{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,28]],"date-time":"2026-04-28T17:25:31Z","timestamp":1777397131144,"version":"3.51.4"},"reference-count":43,"publisher":"SAGE Publications","issue":"1","license":[{"start":{"date-parts":[[2026,1,30]],"date-time":"2026-01-30T00:00:00Z","timestamp":1769731200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,1,30]],"date-time":"2026-01-30T00:00:00Z","timestamp":1769731200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"funder":[{"DOI":"10.13039\/501100000272","name":"NIHR","doi-asserted-by":"crossref","award":["301287"],"award-info":[{"award-number":["301287"]}],"id":[{"id":"10.13039\/501100000272","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Journal of Alzheimer\u2019s Disease"],"published-print":{"date-parts":[[2026,3]]},"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Dementia diagnosis is challenging and often delayed. Brain imaging techniques such as single-photon emission computed tomography (SPECT) imaging can help identify subtle changes in brain perfusion. Artificial intelligence methods may support results interpretation for early diagnosis.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>To develop and validate multivariate models for the early diagnosis of Alzheimer's disease (AD), using brain perfusion SPECT imaging and interpretable artificial intelligence methods in a real-world clinical setting.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Two logistic regression models were developed using a training dataset of 420 SPECT scans and tested on an independent clinical dataset of 443 scans. Model 1 was designed to identify abnormal perfusion patterns, while Model 2 identified perfusion changes associated with AD. Input features were extracted from anatomical volumes of interest, with feature selection performed using the Minimum Redundancy Maximum Relevance (MRMR) algorithm.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>The models demonstrated good classification performance using real-world clinical data. Model 1 achieved an area under receiver operator characteristic (AUROC) Curve of 0.89 (Sensitivity 76%, Specificity 87%) in identifying abnormal brain perfusion. Model 2 achieved an AUROC of 0.86 (Sensitivity 87%, Specificity 72%) in identifying AD.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Multivariate logistic regression models trained on real-world clinical data show promise as clinical decision support tools for the diagnosis of AD from brain perfusion SPECT imaging. The models use features from clinically relevant brain regions, which enhances interpretability. Future research should focus on expanding model applicability to other dementia types and on prospective evaluation of their utility in improving diagnostic accuracy, consistency, and care pathways in diverse clinical environments.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1177\/13872877251413790","type":"journal-article","created":{"date-parts":[[2026,1,31]],"date-time":"2026-01-31T02:54:27Z","timestamp":1769828067000},"page":"192-200","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":0,"title":["Alzheimer's disease diagnosis support for brain perfusion SPECT scans in a real-world clinical cohort"],"prefix":"10.1177","volume":"110","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1974-8388","authenticated-orcid":false,"given":"Sofia","family":"Michopoulou","sequence":"first","affiliation":[{"name":"Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton, UK"},{"name":"University Hospital Southampton NHS Foundation Trust, Southampton, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Angus","family":"Prosser","sequence":"additional","affiliation":[{"name":"Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Neil","family":"O\u2019Brien","sequence":"additional","affiliation":[{"name":"University Hospital Southampton NHS Foundation Trust, Southampton, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"John","family":"Dickson","sequence":"additional","affiliation":[{"name":"University College London Hospitals NHS Foundation Trust, London, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Matthew","family":"Guy","sequence":"additional","affiliation":[{"name":"University Hospital Southampton NHS Foundation Trust, Southampton, UK"},{"name":"School of Computer Science, University of Bristol, Bristol, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jessica L.","family":"Teeling","sequence":"additional","affiliation":[{"name":"Biological Sciences, University of Southampton, Southampton, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Christopher M.","family":"Kipps","sequence":"additional","affiliation":[{"name":"Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton, UK"},{"name":"University Hospital Southampton NHS Foundation Trust, Southampton, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","published-online":{"date-parts":[[2026,1,30]]},"reference":[{"key":"e_1_3_3_2_2","doi-asserted-by":"publisher","DOI":"10.1007\/s00259-015-3098-2"},{"key":"e_1_3_3_3_2","doi-asserted-by":"publisher","DOI":"10.1017\/S0033291712001122"},{"key":"e_1_3_3_4_2","article-title":"Temporal trend in dementia incidence since 2002 and projections for prevalence in England and Wales to 2040: modelling study","volume":"358","author":"Ahmadi-Abhari