IPF Registry and Biobank. 3. Department of Internal Medicine, Universities of Giessen and Marburg Lung Center, Giessen, Germany; European IPF Registry and Biobank. 4. Service de Pneumologie, Centre Hospitalier et Universitaire Dijon-Bourgogne, Université de Bourgogne, Institut National de la Santé et de la Recherche Médicale, Dijon, France; European IPF Registry and Biobank. 5. Service de Pneumologie, Hôpital Bichat, Institut National de la Santé et de la Recherche Médicale, Paris, France; European IPF Registry and Biobank. 6. Department of Clinical and Experimental Medicine, Section of Respiratory Diseases, University of Catania, Regional Center for Interstitial and Rare Lung Diseases, Catania, Italy; European IPF Registry and Biobank. 7. Interstitial Lung Unit, Royal Brompton Hospital, Imperial College London, London, England; European IPF Registry and Biobank. 8. Department of Internal Medicine, Universities of Giessen and Marburg Lung Center, Giessen, Germany; German Center for Lung Research. 9. Department of Radiology, Universities of Giessen and Marburg Lung Center, Giessen, Germany. 10. Department of Internal Medicine, Universities of Giessen and Marburg Lung Center, Giessen, Germany; Lung Clinic Waldhof-Elgershausen, Greifenstein, Germany; German Center for Lung Research; European IPF Registry and Biobank. Electronic address: Andreas.Guenther@innere.med.uni-giessen.de.
Abstract
BACKGROUND: In this study, we retrospectively assessed the relationships among physiologic measurements, survival, and quantitative high-resolution CT (HRCT) scanning indexes in patients with idiopathic pulmonary fibrosis (IPF). METHODS: Seventy patients (48 male; mean [SD] age, 66.4 [9.0] years) with IPF were enrolled in the study. After segmentation of the lungs in thin-section CT scanning with the patient in the supine position at full inspiration, we assessed following parameters: mean lung attenuation (MLA), skewness, kurtosis, peak attenuation, total lung area, inflexion point with slope, and area right of the inflexion point (AROIP). Additionally, FVC, FEV1, total lung capacity, diffusing capacity or transfer factor of the lung for carbon monoxide (Dlco), and 6-min walk distance were analyzed. Univariate and multivariate analysis were used for the prediction of physiologic outcomes by HRCT scanning indexes and then were correlated to survival in a proportional hazards analysis. RESULTS: The strongest correlation was observed between MLA and FEV1, with an r of -0.63. MLA, peak attenuation, slope, attenuation, and AROIP correlated negatively with all physiologic measurements. AROIP was the best predictor of Dlco. Analysis for prediction of mortality showed that AROIP, kurtosis, and FVC were related significantly to survival. Multivariate regression revealed a significant impact of only AROIP (among age, sex, MLA, skewness, kurtosis, FVC, and Dlco) on survival. CONCLUSIONS: These data indicate that HRCT scanning indexes are correlated to physiologic measurements. The newly defined parameter, AROIP, is of additive value for prediction of outcome. TRIAL REGISTRY: ClinicalTrials.gov; No.: NCT02951416; URL: www.clinicaltrials.gov.
BACKGROUND: In this study, we retrospectively assessed the relationships among physiologic measurements, survival, and quantitative high-resolution CT (HRCT) scanning indexes in patients with idiopathic pulmonary fibrosis (IPF). METHODS: Seventy patients (48 male; mean [SD] age, 66.4 [9.0] years) with IPF were enrolled in the study. After segmentation of the lungs in thin-section CT scanning with the patient in the supine position at full inspiration, we assessed following parameters: mean lung attenuation (MLA), skewness, kurtosis, peak attenuation, total lung area, inflexion point with slope, and area right of the inflexion point (AROIP). Additionally, FVC, FEV1, total lung capacity, diffusing capacity or transfer factor of the lung for carbon monoxide (Dlco), and 6-min walk distance were analyzed. Univariate and multivariate analysis were used for the prediction of physiologic outcomes by HRCT scanning indexes and then were correlated to survival in a proportional hazards analysis. RESULTS: The strongest correlation was observed between MLA and FEV1, with an r of -0.63. MLA, peak attenuation, slope, attenuation, and AROIP correlated negatively with all physiologic measurements. AROIP was the best predictor of Dlco. Analysis for prediction of mortality showed that AROIP, kurtosis, and FVC were related significantly to survival. Multivariate regression revealed a significant impact of only AROIP (among age, sex, MLA, skewness, kurtosis, FVC, and Dlco) on survival. CONCLUSIONS: These data indicate that HRCT scanning indexes are correlated to physiologic measurements. The newly defined parameter, AROIP, is of additive value for prediction of outcome. TRIAL REGISTRY: ClinicalTrials.gov; No.: NCT02951416; URL: www.clinicaltrials.gov.
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