Microvascular MRI and unsupervised clustering yields histology-resembling images in two rat models of glioma.

ABSTRACT: Imaging heterogeneous cancer lesions is a real challenge. For diagnosis, histology often remains the reference, but it is widely acknowledged that biopsies are not reliable. There is thus a strong interest in establishing a link between clinical in vivo imaging and the biologic properties of tissues. In this study, we propose to construct histology-resembling images based on tissue microvascularization, a magnetic resonance imaging (MRI) accessible source of contrast. To integrate the large amount of information collected with microvascular MRI, we combined a manual delineation of a spatial region of interest with an unsupervised, model-based cluster analysis (Mclust). This approach was applied to two rat models of glioma (C6 and F98). Six MRI parameters were mapped: apparent diffusion coe

SUBMITTER: Coquery N 

PROVIDER: S-EPMC4126096 | biostudies-literature | 2014 Aug

REPOSITORIES: biostudies-literature