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However, conventional magnetic resonance imaging (MRI) and fluid biomarkers often lack sensitivity to subtle structural alterations in early disease stages.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>METHODS<\/jats:title>\n                    <jats:p>To identify early brain alterations, we applied a perturbation\u2010based brain similarity approach to cognitively normal participants from Alzheimer's Disease Neuroimaging Initiative (ADNI) and Open Access Series of Imaging Studies (OASIS), stratified by amyloid status. We evaluated its predictive performance for cognition and diagnostic conversion against cortical thickness, volumetric MRI, and fluid biomarkers.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>RESULTS<\/jats:title>\n                    <jats:p>In both cohorts, brain similarity consistently outperformed other biomarkers across cognitive domains and amyloid groups. It also achieved superior accuracy in predicting clinical conversion and exhibited associations with cytoarchitectural organization.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>DISCUSSION<\/jats:title>\n                    <jats:p>These findings highlight brain similarity as a sensitive marker of early neuroanatomical disruption in AD. Its ability to detect subtle structural changes before overt atrophy underscores its potential for early disease monitoring and treatment assessment in preclinical AD trials.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Highlights<\/jats:title>\n                    <jats:p>\n                      <jats:list list-type=\"bullet\">\n                        <jats:list-item>\n                          <jats:p>Brain similarity captures early brain changes in preclinical Alzheimer's disease (AD).<\/jats:p>\n                        <\/jats:list-item>\n                        <jats:list-item>\n                          <jats:p>Brain similarity outperforms conventional biomarkers such as cortical thickness, volume measures, and fluid biomarkers in predicting cognitive decline.<\/jats:p>\n                        <\/jats:list-item>\n                        <jats:list-item>\n                          <jats:p>Brain similarity predicts conversion to mild cognitive impairment and AD more accurately than traditional imaging markers, and its predictive performance is further improved when combined with fluid biomarkers.<\/jats:p>\n                        <\/jats:list-item>\n                        <jats:list-item>\n                          <jats:p>Brain similarity captures structural disruptions associated with cortical layer II of the cytoarchitectonic lamina of human neocortex.<\/jats:p>\n                        <\/jats:list-item>\n                      <\/jats:list>\n                    <\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/alz.71170","type":"journal-article","created":{"date-parts":[[2026,3,19]],"date-time":"2026-03-19T03:34:51Z","timestamp":1773891291000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Tracking early cognitive decline in preclinical AD with brain MRI similarity"],"prefix":"10.1002","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2986-2734","authenticated-orcid":false,"given":"Jiawei","family":"Sun","sequence":"first","affiliation":[{"name":"Department of Clinical Neuroscience Division of Neuro Karolinska Institutet  Stockholm Sweden"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Blanca","family":"Zufiria\u2010Gerbol\u00e9s","sequence":"additional","affiliation":[{"name":"Department of Clinical Neuroscience Division of Neuro Karolinska Institutet  Stockholm Sweden"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Massimiliano","family":"Passaretti","sequence":"additional","affiliation":[{"name":"Department of Clinical Neuroscience Division of Neuro Karolinska Institutet  Stockholm Sweden"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Giovanni","family":"Volpe","sequence":"additional","affiliation":[{"name":"Department of Physics Goteborg University  Goteborg Sweden"},{"name":"Science for Lifesciences Laboratory Department of Physics Goteborg University  Goteborg Sweden"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mite","family":"Mijalkov","sequence":"additional","affiliation":[{"name":"Department of Clinical Neuroscience Division of Neuro Karolinska Institutet  Stockholm Sweden"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Joana B.","family":"Pereira","sequence":"additional","affiliation":[{"name":"Department of Clinical Neuroscience Division of Neuro Karolinska Institutet  Stockholm Sweden"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"name":"for the Alzheimer's Disease Neuroimaging 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