Seven Tesla MRI in Alzheimer's disease research: State of the art and future directions: A narrative review

Arosh S. Perera Molligoda Arachchige; Anton Kristoffer Garner; Arosh S. Perera Molligoda Arachchige; Anton Kristoffer Garner

doi:10.3934/Neuroscience.2023030

AIMS Neuroscience

2023, Volume 10, Issue 4: 401-422. doi: 10.3934/Neuroscience.2023030

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Review Topical Sections

Seven Tesla MRI in Alzheimer's disease research: State of the art and future directions: A narrative review

Faculty of Medicine, Humanitas University, Milan, Italy

Received: 27 July 2023 Revised: 29 November 2023 Accepted: 04 December 2023 Published: 11 December 2023

Seven tesla magnetic resonance imaging (7T MRI) is known to offer a superior spatial resolution and a signal-to-noise ratio relative to any other non-invasive imaging technique and provides the possibility for neuroimaging researchers to observe disease-related structural changes, which were previously only apparent on post-mortem tissue analyses. Alzheimer's disease is a natural and widely used subject for this technology since the 7T MRI allows for the anticipation of disease progression, the evaluation of secondary prevention measures thought to modify the disease trajectory, and the identification of surrogate markers for treatment outcome. In this editorial, we discuss the various neuroimaging biomarkers for Alzheimer's disease that have been studied using 7T MRI, which include morphological alterations, molecular characterization of cerebral T2*-weighted hypointensities, the evaluation of cerebral microbleeds and microinfarcts, biochemical changes studied with MR spectroscopy, as well as some other approaches. Finally, we discuss the limitations of the 7T MRI regarding imaging Alzheimer's disease and we provide our outlook for the future.
- MRI,
- 7T,
- ultra-high field,
- Alzheimer,
- dementia
Citation: Arosh S. Perera Molligoda Arachchige, Anton Kristoffer Garner. Seven Tesla MRI in Alzheimer's disease research: State of the art and future directions: A narrative review[J]. AIMS Neuroscience, 2023, 10(4): 401-422. doi: 10.3934/Neuroscience.2023030

Related Papers:

Abstract

Seven tesla magnetic resonance imaging (7T MRI) is known to offer a superior spatial resolution and a signal-to-noise ratio relative to any other non-invasive imaging technique and provides the possibility for neuroimaging researchers to observe disease-related structural changes, which were previously only apparent on post-mortem tissue analyses. Alzheimer's disease is a natural and widely used subject for this technology since the 7T MRI allows for the anticipation of disease progression, the evaluation of secondary prevention measures thought to modify the disease trajectory, and the identification of surrogate markers for treatment outcome. In this editorial, we discuss the various neuroimaging biomarkers for Alzheimer's disease that have been studied using 7T MRI, which include morphological alterations, molecular characterization of cerebral T2*-weighted hypointensities, the evaluation of cerebral microbleeds and microinfarcts, biochemical changes studied with MR spectroscopy, as well as some other approaches. Finally, we discuss the limitations of the 7T MRI regarding imaging Alzheimer's disease and we provide our outlook for the future.

Abbreviations

Aβ

beta-amyloid

Alzheimer's disease

ASL

Arterial Spin Labelling

BOLD

blood oxygenation level-dependent

Cornus Ammonis

CA1-SRLM

stratum radiatum and lacunosum-moleculare of the Cornu Ammonis' field 1

CBF

cerebral blood flow

CEST

chemical exchange saturation transfer

CMI

cerebral microinfarcts

CNR

contrast-to-noise ratio

CSF

cerebrospinal fluid

DKI

diffusion kurtosis imaging

DTI

diffusion tensor imaging

EEG

electroencephalography

FLAIR

fluid attenuated inversion recovery

fMRI

functional MRI

Gln

glutamine

Glu

glutamate

gluCEST

Chemical Exchange Saturation Transfer of glutamate

GABA

γ-Aminobutyric acid

GRE

gradient recalled echo

locus coeruleus

MCI

mild cognitive impairment

myo-inositol

magnetization transfer

MRS

MR Spectroscopy

PET

Positron Emission Tomography

PVS

perivascular spaces

PiB

Pittsburgh compound B

radiofrequency

SNR

signal-to-noise ratio

SWI

susceptibility-weighted imaging

TSE

turbo spin echo

UHF

ultra-high field

Conflicts of interest

The authors have no conflicts of interest to declare.

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