Abstract
Introduction Pulmonary sarcoidosis is a rare heterogeneous lung disease of unknown aetiology, with limited treatment options. Phenotyping relies on clinical testing including visual scoring of chest radiographs. Objective radiomic measures from high-resolution computed tomography (HRCT) may provide additional information to assess disease status. As the first radiomics analysis in sarcoidosis, we investigate the potential of radiomic measures as biomarkers for sarcoidosis, by assessing 1) differences in HRCT between sarcoidosis subjects and healthy controls, 2) associations between radiomic measures and spirometry, and 3) trends between Scadding stages.
Methods Radiomic features were computed on HRCT in three anatomical planes. Linear regression compared global radiomic features between sarcoidosis subjects (n=73) and healthy controls (n=78), and identified associations with spirometry. Spatial differences in associations across the lung were investigated using functional data analysis. A subanalysis compared radiomic features between Scadding stages.
Results Global radiomic measures differed significantly between sarcoidosis subjects and controls (p<0.001 for skewness, kurtosis, fractal dimension and Geary's C), with differences in spatial radiomics most apparent in superior and lateral regions. In sarcoidosis subjects, there were significant associations between radiomic measures and spirometry, with a large association found between Geary's C and forced vital capacity (FVC) (p=0.008). Global radiomic measures differed significantly between Scadding stages (p<0.032), albeit nonlinearly, with stage IV having more extreme radiomic values. Radiomics explained 71.1% of the variability in FVC compared with 51.4% by Scadding staging alone.
Conclusions Radiomic HRCT measures objectively differentiate disease abnormalities, associate with lung function and identify trends in Scadding stage, showing promise as quantitative biomarkers for pulmonary sarcoidosis.
Abstract
Radiomic measures identify pulmonary parenchymal abnormalities in sarcoidosis and are highly associated with lung function, suggesting that radiomics could enhance visual reads and result in improved patient profiling, disease staging and monitoring. http://bit.ly/2HMLaKm
Footnotes
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Conflict of interest: S.M. Ryan has nothing to disclose.
Conflict of interest: T.E. Fingerlin has nothing to disclose.
Conflict of interest: M. Mroz has nothing to disclose.
Conflict of interest: B. Barkes has nothing to disclose.
Conflict of interest: N. Hamzeh has nothing to disclose.
Conflict of interest: L.A. Maier reports grants from NIH/NHLBI during the conduct of the study, and grants from NIH/NHLBI, aTYR and Mallinckrodt ARD, Inc., outside the submitted work.
Conflict of interest: N.E. Carlson has nothing to disclose.
Support statement: Funding was provided from the US Dept of Health and Human Services, National Institute of Health, National Heart, Lung, and Blood Institute: R01 HL089856, R01 HL114587, R01 HL142049, U01 HL112695 and U01 HL112707. Funding information for this article has been deposited with the Crossref Funder Registry.
An earlier version of this manuscript was posted to ArXiv in June 2018 (arXiv:1806.10281) (https://arxiv.org/abs/1806.10281). Compared with that version, the present manuscript has substantial improvements to its methods, results and presentation.
- Received February 21, 2019.
- Accepted May 24, 2019.
- Copyright ©ERS 2019