{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,14]],"date-time":"2026-10-14T20:29:27Z","timestamp":1792009767961,"version":"4.4.0"},"reference-count":39,"publisher":"Wiley","issue":"6","license":[{"start":{"date-parts":[[2022,10,13]],"date-time":"2022-10-13T00:00:00Z","timestamp":1665619200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"funder":[{"DOI":"10.13039\/501100004484","name":"Tehran University of Medical Sciences and Health Services","doi-asserted-by":"publisher","award":["99\u20103\u2010101\u201045445"],"award-info":[{"award-number":["99\u20103\u2010101\u201045445"]}],"id":[{"id":"10.13039\/501100004484","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Magnetic Resonance Imaging"],"published-print":{"date-parts":[[2023,6]]},"abstract":"<jats:sec><jats:title>Background<\/jats:title><jats:p>Alzheimer disease (AD) is a neurological disorder with brain network dysfunction. Investigation of the brain network functional connectivity (FC) alterations using resting\u2010state functional MRI (rs\u2010fMRI) can provide valuable information about the brain network pattern in early AD diagnosis.<\/jats:p><\/jats:sec><jats:sec><jats:title>Purpose<\/jats:title><jats:p>To quantitatively assess FC patterns of resting\u2010state brain networks and graph theory metrics (GTMs) to identify potential features for differentiation of amnestic mild cognitive impairment (aMCI) and late\u2010onset AD from normal.<\/jats:p><\/jats:sec><jats:sec><jats:title>Study Type<\/jats:title><jats:p>Prospective.<\/jats:p><\/jats:sec><jats:sec><jats:title>Subjects<\/jats:title><jats:p>A total of 14 normal, 16 aMCI, and 13 late\u2010onset AD.<\/jats:p><\/jats:sec><jats:sec><jats:title>Field Strength\/Sequence<\/jats:title><jats:p>A 3.0\u2009T; <jats:styled-content style=\"fixed-case\">rs\u2010fMRI<\/jats:styled-content>: single\u2010shot <jats:styled-content style=\"fixed-case\">2D\u2010EPI<\/jats:styled-content> and <jats:styled-content style=\"fixed-case\">T1<\/jats:styled-content>\u2010weighted structure: <jats:styled-content style=\"fixed-case\">MPRAGE<\/jats:styled-content>.<\/jats:p><\/jats:sec><jats:sec><jats:title>Assessment<\/jats:title><jats:p>By applying bivariate correlation coefficient and Fisher transformation on the time series of predefined ROIs' pairs, correlation coefficient matrixes and ROI\u2010to\u2010ROI connectivity (RRC) were extracted. By thresholding the RRC matrix (with a threshold of 0.15), a graph adjacency matrix was created to compute GTMs.<\/jats:p><\/jats:sec><jats:sec><jats:title>Statistical Tests<\/jats:title><jats:p>Region of interest (ROI)\u2010based analysis: parametric multivariable statistical analysis (PMSA) with a false discovery rate using (FDR)\u2010corrected <jats:italic>P<\/jats:italic>\u00a0&lt;\u20090.05 cluster\u2010level threshold together with posthoc uncorrected <jats:italic>P<\/jats:italic>\u00a0&lt;\u20090.05 connection\u2010level threshold. Graph\u2010theory analysis (GTA): <jats:italic>P<\/jats:italic>\u2010FDR\u2010corrected\u2009&lt;\u20090.05. One\u2010way ANOVA and Chi\u2010square tests were used to compare clinical characteristics.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>PMSA differentiated AD from normal, with a significant decrease in FC of default mode, salience, dorsal attention, frontoparietal, language, visual, and cerebellar networks. Furthermore, significant increase in overall FC of visual and language networks was observed in aMCI compared to normal. GTA revealed a significant decrease in global\u2010efficiency (28.05\u2009&lt;\u200945), local\u2010efficiency (22.98\u2009&lt;\u200924.05), and betweenness\u2010centrality (14.60\u2009&lt;\u200917.39) for AD against normal. Moreover, a significant increase in local\u2010efficiency (33.46\u2009&gt;\u200924.05) and clustering\u2010coefficient (25\u2009&gt;\u200920.18) were found in aMCI compared to normal.<\/jats:p><\/jats:sec><jats:sec><jats:title>Data Conclusion<\/jats:title><jats:p>This study demonstrated resting\u2010state FC potential as an indicator to differentiate AD, aMCI, and normal. GTA revealed brain integration and breakdown by providing concise and comprehensible statistics.<\/jats:p><\/jats:sec><jats:sec><jats:title>Evidence Level<\/jats:title><jats:p>1<\/jats:p><\/jats:sec><jats:sec><jats:title>Technical Efficacy<\/jats:title><jats:p>Stage 2<\/jats:p><\/jats:sec>","DOI":"10.1002\/jmri.28469","type":"journal-article","created":{"date-parts":[[2022,10,13]],"date-time":"2022-10-13T10:49:40Z","timestamp":1665658180000},"page":"1702-1712","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":15,"title":["Quantitative Assessment of Resting\u2010State Functional Connectivity <scp>MRI<\/scp> to Differentiate Amnestic Mild Cognitive Impairment, Late\u2010Onset Alzheimer's Disease From Normal 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