Sodium signal intensity of CSF using 1H-guided 23Na-MRI as a potential noninvasive biomarker in Alzheimer's disease.

Alzheimer's disease biomarkers cerebrospinal fluid (CSF) magnetic resonance imaging sodium (23Na) MRI

Journal

Journal of neuroimaging : official journal of the American Society of Neuroimaging
ISSN: 1552-6569
Titre abrégé: J Neuroimaging
Pays: United States
ID NLM: 9102705

Informations de publication

Date de publication:
28 May 2024
Historique:
revised: 14 05 2024
received: 10 01 2024
accepted: 14 05 2024
medline: 29 5 2024
pubmed: 29 5 2024
entrez: 29 5 2024
Statut: aheadofprint

Résumé

Alzheimer's disease (AD) is characterized by cognitive decline and mnestic deficits. The pathophysiology of AD is not fully understood, which renders the development of accurate tools for early diagnosis and effective therapies exceedingly difficult. In this study, we investigated the use of We prospectively recruited 11 patients with biomarker-diagnosed early-stage AD, as well as 12 cognitively healthy age-matched controls. All participants underwent RSSIs in CSF were significantly higher in AD patients (mean = 68.6% ± 7.7%) compared to healthy controls (mean = 56.9% ± 5.5%) (p < .001). There was also a significant negative correlation between rSSI in CSF and hippocampus and amygdala volumes (r = -.54 and -.49, p < .05) as well as a positive correlation with total CSF volumes (r = .81, p < .05). Receiver operating characteristic analysis showed high diagnostic accuracy for rSSI in discriminating between AD patients and healthy controls (area under the curve = .94). Our study provides evidence that rSSI in CSF is increased in AD patients in comparison to healthy controls. rSSI may serve as a potential marker for early detection and monitoring of disease progression. Larger, longitudinal studies are needed to confirm our findings and to investigate the association between rSSI in CSF and the severity of cognitive impairment.

Sections du résumé

BACKGROUND AND PURPOSE OBJECTIVE
Alzheimer's disease (AD) is characterized by cognitive decline and mnestic deficits. The pathophysiology of AD is not fully understood, which renders the development of accurate tools for early diagnosis and effective therapies exceedingly difficult. In this study, we investigated the use of
METHODS METHODS
We prospectively recruited 11 patients with biomarker-diagnosed early-stage AD, as well as 12 cognitively healthy age-matched controls. All participants underwent
RESULTS RESULTS
RSSIs in CSF were significantly higher in AD patients (mean = 68.6% ± 7.7%) compared to healthy controls (mean = 56.9% ± 5.5%) (p < .001). There was also a significant negative correlation between rSSI in CSF and hippocampus and amygdala volumes (r = -.54 and -.49, p < .05) as well as a positive correlation with total CSF volumes (r = .81, p < .05). Receiver operating characteristic analysis showed high diagnostic accuracy for rSSI in discriminating between AD patients and healthy controls (area under the curve = .94).
CONCLUSION CONCLUSIONS
Our study provides evidence that rSSI in CSF is increased in AD patients in comparison to healthy controls. rSSI may serve as a potential marker for early detection and monitoring of disease progression. Larger, longitudinal studies are needed to confirm our findings and to investigate the association between rSSI in CSF and the severity of cognitive impairment.

Identifiants

pubmed: 38807265
doi: 10.1111/jon.13216
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : None

Informations de copyright

© 2024 The Author(s). Journal of Neuroimaging published by Wiley Periodicals LLC on behalf of American Society of Neuroimaging.

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Auteurs

Hans-Ulrich Kerl (HU)

Department of Neuroradiology, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany.

Hakim Baazaoui (H)

Department of Neuroradiology, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany.
Department of Neurology, University Hospital Zurich, Zurich, Switzerland.

Katrin Herrmann (K)

Department of Neuroradiology, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany.

Anne Adlung (A)

Department of Computer Assisted Clinical Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany.
Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, New York, USA.

Nadia K Ludwig (NK)

Department of Computer Assisted Clinical Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany.
Löwenstein Medical Technology, Karlsruhe, Germany.

Lucrezia Hausner (L)

Department of Geriatric Psychiatry, Central Institute of Mental Health, Heidelberg University, Mannheim, Germany.

Lutz Frölich (L)

Department of Geriatric Psychiatry, Central Institute of Mental Health, Heidelberg University, Mannheim, Germany.

Lothar Schad (L)

Department of Computer Assisted Clinical Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany.

Christoph Groden (C)

Department of Neuroradiology, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany.

Sherif A Mohamed (SA)

Department of Neuroradiology, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany.

Classifications MeSH