Keywords: Diagnosis/Prediction, Radiomics
Motivation: Prostate cancer is the leading male malignancy in South Korea, with BRCA1/2 mutations critical for PARP inhibitor use in personalized therapy.
Goal(s): Build a model to predict BRCA mutations using MRI, aiming to reduce NGS costs and improve personalized treatment.
Approach: In a retrospective study of 204 patients, BRCA mutations were identified with NGS. T2-weighted MRIs were segmented, and 1,422 radiomic features extracted. Feature selection included ICC, LASSO, and classifiers (KNN, RF, GNB) were applied.
Results: The KNN model achieved AUROCs of 1.00 (train) and 0.80 (test) with TNR of 0.84. RF and GNB had TNRs of 0.86 and 1.00 for negatives.
Impact: MRI-based radiomics models offer a non-invasive, cost-effective alternative to NGS, potentially reducing the need for NGS testing. These models could aid in drug selection and prognosis prediction, enhancing personalized treatment strategies.
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