Data-driven mapping of hypoxia-related tumor heterogeneity using DCE-MRI and OE-MRI.

ABSTRACT:

Purpose

Previous work has shown that combining dynamic contrast-enhanced (DCE)-MRI and oxygen-enhanced (OE)-MRI binary enhancement maps can identify tumor hypoxia. The current work proposes a novel, data-driven method for mapping tissue oxygenation and perfusion heterogeneity, based on clustering DCE/OE-MRI data.

Methods

DCE-MRI and OE-MRI were performed on nine U87 (glioblastoma) and seven Calu6 (non-small cell lung cancer) murine xenograft tumors. Area under the curve and principal component analysis features were calculated and clustered separately using Gaussian mixture modelling. Evaluation metrics were calculated to determine the optimum feature set and cluster number. Outputs were quantitatively compared with a previous non data-driven approach.

Results

The opt

SUBMITTER: Featherstone AK 

PROVIDER: S-EPMC5836865 | biostudies-literature | 2018 Apr

REPOSITORIES: biostudies-literature