The project aims at enhancing performance metrics and prospectively validating a radiogenomics model based on ovarian US images for predicting germline breast cancer susceptibility gene 1 and/or 2 (BRCA) status in women with healthy ovaries. The project is divided in two operational phases: Model development phase (ambispective) AIM 1: To define and implement a proper and fine-tuned image preprocessing pipeline on the existing dataset; AIM 2: To enlarge dataset size with new real images from different centers and apply data augmentation techniques, deep neural network models combined with the aforementioned handcrafted imaging features from radiomics analysis; Implementation and validation phase (prospective) AIM 3: To further cross-validate the predictive model on US images acquired prospectively in an observational multicenter study.
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Radiogenomics model for predicting germline breast cancer.
Timeframe: 96 months