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Acta Neuropathologica

, Volume 131, Issue 5, pp 687–707 | Cite as

Brain imaging of neurovascular dysfunction in Alzheimer’s disease

  • Axel Montagne
  • Daniel A. Nation
  • Judy Pa
  • Melanie D. Sweeney
  • Arthur W. Toga
  • Berislav V. ZlokovicEmail author
Review

Abstract

Neurovascular dysfunction, including blood–brain barrier (BBB) breakdown and cerebral blood flow (CBF) dysregulation and reduction, are increasingly recognized to contribute to Alzheimer’s disease (AD). The spatial and temporal relationships between different pathophysiological events during preclinical stages of AD, including cerebrovascular dysfunction and pathology, amyloid and tau pathology, and brain structural and functional changes remain, however, still unclear. Recent advances in neuroimaging techniques, i.e., magnetic resonance imaging (MRI) and positron emission tomography (PET), offer new possibilities to understand how the human brain works in health and disease. This includes methods to detect subtle regional changes in the cerebrovascular system integrity. Here, we focus on the neurovascular imaging techniques to evaluate regional BBB permeability (dynamic contrast-enhanced MRI), regional CBF changes (arterial spin labeling- and functional-MRI), vascular pathology (structural MRI), and cerebral metabolism (PET) in the living human brain, and examine how they can inform about neurovascular dysfunction and vascular pathophysiology in dementia and AD. Altogether, these neuroimaging approaches will continue to elucidate the spatio-temporal progression of vascular and neurodegenerative processes in dementia and AD and how they relate to each other.

Keywords

Alzheimer’s disease Neurovascular dysfunction Blood–brain barrier Cerebral blood flow Magnetic resonance imaging 

Abbreviations

AD

Alzheimer’s disease

AIF

Arterial input function

APOE

Apolipoprotein E

AR

Albumin ratio

ASL

Arterial spin labeling

Amyloid beta

BBB

Blood–brain barrier

BOLD

Blood oxygen level-dependent

CA1

Cornu ammonis 1

CAA

Cerebral amyloid angiopathy

CBF

Cerebral blood flow

CBV

Cerebral blood volume

CMB

Cerebral microbleed

CMRglc

Cerebral metabolic rate of glucose

CMRO2

Cerebral metabolic rate of oxygen consumption

CSF

Cerebrospinal fluid

DCE

Dynamic contrast-enhanced

dHb

Deoxyhemoglobin

DMN

Default mode network

DRS

Dementia rating scale

DTI

Diffusion tensor imaging

FA

Fractional anisotropy

FDG

Fluorodeoxyglucose

FLAIR

Fluid-attenuated inversion recovery

fMRI

Functional magnetic resonance imaging

GBCA

Gadolinium-based contrast agent

Hct

Hematocrit

kDa

KiloDalton

MCI

Mild cognitive impairment

MD

Mean diffusivity

MRI

Magnetic resonance imaging

NCI

No cognitive impairment

NVU

Neurovascular unit

PET

Positron emission tomography

PiB

Pittsburgh compound B

ROI

Region-of-interest

SNR

Signal-to-noise ratio

sPDGFRβ

Soluble platelet-derived growth factor receptor-β

SWI

Susceptibility weighted imaging

T

Tesla

WM

White matter

WMH

White matter hyperintensity

WML

White matter lesion

Notes

Acknowledgments

We thank the National Institutes of Health (NIH), the Zilkha Senior Scholar program, and the Alzheimer’s Association for support. Dr. Zlokovic’s research is supported by the NIH through grants R37NS34467, R37AG23084, and R01AG039452. Dr. Pa’s research is supported by the NIH through grant R01AG046928 and the Alzheimer’s Association grant NIRP12259277. Dr. Toga’s research is supported by the NIH through grant P41EB015922. We apologize to those authors whose original work we were not able to cite due to the limited length of this review.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  • Axel Montagne
    • 1
  • Daniel A. Nation
    • 2
  • Judy Pa
    • 3
  • Melanie D. Sweeney
    • 1
  • Arthur W. Toga
    • 3
  • Berislav V. Zlokovic
    • 1
    Email author
  1. 1.Zilkha Neurogenetic Institute and Department of Physiology and Biophysics, Keck School of MedicineUniversity of Southern CaliforniaLos AngelesUSA
  2. 2.Department of PsychologyUniversity of Southern CaliforniaLos AngelesUSA
  3. 3.Department of Neurology, Institute for Neuroimaging and InformaticsUniversity of Southern CaliforniaLos AngelesUSA

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