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Advanced analysis of MR imaging in epilepsy to predict surgery outcome: a machine learning approach

Grant number: 20/00019-7
Support type:Scholarships in Brazil - Post-Doctorate
Effective date (Start): July 01, 2020
Effective date (End): June 30, 2022
Field of knowledge:Health Sciences - Medicine - Medical Clinics
Principal Investigator:Fernando Cendes
Grantee:Raphael Fernandes Casseb
Home Institution: Faculdade de Ciências Médicas (FCM). Universidade Estadual de Campinas (UNICAMP). Campinas , SP, Brazil
Associated research grant:13/07559-3 - BRAINN - The Brazilian Institute of Neuroscience and Neurotechnology, AP.CEPID

Abstract

Surgery outcome prediction based on neuroimaging has great potential and importance in the clinical practice. In this project we propose to use machine learning approaches to 1) perform a variety of functional and structural analysis of EEG-fMRI and other functional and structural MRI datasets, including modern techniques (eg: segmentation of brain structures using multi-atlas approaches, dynamic functional connectivity), to complement the neurologic profile of epilepsy patients; and 2) explore different machine learning approaches to predict surgical outcome (favourable vs. unfavourable) based on the extracted features. We believe that the results may help identify with more confidence patients who can benefit from surgical resection and revisit carefully the cases in which the algorithm advises against it. Moreover, we can potentially isolate characteristics or brain patterns to aid in the presurgical decision, since this is part of machine learning capabilities. (AU)