Meeting Banner
Abstract #1532

Co-registration of MRI and histological habitats in pre-clinical tumor models

Bruna Victorasso Jardim-Perassi1, Suning Huang1, William Dominguez-Viqueira1, Epifanio Ruiz1, Mikalai Budzevich1, Jan Poleszczuk2, Marilyn Bui3, Robert Gillies1, and Gary Martinez1

1Cancer Imaging and Metabolism, Moffitt Cancer Center, Tampa, FL, United States, 2Nalecz Institute of Biocybernetics and Biomedical Engineering, Warsaw, Poland, 3Pathology Anatomic, Moffitt Cancer Center, Tampa, FL, United States

Tumor heterogeneity, may give insight into natural selection through detection of tumor sub-regions, referred as imaging habitats. We used statistical clustering of multiple pixels based on multiple MRI parameter maps to identify tumor habitats in pre-clinical models of sarcoma and breast cancer using T2, T2*, ADC and three model free parameter maps determined from dynamic contrast enhanced images. MRI-derived habitat maps were determined by clustering multidimensional voxels using a Gaussian mixture model. 3D-printed tumor molds were used to successfully co-register MR imaging slices with their histological habitat-counterparts. Four distinct tumor habitats were detected by MRI and biologically corroborated by histology.

This abstract and the presentation materials are available to members only; a login is required.

Join Here