[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"detail-sidebar-cat-0-en-105":3,"doc-seo-469917-105":59,"doc-detail-469917-en":130},{"code":4,"msg":5,"data":6},0,"success",[7,13,18,23,28,33,38,43,48,51,55],{"id":8,"doc_module":4,"doc_module_name":9,"category_name":10,"show_sort_weight":11,"slug":12},1,"Document","Story & Novel",90,"story-novel",{"id":14,"doc_module":4,"doc_module_name":9,"category_name":15,"show_sort_weight":16,"slug":17},2,"Literature",80,"literature",{"id":19,"doc_module":4,"doc_module_name":9,"category_name":20,"show_sort_weight":21,"slug":22},4,"Exam",70,"exam",{"id":24,"doc_module":4,"doc_module_name":9,"category_name":25,"show_sort_weight":26,"slug":27},5,"Comic",60,"comic",{"id":29,"doc_module":4,"doc_module_name":9,"category_name":30,"show_sort_weight":31,"slug":32},6,"Technology",50,"technology",{"id":34,"doc_module":4,"doc_module_name":9,"category_name":35,"show_sort_weight":36,"slug":37},7,"Healthcare",40,"healthcare",{"id":39,"doc_module":4,"doc_module_name":9,"category_name":40,"show_sort_weight":41,"slug":42},8,"Research & Report",30,"research-report",{"id":44,"doc_module":4,"doc_module_name":9,"category_name":45,"show_sort_weight":46,"slug":47},9,"Religion & Spirituality",20,"religion-spirituality",{"id":46,"doc_module":4,"doc_module_name":9,"category_name":49,"show_sort_weight":46,"slug":50},"World Cup","world-cup",{"id":52,"doc_module":4,"doc_module_name":9,"category_name":53,"show_sort_weight":52,"slug":54},10,"Lifestyle","lifestyle",{"id":56,"doc_module":4,"doc_module_name":9,"category_name":57,"show_sort_weight":24,"slug":58},19,"General","general",{"code":4,"msg":60,"data":61},"ok",{"site_id":62,"language":63,"slug":64,"title":65,"keywords":66,"description":67,"schema_data":68,"social_meta":123,"head_meta":125,"extra_data":127,"updated_unix":129},105,"en","local-brain-aging-maps-proximity-to-alzheimers-related-cognitive-impairment-poster-presentation","Local brain aging maps proximity to Alzheimer’s-related cognitive impairment - Poster presentation","","Background: Traditional brain morphometrics, such as regional brain volumes, may be insufficiently sensitive to early, subtle neurodegeneration before cognitive impairment (CI). Deep learning models can estimate chronological age from MRIs and derive brain age gap (AG). Method: Global and local AGs are quantified in 1,320 participants from NACC and ADNI, comparing converters/non-converters and Alzheimer’s disease groups. Regional aging changes are assessed across short-, mid-, and long-term converters. Results: Global AG is elevated in converters and AD subjects, while regional local AG increases in temporal/insular/orbitofrontal areas and spreads toward cingulate, temporal, frontal, and parietal regions near CI onset. Conclusion: Local AG maps provide non-invasive, temporally sensitive biomarkers that reflect known AD patterns and support earlier detection.",{"@graph":69,"@context":122},[70,84,105],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":35,"@type":76,"position":81},"https://docshare.wps.com/document/healthcare/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/local-brain-aging-maps-proximity-to-alzheimers-related-cognitive-impairment-poster-presentation/469917/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/local-brain-aging-maps-proximity-to-alzheimers-related-cognitive-impairment-poster-presentation/469917.png","ImageObject",300,407,{"name":92,"@type":93},"anakgang17","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-11-08","2026-09-30",true,{"@type":102,"interactionType":103,"userInteractionCount":29},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"Why are traditional brain morphometrics considered limited for early CI?","Question",{"text":112,"@type":113},"Regional brain volumes may not capture early, subtle neurodegenerative changes that precede cognitive impairment.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"How is the brain age gap (AG) used in this study?",{"text":117,"@type":113},"A deep learning model predicts chronological age from MRIs, producing a brain age estimate; the difference between brain age and chronological age forms the age gap (AG), including local AGs by brain region.",{"name":119,"@type":110,"acceptedAnswer":120},"What do the results show about global and local AG in converters and Alzheimer’s subjects?",{"text":121,"@type":113},"Global AG is significantly higher in short- and mid-term converters and Alzheimer’s subjects versus non-converters, while mid-term converters show higher local AGs in temporal, insular, and orbitofrontal regions.","https://schema.org",{"og:url":83,"og:type":124,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":126,"canonical":83},"index,follow",{"doc_id":128,"site_id":62},469917,1790776449,{"code":4,"msg":5,"data":131},{"doc_id":128,"user_id":132,"nickname":92,"user_avatar":133,"doc_module":4,"category_id":34,"category_name":35,"doc_title":65,"doc_description":67,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":29,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":14,"language":139,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":140,"faqs":141,"seo_title":142,"seo_description":67,"update_tm":129,"read_time":24,"preview_page_count":4},962090883568,"https://ap-avatar.wpscdn.com/davatar_a8503ba1806abce46bf441b54a3ca4cd","DOI: 10. 