Prediction of survival by texture-based automated quantitative assessment of regional disease patterns on CT in idiopathic pulmonary fibrosis

Sang Min Lee, Joon Beom Seo, Sang Young Oh, Tae Hoon Kim, Jin Woo Song, Sang Min Lee, Namkug Kim
European Radiology, 2017
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Lung Texture

Date Published
2017. 09

This retrospective study investigated whether the baseline extent and 1-year change in regional disease patterns on CT can predict the survival of patients with idiopathic pulmonary fibrosis (IPF). The research incorporated 144 IPF patients, utilizing an in-house texture-based automated system to quantify the extents of five regional disease patterns. The fibrosis score was defined as the sum of the extent of honeycombing and reticular opacity. Through the Cox proportional hazard model, the study determined that age, desaturation, fibrosis score, and interval change in fibrosis score were significant independent predictors of survival. This texture-based, automated CT quantification of fibrosis, which later influenced the development of AVIEW Lung Texture by Coreline Soft, can indeed serve as an independent predictor of survival in IPF patients, offering a valuable tool for predicting disease outcomes.


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