Exploring anatomical brain heterogeneity in subjects with mild cognitive impairment

The wide range of clinical manifestations in Mild Cognitive Impairment (MCI) poses a significant challenge. The inherent heterogeneity within MCI emphasizes the importance of a comprehensive characterization of individuals diagnosed with this condition. We identified and characterized MCI subgroups...

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Bibliographic Details
Published in:	2023 19th International Symposium on Medical Information Processing and Analysis (SIPAIM) pp. 1 - 5
Main Authors:	Ochoa, German A. Pabon, Giraldo, Diana L., Romero, Eduardo
Format:	Conference Proceeding
Language:	English
Published:	IEEE 15-11-2023
Subjects:	Alzheimer's Disease Atrophy Computational neuroscience Grey matter Information processing Mild Cognitive Impairment Neuroimaging Neuroscience Quantitative characterization Voxel-based Morphometry Writing
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Summary:	The wide range of clinical manifestations in Mild Cognitive Impairment (MCI) poses a significant challenge. The inherent heterogeneity within MCI emphasizes the importance of a comprehensive characterization of individuals diagnosed with this condition. We identified and characterized MCI subgroups with distinct neuropsychological profiles within the Alzheimer's Disease Neuroimaging Initiative. A total of 194 individuals diagnosed with MCI were partitioned into 7 subgroups using a data-driven clustering approach that incorporated follow-up information. Voxel-based morphometry was then utilized to investigate patterns of gray matter atrophy in each of these subgroups, comparing them against 108 cognitively normal individuals. The analysis disclosed specific brain regions with significant differences. A remarkable relationship between cognitive impairment and the extent of brain atrophy was observed. Increasing cognitive and behavioral abnormalities corresponded to more extensive gray matter atrophy patterns. This study enhances the understanding of neurodegenerative patterns in mild cognitive impairment, providing valuable perspectives for improved characterization and potential interventions in the prodromal stage of Alzheimer's Disease. 1 Data used in preparation of this article were obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. The investigators within the ADNI contributed to the design and implementation of ADNI and provided data but did not participate in analysis or writing of this report.
DOI:	10.1109/SIPAIM56729.2023.10373453