Keywords: Tumors (Post-Treatment), Treatment Response
Motivation: Non-invasively distinguishing recurrent tumor (rTumor) from treatment-induced effects (TxE) is an ongoing challenge for treating glioma.
Goal(s): We build off previous work to spatially map probabilities of rTumor and TxE by expanding the maps beyond the visually identifiable lesion, include robust evaluation criteria, and associate prediction maps to survival.
Approach: We predict abnormal brain regions to generate maps of TxE without relying exclusively on the T2-lesion, and associate spatial prediction features to survival.
Results: The model discriminates TxE from rTumor with an AUROC=0.74 and abnormal brain with 0.99, which enables expansion of inference. Spatial prediction features were significantly (p<.05) associated with survival.
Impact: Spatial maps of recurrent glioma and treatment-effects that account for normal brain demonstrate reliable performance for mapping glioma beyond the visually identifiable lesion with anatomical MRI. Spatial prediction features are associated with survival and may enhance treatment decisions.
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