Isocitrate dehydrogenase (IDH) and telomerase reverse transcriptase promoter (TERTp) mutations highly affect the clinical outcome in gliomas. The aim of this study was to identify IDH and TERTp mutations in glioma patients using machine learning approaches on relative cerebral blood volume (rCBV) maps obtained from dynamic susceptibility contrast MRI (DSC-MRI). The highest classification accuracy was 87.2% (sensitivity = 85.7%, specificity = 88.9%) for the IDH subgroup, 81.8% accuracy (sensitivity = 77.5%, specificity = 86.4%) was obtained for classifying the TERTp subgroup. Additionally, a classification accuracy of 89.6% (sensitivity = 88.3%, specificity = 91.2%) was obtained for identifying the TERTp-only gliomas.
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