{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,18]],"date-time":"2026-10-18T15:10:24Z","timestamp":1792336224787,"version":"4.4.0"},"reference-count":38,"publisher":"Oxford University Press (OUP)","issue":"3","license":[{"start":{"date-parts":[[2026,5,7]],"date-time":"2026-05-07T00:00:00Z","timestamp":1778112000000},"content-version":"vor","delay-in-days":126,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100007333","name":"Alzheimer\u2019s Disease Neuroimaging Initiative","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100007333","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100014041","name":"ADNI","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100014041","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000049","name":"National Institute on Aging","doi-asserted-by":"publisher","award":["U19AG24904"],"award-info":[{"award-number":["U19AG24904"]}],"id":[{"id":"10.13039\/100000049","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000049","name":"National Institute on Aging","doi-asserted-by":"publisher","award":["K99AG088363"],"award-info":[{"award-number":["K99AG088363"]}],"id":[{"id":"10.13039\/100000049","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000957","name":"Alzheimer\u2019s Association","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000957","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100018580","name":"National Alzheimer\u2019s Coordinating Center","doi-asserted-by":"publisher","award":["NIAP24-1268927"],"award-info":[{"award-number":["NIAP24-1268927"]}],"id":[{"id":"10.13039\/100018580","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Richman Family Precision Medicine Center of Excellence in Alzheimer\u2019s Disease"},{"DOI":"10.13039\/100012304","name":"Johns Hopkins University School of Medicine","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100012304","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,5,5]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Alzheimer\u2019s disease (AD) exhibits selective vulnerability in hippocampal subfields, where microstructural alterations precede overt atrophy. Conventional morphometric measures, such as volume or thickness, are limited in their ability to capture subtle textural heterogeneity that reflects underlying cytoarchitectural disorganization, particularly perforant path fibres within the subiculum. The objective of this study is to determine whether hippocampal subregional texture-based radiomic features can serve as sensitive markers of disease severity and cognitive impairment along the AD continuum. This retrospective, multicentre, cross-sectional study used data from the Alzheimer\u2019s Disease Neuroimaging Initiative (ADNI). Participants who underwent coronal high-resolution T2-weighted \u2018HighResHippo\u2019 magnetic resonance imaging (MRI) and cerebrospinal fluid (CSF) biomarker assessment within 1 month of each other between June 2011 and May 2025 were included. Automatic Segmentation of Hippocampal Subfields was used to delineate cornu ammonis 1\u20133, dentate gyrus, subiculum, and other medial temporal cortices, followed by quality control to exclude mislabelled or artefact-degraded segmentations. After bias-field correction, intensity normalization, and voxel-resampling, first-order, shape, and texture features\u2014including grey-level run-length matrix (GLRLM) metrics\u2014were extracted. Participants were categorized according to cognitive status and CSF amyloid-\u03b2 (A\u03b2) positivity. Associations between radiomic features and Montreal Cognitive Assessment (MoCA) scores as well as CSF tau concentrations were evaluated using multiple linear regression, adjusting for age, sex, education, and APOE \u03b54 status. Among 1264 screened participants, 241 met all inclusion criteria (mean age 73.4 \u00b1 6.9 years; 54% women). GLRLM-based run entropy within the subiculum demonstrated a stepwise increase across the AD continuum (cognitively unimpaired-A\u03b2\u2212 &amp;lt; cognitively unimpaired-A\u03b2+ &amp;lt; mild cognitive impairment-A\u03b2+ &amp;lt; AD dementia-A\u03b2+). Orientation-specific analyses revealed that the superior\u2013inferior component\u2014aligned with the dominant fibre orientation of the subicular efferent pathway\u2014showed the strongest associations with clinical and biomarker indices. Higher SI run entropy correlated with lower MoCA performance (standardized \u03b2 = \u22120.710 [95% CI \u22121.416 to \u22120.038]) and higher CSF tau levels (standardized \u03b2 = 2.307 [95% CI 0.767 to 3.848]) compared with other directional components. Radiomic texture features derived from in vivo high-resolution T2-weighted MRI of hippocampal subregions\u2014particularly subicular GLRLM run entropy aligned with superior\u2013inferior tract orientation\u2014track disease severity and cognitive impairment along the AD continuum. These findings support texture-based imaging biomarkers as sensitive indicators of early microstructural alterations in AD.<\/jats:p>","DOI":"10.1093\/braincomms\/fcag164","type":"journal-article","created":{"date-parts":[[2026,5,6]],"date-time":"2026-05-06T11:38:38Z","timestamp":1778067518000},"source":"Crossref","is-referenced-by-count":3,"title":["Hippocampal subregional texture features associated with Alzheimer\u2019s disease severity and cognition"],"prefix":"10.1093","volume":"8","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6521-0784","authenticated-orcid":false,"given":"Yuto","family":"Uchida","sequence":"first","affiliation":[{"name":"Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine , Baltimore, MD 21205 ,","place":["USA"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kei","family":"Nishimaki","sequence":"additional","affiliation":[{"name":"Department of Applied Informatics, Graduate School of Science and Engineering, Hosei University , Tokyo 184-8584 ,","place":["Japan"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hirohito","family":"Kan","sequence":"additional","affiliation":[{"name":"Department of Integrated Health Sciences, Nagoya University Graduate School of Medicine , Nagoya, Aichi 461-8673 ,","place":["Japan"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hitoshi","family":"Iyatomi","sequence":"additional","affiliation":[{"name":"Department of Applied Informatics, Graduate School of Science and Engineering, Hosei University , Tokyo 184-8584 ,","place":["Japan"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1200-8611","authenticated-orcid":false,"given":"Kenichi","family":"Oishi","sequence":"additional","affiliation":[{"name":"Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine , Baltimore, MD 21205 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