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TM was segmented using a convolutional neural network trained in ADNI and externally validated in ARIC. Radiomic features were reduced using least absolute shrinkage and selection operator\u2010penalized Cox models to generate a composite score. Multivariable Cox regression adjusted for demographics,\n                      <jats:italic>apolipoprotein\u00a0E<\/jats:italic>\n                      \u03b54, baseline cognition, body mass index, and physical performance.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>RESULTS<\/jats:title>\n                    <jats:p>Higher TM radiomic scores were associated with increased dementia risk in ADNI (hazard ratio per SD, 1.32) and ARIC (1.64). Smaller TM CSA predicted dementia in ADNI but not ARIC.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>DISCUSSION<\/jats:title>\n                    <jats:p>TM texture patterns from routine brain MRI are associated with dementia risk, supporting TM phenotyping as a scalable marker of systemic biological vulnerability.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/alz.71622","type":"journal-article","created":{"date-parts":[[2026,8,6]],"date-time":"2026-08-06T11:00:28Z","timestamp":1786014028000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Temporalis muscle biomarkers from routine brain MRI and risk of dementia in two independent cohorts"],"prefix":"10.1002","volume":"22","author":[{"given":"Kamyar","family":"Moradi","sequence":"first","affiliation":[{"name":"Russell H. 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