MILD COGNITIVE IMPAIRMENT CLASSIFICATION USING A NOVEL FINER-SCALE BRAIN CONNECTOME

Area of Science:

• Neuroscience
• Medical Imaging
• Computational Biology

Background:

• Mild cognitive impairment (MCI) often precedes Alzheimer's disease (AD), a progressive neurodegenerative disorder.
• Brain network degeneration is crucial in MCI and AD development.
• Traditional brain connectomes use coarse-grained regions, potentially missing finer neurodegenerative details.

Purpose of the Study:

• To develop and evaluate a novel, finer-scale brain connectome based on 3-hinge gyri (3HG).
• To compare the predictive performance of the 3HG-based connectome against traditional region-based connectomes for MCI detection.
• To explore the potential of 3HG connectomes in capturing subtle neurodegenerative patterns.

Main Methods:

• Identification and definition of 3-hinge gyri (3HG) as novel brain folding patterns.
• Construction of a 3HG-based finer-scale brain connectome.
• Comparative analysis of 3HG-based and traditional region-based connectomes in predicting MCI versus Normal Controls (NC).

Main Results:

• The 3HG-based brain connectome demonstrated superior performance in predicting MCI.
• This finer-scale approach effectively captured intricate neurodegenerative patterns.
• Results highlight the diagnostic potential of 3HG connectomes.

Conclusions:

• 3-hinge gyrus-based brain connectomes offer a more sensitive method for identifying MCI.
• This novel approach may enhance early detection and understanding of neurodegeneration in AD.
• Finer-scale brain network analysis holds promise for future neurological research.