A multi-contrast MRI study of microstructural brain damage in patients with mild cognitive impairment.

Détails

Ressource 1Télécharger: BIB_9AC329E8E273.P001.pdf (1268.43 [Ko])
Etat: Public
Version: Final published version
ID Serval
serval:BIB_9AC329E8E273
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Titre
A multi-contrast MRI study of microstructural brain damage in patients with mild cognitive impairment.
Périodique
Neuroimage. Clinical
Auteur(s)
Granziera C., Daducci A., Donati A., Bonnier G., Romascano D., Roche A., Bach Cuadra M., Schmitter D., Klöppel S., Meuli R., von Gunten A., Krueger G.
ISSN
2213-1582 (Electronic)
ISSN-L
2213-1582
Statut éditorial
Publié
Date de publication
2015
Peer-reviewed
Oui
Volume
8
Pages
631-639
Langue
anglais
Notes
Publication types: Journal Article ; Research Support, Non-U.S. Gov't ; Research Support, U.S. Gov't, Non-P.H.S.
Publication Status: epublish
Résumé
OBJECTIVES: The aim of this study was to investigate pathological mechanisms underlying brain tissue alterations in mild cognitive impairment (MCI) using multi-contrast 3 T magnetic resonance imaging (MRI).
METHODS: Forty-two MCI patients and 77 healthy controls (HC) underwent T1/T2* relaxometry as well as Magnetization Transfer (MT) MRI. Between-groups comparisons in MRI metrics were performed using permutation-based tests. Using MRI data, a generalized linear model (GLM) was computed to predict clinical performance and a support-vector machine (SVM) classification was used to classify MCI and HC subjects.
RESULTS: Multi-parametric MRI data showed microstructural brain alterations in MCI patients vs HC that might be interpreted as: (i) a broad loss of myelin/cellular proteins and tissue microstructure in the hippocampus (p ≤ 0.01) and global white matter (p < 0.05); and (ii) iron accumulation in the pallidus nucleus (p ≤ 0.05). MRI metrics accurately predicted memory and executive performances in patients (p ≤ 0.005). SVM classification reached an accuracy of 75% to separate MCI and HC, and performed best using both volumes and T1/T2*/MT metrics.
CONCLUSION: Multi-contrast MRI appears to be a promising approach to infer pathophysiological mechanisms leading to brain tissue alterations in MCI. Likewise, parametric MRI data provide powerful correlates of cognitive deficits and improve automatic disease classification based on morphometric features.
Mots-clé
Aged, Aged, 80 and over, Female, Globus Pallidus/metabolism, Hippocampus/pathology, Humans, Iron/metabolism, Magnetic Resonance Imaging/methods, Magnetic Resonance Imaging/standards, Male, Middle Aged, Mild Cognitive Impairment/pathology, Sensitivity and Specificity, White Matter/pathology
Pubmed
Open Access
Oui
Création de la notice
28/08/2015 14:08
Dernière modification de la notice
20/08/2019 15:01
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