CT quantification of the heterogeneity of fibrosis boundaries in idiopathic pulmonary fibrosis

Abstract

Objectives To quantify the heterogeneity of fibrosis boundaries in idiopathic pulmonary fibrosis (IPF) using the Gaussian curvature analysis for evaluating disease severity and predicting survival. Methods We retrospectively included 104 IPF patients and 52 controls who underwent baseline chest CT scans. Normal lungs below − 500 HU were segmented, and the boundary was three-dimensionally reconstructed using in-house software. Gaussian curvature analysis provided histogram features on the heterogeneity of the fibrosis boundary. We analyzed the correlations between histogram features and the gender-age-physiology (GAP) and CT fibrosis scores. We built a regression model to predict diffusing capacity of carbon monoxide (DLCO) using the histogram features and calculated the modified GAP (mGAP) score by replacing DLCO with the predicted DLCO. The performances of the GAP, CT-GAP, and mGAP scores were compared using 100 repeated random-split sets. Results Patients with moderate-to-severe IPF had more numerous Gaussian curvatures at the fibrosis boundary, lower uniformity, and lower 10th to 30th percentiles of Gaussian curvature than controls or patients with mild IPF (all p < 0.0033). The 20th percentile was most significantly correlated with the GAP score (r = − 0.357; p < 0.001) and the CT fibrosis score (r = − 0.343; p = 0.001). More numerous Gaussian curvatures, higher entropy, lower uniformity, and 10th to 30th percentiles (p < 0.001-0.041) were associated with mortality. The mGAP score was comparable to the GAP and CT-GAP scores for survival prediction (mean C-indices, 0.76 vs. 0.79 vs. 0.77, respectively). Conclusions Gaussian curvatures of fibrosis boundaries became more heterogeneous as the disease progressed, and heterogeneity was negatively associated with survival in IPF. Key Points• Gaussian curvature of the fibrotic lung boundary was more heterogeneous in patients with moderate-to-severe IPF than those with mild IPF or normal controls. • The 20th percentile of the Gaussian curvature of the fibrosis boundary was linearly correlated with the GAP score and the CT fibrosis score. • A modified GAP score that replaced the diffusing capacity of carbon monoxide with a composite measure using histogram features of the Gaussian curvature of the fibrosis boundary showed a comparable ability to predict survival to both the GAP and the CT-GAP score.

Idiopathic pulmonary fibrosis: Current and future treatment

“… 28 , 29 The most typical radiological pattern is UIP. 30 Extent of fibrosis on CT can be assessed visually or quantified more objectively using computer algorithms. 31 , 32 High‐resolution CT often shows honeycomb changes, traction bronchiectasis, and a reticular pattern that is predominantly in the periphery of the lower lobes.…”

Quantitative computed tomography and machine learning: recent data in fibrotic interstitial lung disease and potential role in pulmonary sarcoidosis

“…Park et al . [21 ▪ ] retrospectively quantified heterogeneity of fibrosis boundaries on CT in IPF patients. Gaussian curvature analysis was used to provide histograms capturing fibrosis boundary heterogeneity, modelled against the diffusing capacity of carbon monoxide (DLco) and integrated into the GAP model, replacing measured DLco.…”