Chest high resolution computed tomography (HRCT) is increasingly used in clinical practice for sarcoidosis. Visual assessment (VAS) remains standard even with its high inter- and intra-rater variation. Radiomics may be a less variable assessment. We developed radiomic profiles of HRCT and mapped them to radiologic, functional, and patient reported outcomes. Radiomics were calculated on HRCT for both lungs from sarcoidosis cases enrolled in the Genomic Research in Alpha-1 Antitrypsin Deficiency and Sarcoidosis (GRADS) study ( N = 320). Cases were clustered using radiomics profiles via robust and sparse K-means. Differences in VAS by cluster were identified using chi-squared tests. Linear regression investigated how pulmonary function tests (PFT) and patient reported outcomes (PRO) differed between clusters with and without adjustment for other radiologic quantification. Sensitivity analyses were used for validation. Clustering produced four patient groups that were associated with, but did not mimic, Scadding stage and Oberstein score ( p < 0.001). One cluster had markedly few abnormalities. Another cluster had consistently more abnormalities and fibrosis. Clusters explained 10–15% of PFT variation and significantly predicted PFT even after accounting for other radiologic findings ( p < 0.001). Associations with PRO were less consistent. These findings provide early-stage evidence that radiomics may be a useful component in identifying disease phenotypes.
Carlson et al. (Wed,) studied this question.
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