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
To the Editor:
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].
We performed a sequential database analysis to identify two separate cohorts (n=12 per group) of IPF patients (hereby termed “stable” or “progressive”) from a specialist centre in the UK. The aim was to determine if, between two CT timepoints, FRI could distinguish between patients with more evidence of clinicoradiological disease progression. Inclusion criteria were multidisciplinary team (MDT) diagnosis of IPF, treatment naivety to antifibrotic therapy and two CTs of sufficient quality (determined by an expert thoracic radiologist) ≥3 months apart, with PFT in close association (within 3 months) with each CT. Exclusion criteria were forced expiratory volume in 1 s/FVC <0.7, significant other respiratory pathology including emphysema >15% on CT (as determined by radiologist) or evidence of IPF exacerbation at the time of CT.
Patients were assigned to the stable group if there was a ≤10% absolute FVC decline between CTs and clinicoradiological evidence of disease stability confirmed at repeat MDT. Patients were assigned to the progressive group if there was a ≥10% absolute FVC decline between CTs and evidence of progression, again confirmed by MDT. All CT data were anonymised and underwent FRI analysis (figure 1a). Analysts were blinded to clinical information. Lung and airway volumes were available for total lung, individual lobes, central (first to second generation) and distal (third to seventh generation) airways. Specific airway volume (siVaw) was calculated by dividing the airway volume by lung volume. This allowed for interpatient comparison of airway volume in patients with different lung volumes and intrapatient comparison, given that lung volumes were expected to decline between imaging [4]. The study was approved by the ethics committee at our institution (ref. S02467). Initial statistical analysis was performed using R version 3.6.1 (R Foundation for Statistical Computing, Vienna, Austria); diagrams and between group comparisons using Prism v.8.1.1 (GraphPad, La Jolla, CA, USA).
a) Specific airway volume change between computed tomography scans in an example patient. b) Median change in specific airway volume in the stable and progressive groups. The error bars represent the interquartile range and the bars themselves the median change. c) Correlation between absolute decline in forced vital capacity (FVC) (% predicted) with change in total specific airway volume.
Both groups were matched for both demographics and baseline PFTs. There was no difference (p=0.5) between groups in the timing of CT to PFT; the majority were performed within 2 months of imaging. The interval between imaging varied between 174 and 1059 days (median interval 366 (stable) and 695 (progressive) days, p=0.05). Both groups exhibited decline in FVC between CT scans with a smaller median drop in the stable group (−140 mL) versus the progressive group (−400 mL) (p=0.005). Similar findings were observed in change in transfer factor of the lung for carbon monoxide between groups (stable −7%, progressive −17%; p=0.02). To support the changes in FVC, there was a decline in FRI lung volume in both groups. This was smaller in the stable (−270 mL) versus the progressive (−740 mL) group (p=0.03).
We used random forest analysis and out-of-bag cross-validation to identify FRI parameters that best distinguished between groups (corrected and uncorrected airway/lung volumes and resistance measured overall and in individual lobes; minimum nodes 1, maximum 48). There were seven parameters with a Gini index >0.65 and within these parameters, the siVaw measurements were more predictive at distinguishing between groups than uncorrected airway volumes.
At first CT scan, median airway volumes for stable and progressive groups were similar at 53 and 60 mL respectively, with total siVaw values of 14.9 and 15.6 ml·L−1 (Kruskal–Wallis, p=0.48). There was then a significant increase in the siVaw of the progressive group (median change +6 ml·L−1) compared with the stable group (median change −0.57 mL·L−1) (p=0.0002). This difference was replicated when analysis was confined to upper or lower lobes, or when comparing central or distal airways, with proportionally larger increase in distal airways (figure 1b). Regression analysis showed a weak correlation between siVaw and interval change in FVC (r2=0.39) (figure 1c). Change in specific airway resistance was also measured. There was a larger fall in total resistance in the progressive versus stable group but this was not statistically significant (−0.023 versus −0.001 kPa·s, p=0.14).
Previous work suggested that traction bronchiectasis predicts mortality in IPF [8, 9], and its presence is associated with increased fibroblastic activity when CT and pathological samples are compared [10]. As IPF progresses, the proximal airways widen and distal airways dilate and become increasingly tortuous and cystic, possibly eventually causing honeycombing. This is due in part to tractional forces caused by the collagenisation and contraction of the subpleural and epithelial extracellular matrix, but also due to the direct effect of the disease on the airway [11, 12]. The lungs experience increasing shear and strain stress during ventilation due to the interdependence between nondistensible and rigid airways, vasculature, and parenchyma [13]. At a cellular level, this process of mechanotransduction amplifies fibroblast activity [14]. We have demonstrated a link between increasing airway volume and disease progression, which adds weight to these data.
There are limitations with our study inherent to retrospective data. It was specifically designed to assess differences between two CT scans but did not consider rate of change because we were unable to standardise the timing of CTs. There was no control over the adequacy of inspiration/expiration imaging and although we calculated airway resistances, the lack of standardisation may explain why we did not see significant differences between groups.
Nevertheless, we show for the first time that airway volume can be used to identify CT scans from IPF patients with progressive disease. Several ongoing clinical trials of antifibrotic therapy are focused on progressive fibrotic lung disease in non-IPF disorders [15]; however, it is currently not possible to reliably predict which patients will progress and which will remain stable using baseline data. FRI is a safe, robust mechanism for assessing airway volume and it may be possible that change in siVaw used in conjunction with existing assessment tools is more sensitive to IPF progression than decline in FVC or CT appearances alone. Further evaluation is needed with prospective data in order to answer this question.
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
This article is open access and distributed under the terms of the Creative Commons Attribution Non-Commercial Licence 4.0.