1002/alz70856_107525  \nBIOMARKERS  \nPOSTER PRESENTATION  \nNEUROIMAGING  \nLocal brain aging maps proximity to Alzheimer’s-related cognitive impairment  \nPhoebe Imms1  Nikhil N Chaudhari 1, 2  Owen M Vega 1  Andrei Irimia 1, 2, 3, 4  \n1 Leonard Davis School of Gerontology, University of Southern California, Los Angeles, CA, USA  \n2Viterbi School of Engineering, University of Southern California, Los Angeles, CA, USA  \n3 Dana and David Dornsife College of Arts & Sciences, University of Southern California, Los Angeles, CA, USA  \n4 Kings College London, London, London, United Kingdom  \nCorrespondence  \nPhoebe Imms, Leonard Davis School of Gerontology, University of Southern California, Los Angeles, CA, USA. Email: [imms@usc.edu](imms@usc.edu)  \nAbstract  \nBackground: Traditional brain morphometrics(e.g., regional brain volumes)may not be sensitive to early and subtle neurodegenerations that precede cognitive impairment (CI). Deep learning neural networks (DNNs) leverage neuroimaging data to detect voxel-level deviations from normality. DNNs are trained to predict chronological age (CA) from magnetic resonance images (MRIs), resulting in a global brain age (BA) that estimates the biological age of a brain. The difference between BA and CA reflects the age gap (AG), which is larger in patients with neurodegenerative diseases. Our DNN generates local AGs in specific brain regions, to offer regionally interpretable insights into neurodegeneration.  \nMethod: We quantify global and local AGs in 1,320 participants across two largescale data repositories (i.e., NACC and ADNI). We compare group-level differences in global AG to group-level differences in brain volume across CN adults with and without CI in their future (converters and non-converters, respectively), and individuals with Alzheimer’s disease. Additionally, we explore regional-level spatial changes in brain aging across CN adults who will convert in the short-term (ST; 0.5 to 2.5 years), mid-term (MT; 2.5 to 6 years), and long-term (LT; > 6years).  \nResult: Global AGs, but not brain volumes, are significantly elevated in ST and MT converters and AD subjects compared to non-converters. Compared to nonconverters, MT converters’ local AGs are significantly higher in temporal, insular, and orbitofrontal regions. As converters approach CI onset (i.e., ST converters), larger AGs propagate to anterior cingulate cortices, lateral temporal and frontal lobes, and parietal regions, before encompassing the rest of the cortex in subjects with AD. Conclusion: Our results challenge the assumption that T1-weighted MRIs cannot reveal temporal dynamics of neurodegeneration. The patterns revealed by local AG maps recapitulate known neurodegenerative patterns of AD observed using imaging techniques that require exposure to radiation (i.e., positron emission tomography). The ability to employ spatiotemporally sensitive biomarkers that are non-invasive  \nThis is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.  \n© 2025 The Alzheimer’s Association. Alzheimer’s & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer’s Association.  \nAlzheimer’s Dement. 2025;21(Suppl. 2):e107525.  \n[https://doi.org/10.1002/alz70856_107525](https://doi.org/10.1002/alz70856_107525)  \nwi[leyonlinelibrary.com/journal/alz](leyonlinelibrary.com/journal/alz)  \n1of2  \nBIOMARKERS  \nand informative of proximity to CI conversion reduces barriers to early detection of Alzheimer’s disease.","cbCaioyFUNxE8nqN","https://ap.wps.com/l/cbCaioyFUNxE8nqN","pdf",3574564,"English","# Abstract\n## Background\n## Method\n## Result\n## Conclusion","[{\"question\":\"Why are traditional brain morphometrics considered limited for early CI?\",\"answer\":\"Regional brain volumes may not capture early, subtle neurodegenerative changes that precede cognitive impairment.\"},{\"question\":\"How is the brain age gap (AG) used in this study?\",\"answer\":\"A deep learning model predicts chronological age from MRIs, producing a brain age estimate; the difference between brain age and chronological age forms the age gap (AG), including local AGs by brain region.\"},{\"question\":\"What do the results show about global and local AG in converters and Alzheimer’s subjects?\",\"answer\":\"Global AG is significantly higher in short- and mid-term converters and Alzheimer’s subjects versus non-converters, while mid-term converters show higher local AGs in temporal, insular, and orbitofrontal regions.\"}]","Local brain aging maps proximity to Alzheimer’s-related cognitive impairment - Poster presentation | PDF"]