{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,15]],"date-time":"2026-07-15T15:03:34Z","timestamp":1784127814275,"version":"3.55.0"},"reference-count":39,"publisher":"Wiley","issue":"6","license":[{"start":{"date-parts":[[2026,6,15]],"date-time":"2026-06-15T00:00:00Z","timestamp":1781481600000},"content-version":"vor","delay-in-days":14,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"funder":[{"DOI":"10.13039\/501100002865","name":"Chongqing Municipal Science and Technology Bureau","doi-asserted-by":"publisher","award":["cstc2022ycjh\u2010bgzXM0230"],"award-info":[{"award-number":["cstc2022ycjh\u2010bgzXM0230"]}],"id":[{"id":"10.13039\/501100002865","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000049","name":"National Institute on Aging","doi-asserted-by":"publisher","award":["U19AG024904"],"award-info":[{"award-number":["U19AG024904"]}],"id":[{"id":"10.13039\/100000049","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":[[2026,6]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Aims<\/jats:title>\n                    <jats:p>Alzheimer's disease (AD) is the most prevalent neurodegenerative disorder, and its identification of its prodromal stages remains a challenge. The choroid plexus (CP) plays a crucial role in AD pathology. This study aims to develop the CP radiomics model to distinguish AD from mild cognitive impairment (MCI) patients and predict the risk of MCI progression to AD.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Radiomics features of CP were derived from magnetic resonance imaging (MRI) data, utilizing scans derived from the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort and a local institutional cohort. A range of 12 classic machine learning algorithms was utilized for model construction. Additionally, we assessed the partial correlations of CP radiomics features with the Mini\u2010Mental State Examination (MMSE) score and with CSF biomarkers.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      In the MCI versus AD classification task, the CP model attained a best AUC of 0.794. This performance was further boosted to an AUC of 0.907 upon integration with clinical features. In the model predicting MCI\u2010to\u2010AD conversion, the CP model achieved an AUC of 0.745, which increased to 0.908 after incorporating clinical features. Furthermore, the high\u2010risk group, as defined by the radiomics model, had a significantly shorter time to AD conversion (HR\u2009=\u20092.201,\n                      <jats:italic>p<\/jats:italic>\n                      \u2009&lt;\u20090.001). CP radiomics features showed significant correlations with MMSE and CSF biomarkers (\n                      <jats:italic>p<\/jats:italic>\n                      \u2009&lt;\u20090.05).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>The machine learning model based on CP radiomics features effectively differentiates AD from MCI patients and predicts the risk of MCI progression to AD, offering new insights into the role of the CP in AD pathophysiology.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/cns.70987","type":"journal-article","created":{"date-parts":[[2026,6,16]],"date-time":"2026-06-16T06:07:28Z","timestamp":1781590048000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Decoding Choroid Plexus Pathology in Alzheimer's Disease: A Longitudinal Radiomics Approach for Prodromal Identification and Risk Stratification"],"prefix":"10.1002","volume":"32","author":[{"given":"Feiyue","family":"Yin","sequence":"first","affiliation":[{"name":"Department of Radiology The First Affiliated Hospital of Chongqing Medical University  Chongqing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaohua","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Radiology, Sichuan Provincial People's Hospital University of Electronic Science and Technology of China  Chengdu China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiao","family":"Chen","sequence":"additional","affiliation":[{"name":"Department of Nuclear Medicine Daping Hospital of Army Medical University  Chongqing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jinju","family":"Sun","sequence":"additional","affiliation":[{"name":"Department of Nuclear Medicine Daping Hospital of Army Medical University  Chongqing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kai","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Radiology The First Affiliated Hospital of Chongqing Medical University  Chongqing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaojuan","family":"Dong","sequence":"additional","affiliation":[{"name":"Department of Radiology The First Affiliated Hospital of Chongqing Medical University  Chongqing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wenwen","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Radiology The First Affiliated Hospital of Chongqing Medical University  Chongqing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Peng","family":"Zeng","sequence":"additional","affiliation":[{"name":"Department of Radiology The First Affiliated Hospital of Chongqing Medical University  Chongqing 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