{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,5,28]],"date-time":"2025-05-28T04:19:58Z","timestamp":1748405998575,"version":"3.41.0"},"reference-count":76,"publisher":"Wiley","issue":"5","license":[{"start":{"date-parts":[[2015,5,4]],"date-time":"2015-05-04T00:00:00Z","timestamp":1430697600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"funder":[{"name":"NSF","award":["1416953, 0716055 and 1023115"],"award-info":[{"award-number":["1416953, 0716055 and 1023115"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Journal of Neuroimaging"],"published-print":{"date-parts":[[2015,9]]},"abstract":"<jats:title>ABSTRACT<\/jats:title><jats:sec><jats:title>BACKGROUND AND PURPOSE<\/jats:title><jats:p>This study investigates 36 subjects aged 55\u201065 from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database to expand our knowledge of early\u2010onset (EO) Alzheimer's Disease (EO\u2010AD) using neuroimaging biomarkers.<\/jats:p><\/jats:sec><jats:sec><jats:title>METHODS<\/jats:title><jats:p>Nine of the subjects had EO\u2010AD, and 27 had EO mild cognitive impairment (EO\u2010MCI). The structural ADNI data were parcellated using BrainParser, and the 15 most discriminating neuroimaging markers between the two cohorts were extracted using the Global Shape Analysis (GSA) Pipeline workflow. Then the Local Shape Analysis (LSA) Pipeline workflow was used to conduct local (per\u2010vertex) post\u2010hoc statistical analyses of the shape differences based on the participants\u2019 diagnoses (EO\u2010MCI+EO\u2010AD). Tensor\u2010based Morphometry (TBM) and multivariate regression models were used to identify the significance of the structural brain differences based on the participants\u2019 diagnoses.<\/jats:p><\/jats:sec><jats:sec><jats:title>RESULTS<\/jats:title><jats:p>The significant between\u2010group regional differences using GSA were found in 15 neuroimaging markers. The results of the LSA analysis workflow were based on the subject diagnosis, age, years of education, apolipoprotein E (\u03b54), Mini\u2010Mental State Examination, visiting times, and logical memory as regressors. All the variables had significant effects on the regional shape measures. Some of these effects survived the false discovery rate (FDR) correction. Similarly, the TBM analysis showed significant effects on the Jacobian displacement vector fields, but these effects were reduced after FDR correction.<\/jats:p><\/jats:sec><jats:sec><jats:title>CONCLUSIONS<\/jats:title><jats:p>These results may explain some of the differences between EO\u2010AD and EO\u2010MCI, and some of the characteristics of the EO cognitive impairment subjects.<\/jats:p><\/jats:sec>","DOI":"10.1111\/jon.12252","type":"journal-article","created":{"date-parts":[[2015,5,4]],"date-time":"2015-05-04T09:49:24Z","timestamp":1430732964000},"page":"728-737","source":"Crossref","is-referenced-by-count":13,"title":["Structural Brain Changes in Early\u2010Onset Alzheimer's Disease Subjects Using the LONI Pipeline Environment"],"prefix":"10.1111","volume":"25","author":[{"given":"Seok Woo","family":"Moon","sequence":"first","affiliation":[{"name":"Department of Psychiatry Konkuk University School of Medicine Seoul 143\u2010701 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