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Evaluation and Characterization of Brain Structural Changes in Patients with Stable and Progressive Mild Cognitive Impairment: A Magnetic Resonance Imaging Study

Grant number: 24/02491-6
Support Opportunities:Scholarships in Brazil - Scientific Initiation
Effective date (Start): May 01, 2024
Effective date (End): April 30, 2025
Field of knowledge:Physical Sciences and Mathematics - Computer Science - Computing Methodologies and Techniques
Principal Investigator:Ricardo José Ferrari
Grantee:Leo Rodrigues Aoki
Host Institution: Centro de Ciências Exatas e de Tecnologia (CCET). Universidade Federal de São Carlos (UFSCAR). São Carlos , SP, Brazil

Abstract

The study of brain structural changes in patients with Stable (sMCI) and Progressive Mild Cognitive Impairment (pMCI) has garnered significant attention from the scientific community, given the global challenge posed by Alzheimer's disease (AD) and other neurodegenerative conditions. Early detection of these diseases, particularly at the MCI stage, is crucial for implementing effective therapeutic interventions and slowing symptom progression, especially in the case of AD. In this context, the proposed research aims to deepen the understanding of structural brain changes in patients with sMCI and pMCI, utilizing magnetic resonance imaging (MRI) and advanced techniques in digital image processing and machine learning. To achieve this goal, MRI images will undergo initial preprocessing to optimize their quality and consistency. Subsequently, a parceling technique via anatomical atlases will be employed to segment the images into regions commonly affected by AD. Finally, the NeuroNet technique will be utilized for segmentation of gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF). Cortical thickness of the segmented brain regions will be obtained using the DiReCT technique. Evaluation of the extracted image attributes will allow for a detailed analysis of structural changes in different brain areas, providing valuable insights into the specific patterns associated with sMCI and pMCI.

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