S","year":"2017","unstructured":"Ahmadi-Abhari S, Guzman-Castillo M, Bandosz P, et al. Temporal trend in dementia incidence since 2002 and projections for prevalence in England and Wales to 2040: modelling study. Br Med J 2017; 358: j2856.","journal-title":"Br Med J"},{"key":"e_1_3_3_5_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jalz.2005.06.003"},{"key":"e_1_3_3_6_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.trci.2017.06.001"},{"key":"e_1_3_3_7_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.pneurobio.2013.04.005"},{"key":"e_1_3_3_8_2","doi-asserted-by":"publisher","DOI":"10.1046\/j.1532-5415.5153.x"},{"key":"e_1_3_3_9_2","doi-asserted-by":"publisher","DOI":"10.1038\/nrneurol.2010.4"},{"key":"e_1_3_3_10_2","doi-asserted-by":"publisher","DOI":"10.1056\/NEJMoa2212948"},{"key":"e_1_3_3_11_2","doi-asserted-by":"publisher","DOI":"10.1001\/jama.2023.13239"},{"key":"e_1_3_3_12_2","doi-asserted-by":"publisher","DOI":"10.2174\/156720511795745348"},{"key":"e_1_3_3_13_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41398-019-0485-7"},{"key":"e_1_3_3_14_2","doi-asserted-by":"publisher","DOI":"10.1001\/jamaneurol.2024.3770"},{"key":"e_1_3_3_15_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jalz.2018.02.018"},{"key":"e_1_3_3_16_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.tins.2011.05.005"},{"key":"e_1_3_3_17_2","doi-asserted-by":"publisher","DOI":"10.3389\/fneur.2021.629442"},{"key":"e_1_3_3_18_2","doi-asserted-by":"publisher","DOI":"10.1097\/MNM.0000000000001736"},{"key":"e_1_3_3_19_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.neurobiolaging.2004.12.010"},{"key":"e_1_3_3_20_2","doi-asserted-by":"publisher","DOI":"10.1002\/alz.13859"},{"key":"e_1_3_3_21_2","doi-asserted-by":"publisher","DOI":"10.1109\/RBME.2018.2886237"},{"key":"e_1_3_3_22_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.trsl.2018.01.001"},{"key":"e_1_3_3_23_2","doi-asserted-by":"publisher","DOI":"10.1002\/alz.13412"},{"key":"e_1_3_3_24_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jalz.2013.05.1769"},{"key":"e_1_3_3_25_2","doi-asserted-by":"publisher","DOI":"10.3233\/JAD-150334"},{"key":"e_1_3_3_26_2","unstructured":"Statistical Parametric Mapping 12. https:\/\/www.fil.ion.ucl.ac.uk\/spm\/software\/spm12\/ (Accessed 8 Dec 2025)."},{"key":"e_1_3_3_27_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4615-1079-6_16"},{"key":"e_1_3_3_28_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2019.116189"},{"key":"e_1_3_3_29_2","unstructured":"National Institute for Health and Care Excellence Guideline [NG79]. Dementia: assessment management and support for people living with dementia and their carers. https:\/\/www.nice.org.uk\/guidance\/ng97\/chapter\/recommendations (Accessed 8 Dec 2025)."},{"key":"e_1_3_3_30_2","doi-asserted-by":"publisher","DOI":"10.1142\/S0219720005001004"},{"key":"e_1_3_3_31_2","doi-asserted-by":"publisher","DOI":"10.1053\/j.semnuclmed.2025.04.007"},{"key":"e_1_3_3_32_2","doi-asserted-by":"publisher","DOI":"10.1007\/s11604-024-01612-5"},{"key":"e_1_3_3_33_2","doi-asserted-by":"publisher","DOI":"10.2967\/jnumed.106.037218"},{"key":"e_1_3_3_34_2","doi-asserted-by":"publisher","DOI":"10.2967\/jnumed.114.143347"},{"key":"e_1_3_3_35_2","doi-asserted-by":"publisher","DOI":"10.3174\/ajnr.A1357"},{"key":"e_1_3_3_36_2","doi-asserted-by":"publisher","DOI":"10.1007\/s12149-021-01626-3"},{"key":"e_1_3_3_37_2","doi-asserted-by":"publisher","DOI":"10.3390\/jcm12062218"},{"key":"e_1_3_3_38_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41591-023-02540-z"},{"key":"e_1_3_3_39_2","doi-asserted-by":"publisher","DOI":"10.1002\/alz.12068"},{"key":"e_1_3_3_40_2","doi-asserted-by":"publisher","DOI":"10.1097\/NEN.0b013e31824b211b"},{"key":"e_1_3_3_41_2","doi-asserted-by":"publisher","DOI":"10.1093\/brain\/aww224"},{"key":"e_1_3_3_42_2","doi-asserted-by":"publisher","DOI":"10.1007\/s00259-025-07237-8"},{"key":"e_1_3_3_43_2","doi-asserted-by":"publisher","DOI":"10.1186\/s12916-019-1426-2"},{"key":"e_1_3_3_44_2","first-page":"96","article-title":"Interpretable AI in medical imaging: enhancing diagnostic accuracy through human-computer interaction","volume":"6","author":"Mishra R","year":"2024","unstructured":"Mishra R, Satpathy R, Pati B. Interpretable AI in medical imaging: enhancing diagnostic accuracy through human-computer interaction. J Artif Intell Syst 2024; 6: 96\u2013111.","journal-title":"J Artif Intell Syst"}],"container-title":["Journal of Alzheimer\u2019s Disease"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1177\/13872877251413790","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/full-xml\/10.1177\/13872877251413790","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1177\/13872877251413790","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,28]],"date-time":"2026-04-28T10:10:04Z","timestamp":1777371004000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/10.1177\/13872877251413790"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,1,30]]},"references-count":43,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2026,3]]}},"alternative-id":["10.1177\/13872877251413790"],"URL":"https:\/\/doi.org\/10.1177\/13872877251413790","relation":{},"ISSN":["1387-2877","1875-8908"],"issn-type":[{"value":"1387-2877","type":"print"},{"value":"1875-8908","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,1,30]]}}}