Brain volumetric analysis using artificial intelligence software in premanifest huntington’s disease individuals from a Colombian Caribbean population

datacite.rightshttp://purl.org/coar/access_right/c_abf2
dc.contributor.authorRíos Anillo, Margarita Rosa
dc.contributor.authorAhmad, Mostapha
dc.contributor.authorAcosta-Lopez, Johan E.
dc.contributor.authorCervantes-Henríquez, Martha L.
dc.contributor.authorHenao-Castaño, Maria C.
dc.contributor.authorMorales-Moreno, Maria T.
dc.contributor.authorEspitia-Almeida, Fabian
dc.contributor.authorVARGAS MANOTAS, JOSE
dc.contributor.authorSánchez Barros, Cristian Manuel
dc.contributor.authorPineda, David A
dc.contributor.authorSánchez Rojas, Manuel
dc.date.accessioned2024-11-26T17:08:19Z
dc.date.available2024-11-26T17:08:19Z
dc.date.issued2024
dc.description.abstractBackground 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.eng
dc.format.mimetypepdf
dc.identifier.citationRíos-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
dc.identifier.doihttps://doi.org/10.3390/biomedicines12102166
dc.identifier.issn22279059 (Electrónico)
dc.identifier.urihttps://hdl.handle.net/20.500.12442/15983
dc.identifier.urlhttps://www.mdpi.com/2227-9059/12/10/2166
dc.language.isoeng
dc.publisherMDPIspa
dc.publisherFacultad de Ciencias de la Saludspa
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 United Stateseng
dc.rights.accessrightsinfo:eu-repo/semantics/openAccess
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/us/
dc.subject.keywordsArtificial intelligenceeng
dc.subject.keywordsHuntington’s diseaseeng
dc.subject.keywordsMagnetic resonance imagingeng
dc.subject.keywordsNeuroimagingeng
dc.subject.keywordsStructural MRIeng
dc.titleBrain volumetric analysis using artificial intelligence software in premanifest huntington’s disease individuals from a Colombian Caribbean populationeng
dc.type.driverinfo:eu-repo/semantics/article
dc.type.spaArtículo científico
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