Article
Machine learning-based prediction of microsatellite instability and high tumor mutation burden from contrast-enhanced computed tomography in endometrial cancers.
Scientific reports - 20 Oct 2020
Veeraraghavan Harini, Friedman Claire F, DeLair Deborah F, Ninčević Josip, Himoto Yuki, Bruni Silvio G, Cappello Giovanni, Petkovska Iva, Nougaret Stephanie, Nikolovski Ines, Zehir Ahmet, Abu-Rustum Nadeem R, Aghajanian Carol, Zamarin Dmitriy, Cadoo Karen A, Diaz Luis A, Leitao Mario M, Makker Vicky, Soslow Robert A, Mueller Jennifer J, Weigelt Britta, Lakhman Yulia
Abstract excerpt
To evaluate whether radiomic features from contrast-enhanced computed tomography (CE-CT) can identify DNA mismatch repair deficient (MMR-D) and/or tumor mutational burden-high (TMB-H) endometrial cancers (ECs). Patients who underwent targeted massively parallel sequencing of primary ECs between 2014 and 2018 and preoperative CE-CT were included (n = 150). Molecular subtypes of EC were assigned using DNA...
Read the complete abstract on PubMedTopics
Share this publication in a Topic to start or enrich a Post.