Extract
Idiopathic pulmonary fibrosis (IPF) is progressive condition with unclear aetiology and patients decline with heterogeneous trajectories. Whilst antifibrotic therapy can slow disease progression [1, 2], the ability to determine an individual's disease course is limited to measurement of pulmonary function (pulmonary function testing (PFT)) and visual assessment of computed tomography (CT) scans, both of which have limitations. PFT is affected by patient technique and operator experience [3]; CT scans rely on radiologist expertise to correctly interpret disease stability/progression and are subject to interobserver variability [4]. Recently, automated analysis of blood vessel volume has been shown to predict disease progression [5]. We hypothesised that a novel measurement of airway volume using functional respiratory imaging (FRI) could identify CT scans with more progressive disease. FRI is a semiautomated technique for segmenting thoracic CT anatomy, including airways up to the seventh generation, combined with flow simulation to derive volume and resistance measurements [6]. Images are usually compared at full inspiration (total lung capacity (TLC)) and functional residual capacity (passive expiration) for resistance calculations. However, imaging at TLC alone is sufficient to measure lung and airway volume. The robustness of FRI has been validated in obstructive airway disease, and in IPF has been explored in a small number of patients as part of a phase IIa trial of pamrevlumab [6] and phase IIa trial for the autotaxin inhibitor GLPG1690. Whilst this second study was not powered to show a change in forced vital capacity (FVC), differences were seen in airway volume and resistance in those treated with the medication compared with placebo, but the placebo group was limited with only three patients [7].
Abstract
Airways tell a tale: measuring change in airway volume using functional respiratory imaging can differentiate between stable and progressive idiopathic pulmonary fibrosis on CT scans #imagebiomarkers #ipf http://bit.ly/2M8KVLl
Acknowledgements
Thanks to Piero Ricchiuto (Cambridge, UK) for assistance with statistical analyses.
Footnotes
Conflict of interest: T. McLellan has received travel support to attend the 2019 ERS International Congress. His salary as a research fellow is paid by Royal Papworth but the grant originally came from Roche.
Conflict of interest: P.M. George reports personal fees and nonfinancial support from Roche and Boehringer Ingleheim, and personal fees from Teva, outside the submitted work.
Conflict of interest: P. Ford is an employee of Galapagos.
Conflict of interest: J. de Backer is an employee of Fluidda NV.
Conflict of interest: C. Van Holsbeke is an employee of Fluidda NV.
Conflict of interest: B. Mignot is an employee of Fluidda NV.
Conflict of interest: N.J. Screaton has nothing to disclose.
Conflict of interest: A. Ruggiero reports a leadership position at Qureight Ltd. Qureight Ltd received financial support from Galapagos N.V.
Conflict of interest: M. Thillai reports a leadership position at Qureight Ltd. Qureight Ltd received financial support from Galapagos NV.
- Received October 22, 2019.
- Accepted December 11, 2019.
- Copyright ©ERS 2020
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