Effects of interobserver and interdisciplinary segmentation variabilities on CT-based radiomics for pancreatic cancer.

ABSTRACT: Radiomics is a method to mine large numbers of quantitative imaging features and develop predictive models. It has shown exciting promise for improved cancer decision support from early detection to personalized precision treatment, and therefore offers a desirable new direction for pancreatic cancer where the mortality remains high despite the current care and intense research. For radiomics, interobserver segmentation variability and its effect on radiomic feature stability is a crucial consideration. While investigations have been reported for high-contrast cancer sites such as lung cancer, no studies to date have investigated it on CT-based radiomics for pancreatic cancer. With three radiation oncology observers and three radiology observers independently contouring on the contrast CT

SUBMITTER: Wong J 

PROVIDER: S-EPMC8357939 | biostudies-literature | 2021 Aug

REPOSITORIES: biostudies-literature