Quantitative CT analysis using functional imaging is superior in describing disease progression in idiopathic pulmonary fibrosis compared to forced vital capacity

J. Clukers, M. Lanclus, B. Mignot, C. Van Holsbeke, J. Roseman, S. Porter, E. Gorina, E. Kouchakji ,K. E. Lipson, W. De Backer and J. De Backer

Respiratory Research (2018) 19:213


Background: Idiopathic pulmonary fibrosis (IPF) is chronic fibrosing pneumonia with an unpredictable naturaldisease history. Functional respiratory imaging (FRI) has potential to better characterize this disease. The aim of thisstudy was to identify FRI parameters, which predict FVC decline in patients with IPF.Methods:An IPF-cohort (treated with pamrevlumab for 48 weeks) was retrospectively studied using FRI. Serial CT’swere compared from 66 subjects. Post-hoc analysis was performed using FRI, FVC and mixed effects models.

Results: Lung volumes, determined by FRI, correlated with FVC (lower lung volumes with lower FVC) (R2= 0.61,p< 0.001). A negative correlation was observed between specific image based airway radius (siRADaw) at total lungcapacity (TLC) and FVC (R2= 0.18,p< 0.001). Changes in FVC correlated significantly with changes in lung volumes(R2= 0.18,p< 0.001) and siRADaw (R2= 0.15,p= 0.002) at week 24 and 48, with siRADaw being more sensitive tochange than FVC. Loss in lobe volumes (R2= 0.33,p< 0.001), increasing fibrotic tissue (R2= 0.33,p< 0.001) andairway radius (R2= 0.28,p< 0.001) at TLC correlated with changes in FVC but these changes already occur in thelower lobes when FVC is still considered normal.

Conclusion: This study indicates that FRI is a superior tool than FVC in capturing of early and clinically relevant, disease progression in a regional manner.
Keywords: Functional respiratory imaging is superior in describing the disease in IPF

© The Author(s). 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver(http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article unless otherwise stated.

Categorised in: / November 1, 2018 3:20 pm / Published by