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Cited by 182

The DOI matches its Crossref record; 8 of the 8 references it cites were found in a registry or an index.

Cerebral blood flow measured by arterial spin labeling MRI at resting state in normal aging and Alzheimer’s disease

Open access
Zhang, Nan, Gordon, Marc L., Goldberg, Terry E.·2017·Neuroscience & Biobehavioral Reviews

Abstract

Arterial spin labeling (ASL) magnetic resonance imaging uses arterial blood water as an endogenous tracer to measure cerebral blood flow (CBF). In this review, based on ASL studies in the resting state, we discuss state-of-the-art technical and data processing improvements in ASL, and ASL CBF changes in normal aging, mild cognitive impairment (MCI), Alzheimer's disease (AD), and other types of dementia. We propose that vascular and AD risk factors should be considered when evaluating CBF changes in aging, and that other validated biomarkers should be used as inclusion criteria or covariates when evaluating CBF changes in MCI and AD. With improvements in hardware and experimental design, ASL is proving to be an increasingly promising tool for exploring pathogenetic mechanisms, early detection, monitoring disease progression and pharmacological response, and differential diagnosis of AD.

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Crossref · 10.1016/j.neubiorev.2016.11.023

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Metadata

Authors
Zhang, N., Gordon, M. L., & Goldberg, T. E.
Venue
Neuroscience & Biobehavioral Reviews
Publisher
Elsevier BV
Published
2017-01
Volume
72
Pages
168-175
ISSN
0149-7634 (ISSN-L)
OpenAlex
W2557712647
Cited by
182
References
8
FWCI
11.30
Type
journal article
Language
en
Open access
hybrid

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CoChat. (2026). Citation check: Cerebral blood flow measured by arterial spin labeling MRI at resting state in normal aging and Alzheimer’s disease. https://app.cochat.ai/papers/10.1016/j.neubiorev.2016.11.023
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Zhang, N., Gordon, M. L., & Goldberg, T. E. (2017). Cerebral blood flow measured by arterial spin labeling MRI at resting state in normal aging and Alzheimer’s disease. Neuroscience & Biobehavioral Reviews. https://doi.org/10.1016/j.neubiorev.2016.11.023

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.