{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,21]],"date-time":"2026-10-21T18:41:15Z","timestamp":1792608075520,"version":"4.5.0"},"reference-count":73,"publisher":"Ovid Technologies (Wolters Kluwer Health)","issue":"11","content-domain":{"domain":["www.ahajournals.org"],"crossmark-restriction":true},"short-container-title":["ATVB"],"published-print":{"date-parts":[[2026,11]]},"abstract":"<jats:sec>\n                    <jats:title>BACKGROUND:<\/jats:title>\n                    <jats:p>Accelerated vascular aging, assessed as artificial intelligence\u2013based vascular age (AIVA), is associated with small vessel disease that may impact brain structure and neuropsychological function.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>METHODS:<\/jats:title>\n                    <jats:p>In a cross-section of Framingham Heart Study participants, AIVA was estimated using a validated convolutional neural network trained to predict carotid-femoral pulse wave velocity from a normalized pressure waveform. Brain structure was assessed using magnetic resonance imaging with diffusion tensor imaging, and neuropsychological function was assessed using a standardized test battery. Analyses included magnetic resonance imaging (N=2313) and neuropsychological (N=3001) samples. We used multivariable linear and logistic regression to relate AIVA to brain structural and neuropsychological functional measures.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>RESULTS:<\/jats:title>\n                    <jats:p>\n                      The mean\u00b1SD age across participants was 62\u00b111 years; 56% were women. In multivariable models, higher AIVA was associated with worse markers of cerebral small vessel disease (mean white matter free water:\n                      <jats:italic toggle=\"yes\">\u03b2<\/jats:italic>\n                      [per SD], 0.09 [95% CI, 0.04\u20130.14];\n                      <jats:italic toggle=\"yes\">P<\/jats:italic>\n                      &lt;0.001; peak width of skeletonized mean diffusivity:\n                      <jats:italic toggle=\"yes\">\u03b2<\/jats:italic>\n                      , 0.05 [95% CI, 0.00\u20130.10];\n                      <jats:italic toggle=\"yes\">P<\/jats:italic>\n                      =0.045; white matter hyperintensity volume:\n                      <jats:italic toggle=\"yes\">\u03b2<\/jats:italic>\n                      , 0.08 [95% CI, 0.03\u20130.12];\n                      <jats:italic toggle=\"yes\">P<\/jats:italic>\n                      &lt;0.001) and higher odds of cerebrovascular injury (presence of extensive white matter hyperintensities: odds ratio [per SD], 1.22 [95% CI, 1.02\u20131.47];\n                      <jats:italic toggle=\"yes\">P<\/jats:italic>\n                      =0.03; presence of brain infarcts: odds ratio, 1.44 [95% CI, 1.02\u20132.04];\n                      <jats:italic toggle=\"yes\">P<\/jats:italic>\n                      =0.04). In addition, higher AIVA was associated with worse performance on Trails B-A (\n                      <jats:italic toggle=\"yes\">\u03b2<\/jats:italic>\n                      , \u22120.05 [95% CI, \u22120.10 to \u22120.01];\n                      <jats:italic toggle=\"yes\">P<\/jats:italic>\n                      =0.03), similarities (\n                      <jats:italic toggle=\"yes\">\u03b2<\/jats:italic>\n                      , \u22120.06 [95% CI, \u22120.11 to \u22120.01];\n                      <jats:italic toggle=\"yes\">P<\/jats:italic>\n                      =0.02), and global cognition (\n                      <jats:italic toggle=\"yes\">\u03b2<\/jats:italic>\n                      ,\n                      <jats:italic toggle=\"yes\">\u2212<\/jats:italic>\n                      0.07 [95% CI, \u22120.12 to \u22120.03];\n                      <jats:italic toggle=\"yes\">P<\/jats:italic>\n                      =0.002) and higher odds of prevalent depressive symptoms (odds ratio, 1.24 [95% CI, 1.08\u20131.41];\n                      <jats:italic toggle=\"yes\">P<\/jats:italic>\n                      =0.002) and high Center for Epidemiologic Studies Depression Scale score (odds ratio, 1.20 [95% CI, 1.00\u20131.44];\n                      <jats:italic toggle=\"yes\">P<\/jats:italic>\n                      =0.047). Vascular brain injury markers partially mediated the associations of AIVA with global cognition score and presence of depressive symptoms.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>CONCLUSIONS:<\/jats:title>\n                    <jats:p>Peripheral pressure waveform AIVA may be a novel, noninvasive indicator of subclinical vascular brain injury and neuropsychological function.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1161\/atvbaha.126.325247","type":"journal-article","created":{"date-parts":[[2026,9,24]],"date-time":"2026-09-24T09:00:22Z","timestamp":1790240422000},"update-policy":"https:\/\/doi.org\/10.1161\/crossmarkpolicy","source":"Crossref","is-referenced-by-count":0,"title":["Associations of Brain Structure and Neuropsychological Function With Artificial Intelligence Estimates of Biological Vascular 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