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Diagnostic value of arterial spin labeling for Alzheimer's disease: A systematic review and meta-analysis

Arterial spin labeling (ASL) is a magnetic resonance imaging (MRI) technique that offers a non-invasive approach for measuring cerebral blood perfusion (CBF). CBF serves as a marker of neuronal activity, and ASL has demonstrated the potential to detect reductions in CBF associated with early-stage n...

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Published in:PloS one 2024-11, Vol.19 (11), p.e0311016
Main Authors: Zhang, Xin-Yue, Zhang, Hong, Bao, Qiong-Nan, Yin, Zi-Han, Li, Ya-Qin, Xia, Man-Ze, Chen, Zheng-Hong, Zhong, Wan-Qi, Wu, Ke-Xin, Yao, Jin, Liang, Fan-Rong
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container_title PloS one
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creator Zhang, Xin-Yue
Zhang, Hong
Bao, Qiong-Nan
Yin, Zi-Han
Li, Ya-Qin
Xia, Man-Ze
Chen, Zheng-Hong
Zhong, Wan-Qi
Wu, Ke-Xin
Yao, Jin
Liang, Fan-Rong
description Arterial spin labeling (ASL) is a magnetic resonance imaging (MRI) technique that offers a non-invasive approach for measuring cerebral blood perfusion (CBF). CBF serves as a marker of neuronal activity, and ASL has demonstrated the potential to detect reductions in CBF associated with early-stage neurodegenerative diseases like Alzheimer's disease (AD). Consequently, ASL has garnered growing interest as a potential diagnostic tool for AD. Despite the promise of ASL for diagnosing AD, there is a paucity of data regarding the pooled specificity and sensitivity of this technique in this context. The purpose of this systematic review and meta-analysis is to identify the accuracy of ASL in the diagnosis of AD with international clinical diagnosis as the gold standard. Four English databases and four Chinese databases were searched from their inception to 30 November 2023. Two independent reviewers extracted relevant information from the eligible articles, while the quality assessment of included studies was assessed using the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2). The meta-analysis was carried out using the area under the Receiver Operator Characteristic (ROC) curves (AUC) and sensitivity and specificity values. Meta-DiSc 1.4 was used to perform the statistical analysis. STATA 16.0 was used to perform publication bias and sensitivity analysis. Of 844 relevant articles retrieved, 10 studies involving 494 participants (AD patients = 262, healthy controls = 232) met the inclusion criteria and were included in the meta-analysis. However, the quality of studies was low based on QUADAS-2. The pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio of ASL for diagnosing AD was 0.83 (95% CI: 0.78-0.87), 0.81 (95% CI: 0.76-0.86), 4.52 (95% CI: 3.40-6.00), 0.22 (95% CI: 0.17-0.28), and 19.31(95% CI: 12.30-30.31), respectively. The pooled AUC = 0.8932. There was low heterogeneity across the included studies. Finally, sensitivity analysis suggested that the results were reliable. ASL is an effective and accurate method for the diagnosis of AD. However, due to the limited quantity and quality of the included studies, the above conclusions need to be verified by more studies. PROSPERO registration number: CRD42023484059.
