Brain volumetric analysis using artificial intelligence software in premanifest huntington’s disease individuals from a Colombian Caribbean population
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Fecha
2024
Autores
Ríos Anillo, Margarita Rosa
Ahmad, Mostapha
Acosta-Lopez, Johan E.
Cervantes-Henríquez, Martha L.
Henao-Castaño, Maria C.
Morales-Moreno, Maria T.
Espitia-Almeida, Fabian
VARGAS MANOTAS, JOSE
Sánchez Barros, Cristian Manuel
Pineda, David A
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MDPI
Facultad de Ciencias de la Salud
Facultad de Ciencias de la Salud
Resumen
Background and objectives: The premanifest phase of Huntington’s disease (HD) is
characterized by the absence of motor symptoms and exhibits structural changes in imaging that
precede clinical manifestation. This study aimed to analyze volumetric changes identified through
brain magnetic resonance imaging (MRI) processed using artificial intelligence (AI) software in
premanifest HD individuals, focusing on the relationship between CAG triplet expansion and
structural biomarkers. Methods: The study included 36 individuals descending from families
affected by HD in the Department of Atlántico. Sociodemographic data were collected, followed by
peripheral blood sampling to extract genomic DNA for quantifying CAG trinucleotide repeats in the
Huntingtin gene. Brain volumes were evaluated using AI software (Entelai/IMEXHS, v4.3.4) based
on MRI volumetric images. Correlations between brain volumes and variables such as age, sex, and
disease status were determined. All analyses were conducted using SPSS (v. IBM SPSS Statistics 26),
with significance set at p < 0.05. Results: The analysis of brain volumes according to CAG repeat
expansion shows that individuals with ≥40 repeats evidence significant increases in cerebrospinal
fluid (CSF) volume and subcortical structures such as the amygdalae and left caudate nucleus, along
with marked reductions in cerebral white matter, the cerebellum, brainstem, and left pallidum.
In contrast, those with <40 repeats show minimal or moderate volumetric changes, primarily in
white matter and CSF. Conclusions: These findings suggest that CAG expansion selectively impacts
key brain regions, potentially influencing the progression of Huntington’s disease, and that AI in
neuroimaging could identify structural biomarkers long before clinical symptoms appear.
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Ríos-Anillo, M.R.; Ahmad, M.; Acosta-López, J.E.; Cervantes-Henríquez, M.L.; Henao-Castaño,M.C.; Morales-Moreno, M.T.; Espitia-Almeida, F.; Vargas-Manotas, J.; Sánchez-Barros, C.; Pineda, D.A.; et al. Brain Volumetric Analysis Using Artificial Intelligence Software in Premanifest Huntington’s Disease Individuals from a Colombian Caribbean Population. Biomedicines 2024, 12, 2166. https://doi.org/10.3390/biomedicines12102166
