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J Alzheimers Dis ; 99(1): 177-190, 2024.
Artículo en Inglés | MEDLINE | ID: mdl-38640154

RESUMEN

Background: Being able to differentiate mild cognitive impairment (MCI) patients who would eventually convert (MCIc) to Alzheimer's disease (AD) from those who would not (MCInc) is a key challenge for prognosis. Objective: This study aimed to investigate the ability of sulcal morphometry to predict MCI progression to AD, dedicating special attention to an accurate identification of sulci. Methods: Twenty-five AD patients, thirty-seven MCI and twenty-five healthy controls (HC) underwent a brain-MR protocol (1.5T scanner) including a high-resolution T1-weighted sequence. MCI patients underwent a neuropsychological assessment at baseline and were clinically re-evaluated after a mean of 2.3 years. At follow-up, 12 MCI were classified as MCInc and 25 as MCIc. Sulcal morphometry was investigated using the BrainVISA framework. Consistency of sulci across subjects was ensured by visual inspection and manual correction of the automatic labelling in each subject. Sulcal surface, depth, length, and width were retrieved from 106 sulci. Features were compared across groups and their classification accuracy in predicting MCI conversion was tested. Potential relationships between sulcal features and cognitive scores were explored using Spearman's correlation. Results: The width of sulci in the temporo-occipital region strongly differentiated between each pair of groups. Comparing MCIc and MCInc, the width of several sulci in the bilateral temporo-occipital and left frontal areas was significantly altered. Higher width of frontal sulci was associated with worse performances in short-term verbal memory and phonemic fluency. Conclusions: Sulcal morphometry emerged as a strong tool for differentiating HC, MCI, and AD, demonstrating its potential prognostic value for the MCI population.


Asunto(s)
Enfermedad de Alzheimer , Disfunción Cognitiva , Progresión de la Enfermedad , Imagen por Resonancia Magnética , Pruebas Neuropsicológicas , Humanos , Enfermedad de Alzheimer/patología , Enfermedad de Alzheimer/diagnóstico por imagen , Enfermedad de Alzheimer/psicología , Disfunción Cognitiva/patología , Disfunción Cognitiva/diagnóstico por imagen , Disfunción Cognitiva/diagnóstico , Masculino , Femenino , Anciano , Imagen por Resonancia Magnética/métodos , Persona de Mediana Edad , Encéfalo/patología , Encéfalo/diagnóstico por imagen , Procesamiento de Imagen Asistido por Computador , Anciano de 80 o más Años
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