Idiopathic pulmonary fibrosis: The association between the adaptive multiple features method and fibrosis outcomes

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Abstract

Rationale: Adaptive multiple features method(AMFM)lung texture analysis software recognizes high-resolution computed tomography (HRCT) patterns. Objectives: To evaluate AMFM and visual quantification of HRCT patterns and their relationship with disease progression in idiopathic pulmonary fibrosis. Methods: Patients with idiopathic pulmonary fibrosis in a clinical trial of prednisone, azathioprine, and N-acetylcysteine underwent HRCT at study start and finish. Proportion of lung occupied by ground glass, ground glass-reticular (GGR), honeycombing, emphysema, and normal lung densities were measured by AMFM and three radiologists, documenting baseline disease extent and postbaseline change. Disease progression includes composite mortality, hospitalization, and 10% FVC decline. Measurements and Main Results: Agreement between visual and AMFMmeasurements was moderate for GGR(Pearson's correlation r = 0.60, P,0.0001; mean difference =20.03 with 95% limits of agreement of 20.19 to 0.14). Baseline extent of GGR was independently associated with disease progression when adjusting for baseline Gender-Age-Physiology stage and smoking status (hazard ratio per 10% visual GGR increase = 1.98, 95% confidence interval [CI] = 1.20-3.28, P = 0.008; and hazard ratio per 10%AMFM GGR increase = 1.36, 95% CI = 1.01-1.84, P = 0.04). Postbaseline visual andAMFMGGRtrajectories were correlated with postbaseline FVC trajectory (r =20.30, 95% CI =20.46 to 20.11, P = 0.002; and r =20.25, 95% CI =20.42 to 20.06, P = 0.01, respectively). Conclusions: More extensive baseline visual and AMFM fibrosis (as measured by GGR densities) is independently associated with elevated hazard for disease progression. Postbaseline change in AMFM-measured and visually measured GGR densities are modestly correlated with change in FVC. AMFM-measured fibrosis is an automated adjunct to existing prognostic markers and may allow for study enrichment with subjects at increased disease progression risk.

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Salisbury, M. L., Lynch, D. A., Van Beek, E. J. R., Kazerooni, E. A., Guo, J., Xia, M., … Flaherty, K. R. (2017). Idiopathic pulmonary fibrosis: The association between the adaptive multiple features method and fibrosis outcomes. American Journal of Respiratory and Critical Care Medicine, 195(7), 921–929. https://doi.org/10.1164/rccm.201607-1385OC

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