Quantitative radiomics and qualitative LI-RADS imaging descriptors for non-invasive assessment of β-catenin mutation status in hepatocellular carcinoma.

Purpose: Gain-of-function mutations in CTNNB1, gene encoding for β-catenin, are observed in 25-30% of hepatocellular carcinomas (HCCs). Recent studies have shown β-catenin activation to have distinct roles in HCC susceptibility to mTOR inhibitors and resistance to immunotherapy. Our goal was to develop and test a computational imaging-based model to non-invasively assess β-catenin activation in HCC, since liver biopsies are often not done due to risk of complications.

Gist processing in digital breast tomosynthesis.

Evans et al. (2016) showed that radiologists can classify the mammograms as normal or abnormal at above-chance levels after a 250-ms exposure. Our study documents a similar gist signal in digital breast tomosynthesis (DBT) images.