Multicenter radio-multiomic analysis for predicting breast cancer outcome and unravelling imaging-biological connection.

ABSTRACT: Radiomics offers a noninvasive avenue for predicting clinicopathological factors. However, thorough investigations into a robust breast cancer outcome-predicting model and its biological significance remain limited. This study develops a robust radiomic model for prognosis prediction, and further excavates its biological foundation and transferring prediction performance. We retrospectively collected preoperative dynamic contrast-enhanced MRI data from three distinct breast cancer patient cohorts. In FUSCC cohort (n = 466), Lasso was used to select features correlated with patient prognosis and multivariate Cox regression was utilized to integrate these features and build the radiomic risk model, while multiomic analysis was conducted to investigate the model's biological implications. DUK

SUBMITTER: You C 

PROVIDER: S-EPMC11380684 | biostudies-literature | 2024 Sep

REPOSITORIES: biostudies-literature