NEIM-03 A GRADUAL INTEGRATION MODEL BASED ON MRI TO PREDICT MOLECULAR PROFILES IN PATIENTS WITH GLIOMA
نویسندگان
چکیده
Abstract Glioma is the most common primary brain tumor. Molecular profiles, including IDH mutation, 1p/19q co-deletion, and MGMT promoter methylation, are highly correlated with prognosis clinical decision-making of glioma. To predict molecular profiles from rough segmentation MRI, we developed validated a gradual integration model. We proposed multi-task pseudo-3D model based on segmented multiparametric MRI to profiles. In this model, convolution along depth axis was performed between blocks. A total 750 patients glioma were retrospectively enrolled Sun Yatsen University Cancer Center(n=576) The Imaging Archive(n=167) validate performance framework. local dataset tested an independent external (TCIA) test set. For IDH, 1p/19q, predictions TCIA set, fusion achieves AUCs 0.87, 0.80, 0.71, respectively, outperforming both input or output models 2D models. conclude, our demonstrated potential pre-treatment MRI. Gradual may be reliable method design 3D medical imaging
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ژورنال
عنوان ژورنال: Neuro-oncology advances
سال: 2023
ISSN: ['2632-2498']
DOI: https://doi.org/10.1093/noajnl/vdad070.056