doi_str_mv 10.1371/journal.pone.0311016
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CBF serves as a marker of neuronal activity, and ASL has demonstrated the potential to detect reductions in CBF associated with early-stage neurodegenerative diseases like Alzheimer's disease (AD). Consequently, ASL has garnered growing interest as a potential diagnostic tool for AD. Despite the promise of ASL for diagnosing AD, there is a paucity of data regarding the pooled specificity and sensitivity of this technique in this context. The purpose of this systematic review and meta-analysis is to identify the accuracy of ASL in the diagnosis of AD with international clinical diagnosis as the gold standard. Four English databases and four Chinese databases were searched from their inception to 30 November 2023. Two independent reviewers extracted relevant information from the eligible articles, while the quality assessment of included studies was assessed using the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2). The meta-analysis was carried out using the area under the Receiver Operator Characteristic (ROC) curves (AUC) and sensitivity and specificity values. Meta-DiSc 1.4 was used to perform the statistical analysis. STATA 16.0 was used to perform publication bias and sensitivity analysis. Of 844 relevant articles retrieved, 10 studies involving 494 participants (AD patients = 262, healthy controls = 232) met the inclusion criteria and were included in the meta-analysis. However, the quality of studies was low based on QUADAS-2. The pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio of ASL for diagnosing AD was 0.83 (95% CI: 0.78-0.87), 0.81 (95% CI: 0.76-0.86), 4.52 (95% CI: 3.40-6.00), 0.22 (95% CI: 0.17-0.28), and 19.31(95% CI: 12.30-30.31), respectively. The pooled AUC = 0.8932. There was low heterogeneity across the included studies. Finally, sensitivity analysis suggested that the results were reliable. 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CBF serves as a marker of neuronal activity, and ASL has demonstrated the potential to detect reductions in CBF associated with early-stage neurodegenerative diseases like Alzheimer's disease (AD). Consequently, ASL has garnered growing interest as a potential diagnostic tool for AD. Despite the promise of ASL for diagnosing AD, there is a paucity of data regarding the pooled specificity and sensitivity of this technique in this context. The purpose of this systematic review and meta-analysis is to identify the accuracy of ASL in the diagnosis of AD with international clinical diagnosis as the gold standard. Four English databases and four Chinese databases were searched from their inception to 30 November 2023. Two independent reviewers extracted relevant information from the eligible articles, while the quality assessment of included studies was assessed using the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2). The meta-analysis was carried out using the area under the Receiver Operator Characteristic (ROC) curves (AUC) and sensitivity and specificity values. Meta-DiSc 1.4 was used to perform the statistical analysis. STATA 16.0 was used to perform publication bias and sensitivity analysis. Of 844 relevant articles retrieved, 10 studies involving 494 participants (AD patients = 262, healthy controls = 232) met the inclusion criteria and were included in the meta-analysis. However, the quality of studies was low based on QUADAS-2. The pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio of ASL for diagnosing AD was 0.83 (95% CI: 0.78-0.87), 0.81 (95% CI: 0.76-0.86), 4.52 (95% CI: 3.40-6.00), 0.22 (95% CI: 0.17-0.28), and 19.31(95% CI: 12.30-30.31), respectively. The pooled AUC = 0.8932. There was low heterogeneity across the included studies. Finally, sensitivity analysis suggested that the results were reliable. ASL is an effective and accurate method for the diagnosis of AD. However, due to the limited quantity and quality of the included studies, the above conclusions need to be verified by more studies. PROSPERO registration number: CRD42023484059.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>39570963</pmid><doi>10.1371/journal.pone.0311016</doi><tpages>e0311016</tpages><orcidid>https://orcid.org/0000-0002-2023-4053</orcidid><orcidid>https://orcid.org/0000-0002-5708-7878</orcidid><oa>free_for_read</oa></addata></record>
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identifier ISSN: 1932-6203
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1932-6203
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source Open Access: PubMed Central; Publicly Available Content (ProQuest)
subjects Accuracy
Advertising executives
Alzheimer Disease - diagnosis
Alzheimer Disease - diagnostic imaging
Alzheimer's disease
Bias
Biology and Life Sciences
Care and treatment
Cerebral blood flow
Cerebrovascular Circulation
Contingency tables
Dementia
Diagnosis
Diagnostic imaging
Disease
Diseases
Evaluation
Heterogeneity
Humans
Labeling
Likelihood ratio
Magnetic resonance
Magnetic resonance imaging
Magnetic Resonance Imaging - methods
Medical imaging
Medical imaging equipment
Medical research
Medicine and Health Sciences
Medicine, Experimental
Meta-analysis
Neurodegenerative diseases
Neuroimaging
Patients
Physical Sciences
Quality assessment
Quality control
Research and Analysis Methods
ROC Curve
Sensitivity analysis
Sensitivity and Specificity
Spin labeling
Spin Labels
Statistical analysis
Systematic review
Tomography
title Diagnostic value of arterial spin labeling for Alzheimer's disease: A systematic review and meta-analysis
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