{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,6]],"date-time":"2026-10-06T17:09:02Z","timestamp":1791306542633,"version":"4.3.1"},"reference-count":43,"publisher":"Wiley","issue":"4","license":[{"start":{"date-parts":[[2023,11,30]],"date-time":"2023-11-30T00:00:00Z","timestamp":1701302400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["82102010"],"award-info":[{"award-number":["82102010"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100005090","name":"Beijing Nova Program","doi-asserted-by":"publisher","award":["Z211100002121054"],"award-info":[{"award-number":["Z211100002121054"]}],"id":[{"id":"10.13039\/501100005090","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100005090","name":"Beijing Nova Program","doi-asserted-by":"publisher","award":["20220484177"],"award-info":[{"award-number":["20220484177"]}],"id":[{"id":"10.13039\/501100005090","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["CNS Neurosci Ther"],"published-print":{"date-parts":[[2024,4]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Purpose<\/jats:title>\n                    <jats:p>This study aimed to explore the utility of hippocampal radiomics using multiparametric simultaneous positron emission tomography (PET)\/magnetic resonance imaging (MRI) for early diagnosis of Alzheimer's disease (AD).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      A total of 53 healthy control (HC) participants, 55 patients with amnestic mild cognitive impairment (aMCI), and 51 patients with AD were included in this study. All participants accepted simultaneous PET\/MRI scans, including\n                      <jats:sup>18<\/jats:sup>\n                      F\u2010fluorodeoxyglucose (\n                      <jats:sup>18<\/jats:sup>\n                      F\u2010FDG) PET, 3D arterial spin labeling (ASL), and high\u2010resolution T1\u2010weighted imaging (3D T1WI). Radiomics features were extracted from the hippocampus region on those three modal images. Logistic regression models were trained to classify AD and HC, AD and aMCI, aMCI and HC respectively. The diagnostic performance and radiomics score (Rad\u2010Score) of logistic regression models were evaluated from 5\u2010fold cross\u2010validation.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      The hippocampal radiomics features demonstrated favorable diagnostic performance, with the multimodal classifier outperforming the single\u2010modal classifier in the binary classification of HC, aMCI, and AD. Using the multimodal classifier, we achieved an area under the receiver operating characteristic curve (AUC) of 0.98 and accuracy of 96.7% for classifying AD from HC, and an AUC of 0.86 and accuracy of 80.6% for classifying aMCI from HC. The value of Rad\u2010Score differed significantly between the AD and HC (\n                      <jats:italic>p<\/jats:italic>\n                      \u2009&lt;\u20090.001), aMCI and HC (\n                      <jats:italic>p<\/jats:italic>\n                      \u2009&lt;\u20090.001) groups. Decision curve analysis showed superior clinical benefits of multimodal classifiers compared to neuropsychological tests.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>Multiparametric hippocampal radiomics using PET\/MRI aids in the identification of early AD, and may provide a potential biomarker for clinical applications.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1111\/cns.14539","type":"journal-article","created":{"date-parts":[[2023,11,30]],"date-time":"2023-11-30T06:14:37Z","timestamp":1701324877000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":20,"title":["Multiparametric hippocampal signatures for early diagnosis of Alzheimer's disease using\n                    <scp>\n                      <sup>18<\/sup>\n                      F\u2010FDG PET\n                    <\/scp>\n                    \/\n                    <scp>MRI<\/scp>\n                    Radiomics"],"prefix":"10.1111","volume":"30","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1675-5606","authenticated-orcid":false,"given":"Zhigeng","family":"Chen","sequence":"first","affiliation":[{"name":"Department of Radiology and Nuclear Medicine, Xuanwu Hospital Capital Medical University  Beijing China"},{"name":"Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics  Beijing China"},{"name":"Key Laboratory of Neurodegenerative Diseases Ministry of Education  Beijing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sheng","family":"Bi","sequence":"additional","affiliation":[{"name":"Department of Radiology and Nuclear Medicine, Xuanwu Hospital Capital Medical University  Beijing China"},{"name":"Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics  Beijing China"},{"name":"Key Laboratory of Neurodegenerative Diseases Ministry of 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