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Detectible change in brain volume emerges relatively late in the pathogenic progression of disease, but microstructural changes caused by early neuropathology may cause subtle changes in the MR signal, quantifiable using texture analysis. Texture analysis quantifies spatial patterns in an image, such as smoothness, randomness and heterogeneity. We investigated whether the MRI texture of the hippocampus, an early site of Alzheimer\u2019s disease pathology, is sensitive to changes in brain microstructure before the onset of cognitive impairment. We also explored the longitudinal trajectories of hippocampal texture across the Alzheimer\u2019s continuum in relation to hippocampal volume and other biomarkers. Finally, we assessed the ability of texture to predict future cognitive decline, over and above hippocampal volume. Data were acquired from the Alzheimer\u2019s Disease Neuroimaging Initiative. Texture was calculated for bilateral hippocampi on 3T T1-weighted MRI scans. Two hundred and ninety-three texture features were reduced to five principal components that described 88% of total variance within cognitively unimpaired participants. We assessed cross-sectional differences in these texture components and hippocampal volume between four diagnostic groups: cognitively unimpaired amyloid-\u03b2\u2212 (n = 406); cognitively unimpaired amyloid-\u03b2+ (n = 213); mild cognitive impairment amyloid-\u03b2+ (n = 347); and Alzheimer\u2019s disease dementia amyloid-\u03b2+ (n = 202). To assess longitudinal texture change across the Alzheimer\u2019s continuum, we used a multivariate mixed-effects spline model to calculate a \u2018disease time\u2019 for all timepoints based on amyloid PET and cognitive scores. This was used as a scale on which to compare the trajectories of biomarkers, including volume and texture of the hippocampus. The trajectories were modelled in a subset of the data: cognitively unimpaired amyloid-\u03b2\u2212 (n = 345); cognitively unimpaired amyloid-\u03b2+ (n = 173); mild cognitive impairment amyloid-\u03b2+ (n = 301); and Alzheimer\u2019s disease dementia amyloid-\u03b2+ (n = 161). We identified a difference in texture component 4 at the earliest stage of Alzheimer\u2019s disease, between cognitively unimpaired amyloid-\u03b2\u2212 and cognitively unimpaired amyloid-\u03b2+ older adults (Cohen\u2019s d = 0.23, Padj = 0.014). Differences in additional texture components and hippocampal volume emerged later in the disease continuum alongside the onset of cognitive impairment (d = 0.30\u20131.22, Padj &amp;lt; 0.002). Longitudinal modelling of the texture trajectories revealed that, while most elements of texture developed over the course of the disease, noise reduced sensitivity for tracking individual textural change over time. Critically, however, texture provided additional information than was provided by volume alone to more accurately predict future cognitive change (d = 0.32\u20130.63, Padj &amp;lt; 0.0001). Our results support the use of texture as a measure of brain health, sensitive to Alzheimer\u2019s disease pathology, at a time when therapeutic intervention may be most effective.<\/jats:p>","DOI":"10.1093\/braincomms\/fcad195","type":"journal-article","created":{"date-parts":[[2023,7,5]],"date-time":"2023-07-05T12:48:11Z","timestamp":1688561291000},"source":"Crossref","is-referenced-by-count":15,"title":["Longitudinal changes in hippocampal texture from healthy aging to Alzheimer\u2019s disease"],"prefix":"10.1093","volume":"5","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7699-648X","authenticated-orcid":false,"given":"Alfie","family":"Wearn","sequence":"first","affiliation":[{"name":"Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University , Montreal, QC, Canada H3A 2B4"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8432-7021","authenticated-orcid":false,"given":"Lars Lau","family":"Raket","sequence":"additional","affiliation":[{"name":"Clinical Memory Research Unit, Department of Clinical Sciences, Lund University , Lund SE-221 00 , Sweden"},{"name":"Novo Nordisk A\/S , S\u00f8borg 2860 , Denmark"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"D Louis","family":"Collins","sequence":"additional","affiliation":[{"name":"Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University , Montreal, QC, Canada H3A 2B4"},{"name":"McConnell Brain Imaging Centre, McGill University , Montreal, QC, Canada H3A 2B4"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1530-8916","authenticated-orcid":false,"given":"R Nathan","family":"Spreng","sequence":"additional","affiliation":[{"name":"Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University , Montreal, QC, Canada H3A 2B4"},{"name":"McConnell Brain Imaging Centre, McGill University , Montreal, QC, Canada H3A 2B4"},{"name":"Departments of Psychology and Psychiatry, McGill University , Montreal, QC, Canada H3A 2B4"},{"name":"Douglas Mental Health University Institute , Verdun, QC, Canada H4H 1R3"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"name":"for the Alzheimer\u2019s Disease Neuroimaging Initiative","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2023,7,5]]},"reference":[{"issue":"11","key":"2023071716501517900_fcad195-B1","doi-asserted-by":"crossref","first-page":"1055","DOI":"10.1002\/hipo.20573","article-title":"Hippocampal volume and asymmetry in mild cognitive impairment and Alzheimer\u2019s disease: Meta-analyses of MRI 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