Deep Learning-based Fibrosis Extent on CT Predicts Outcome of Fibrosing Interstitial Lung Disease Independent of Visually Assessed CT Pattern.

Andrea S OhDavid A LynchJeffrey J SwigrisDavid BaraghoshiDebra S DyerValerie A HaleTilman L KoelschCristina MarrocchioKatherine N ParkerShawn TeagueKevin R FlahertyStephen M Humphriesnull null

Published in: Annals of the American Thoracic Society (2023)

Extent of lung fibrosis by quantitative CT is a strong predictor of physiologic progression and survival, independent of visually assessed CT pattern.

Keyphrases

interstitial lung disease
image quality
dual energy
computed tomography
contrast enhanced
systemic sclerosis
deep learning
positron emission tomography
rheumatoid arthritis
magnetic resonance imaging
high resolution
free survival