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.
How to access this content:
For one year after publication, abstracts and videos are only open to registrants of this annual meeting. Registrants should use their existing login information. Non-registrant access can be purchased via the ISMRM E-Library.
After one year, current ISMRM & ISMRT members get free access to both the abstracts and videos. Non-members and non-registrants must purchase access via the ISMRM E-Library.
After two years, the meeting proceedings (abstracts) are opened to the public and require no login information. Videos remain behind password for access by members, registrants and E-Library customers.
Keywords