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Their distinct spatial distributions, namely periventricular versus deep WMH, may differ by underlying age-related and pathobiological processes contributing to cognitive decline. We aimed to identify the spatial patterns of WMH using the 4-scale Fazekas visual assessment and explore their differential association with age, vascular health, AD imaging markers, namely amyloid and tau burden, and cognition. Because our study consisted of scans from GE and Siemens scanners with different resolutions, we also investigated inter-scanner reproducibility and combinability of WMH measurements on imaging.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We identified 1144 participants from the Mayo Clinic Study of Aging consisting of a population-based sample from Olmsted County, Minnesota with available structural magnetic resonance imaging (MRI), amyloid, and tau positron emission tomography (PET). WMH distribution patterns were assessed on FLAIR-MRI, both 2D axial and 3D, using Fazekas ratings of periventricular and deep WMH severity. We compared the association of periventricular and deep WMH scales with vascular risk factors, amyloid-PET, and tau-PET standardized uptake value ratio, automated WMH volume, and cognition using Pearson partial correlation after adjusting for age. We also evaluated vendor compatibility and reproducibility of the Fazekas scales using intraclass correlations (ICC).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Periventricular and deep WMH measurements showed similar correlations with age, cardiometabolic conditions score (vascular risk), and cognition, (\n                      <jats:italic>p<\/jats:italic>\n                      \u2009&lt;\u20090.001). Both periventricular WMH and deep WMH showed weak associations with amyloidosis (\n                      <jats:italic>R<\/jats:italic>\n                      \u2009=\u20090.07,\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u2009&lt;\u20090.001), and none with tau burden. We found substantial agreement between data from the two scanners for Fazekas measurements (ICC\u2009=\u20090.82 and 0.74). The automated WMH volume had high discriminating power for identifying participants with Fazekas\u2009\u2265\u20092 (area under curve\u2009=\u20090.97) and showed poor correlation with amyloid and tau PET markers similar to the visual grading.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>Our study investigated risk factors underlying WMH spatial patterns and their impact on global cognition, with no discernible differences between periventricular and deep WMH. We observed minimal impact of amyloidosis on WMH severity. These findings, coupled with enhanced inter-scanner reproducibility of WMH data, suggest the combinability of inter-scanner data assessed by harmonized protocols in the context of vascular contributions to cognitive impairment and dementia biomarker research.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1186\/s13195-024-01525-5","type":"journal-article","created":{"date-parts":[[2024,7,10]],"date-time":"2024-07-10T00:02:27Z","timestamp":1720569747000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":40,"title":["Can white matter hyperintensities based Fazekas visual assessment scales inform about Alzheimer\u2019s disease pathology in the population?"],"prefix":"10.1186","volume":"16","author":[{"given":"Aishwarya","family":"Pradeep","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sheelakumari","family":"Raghavan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Scott A.","family":"Przybelski","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gregory M.","family":"Preboske","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Christopher G.","family":"Schwarz","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Val J.","family":"Lowe","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"David S.","family":"Knopman","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ronald C.","family":"Petersen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"suffix":"Jr","given":"Clifford R.","family":"Jack","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jonathan","family":"Graff-Radford","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Petrice M.","family":"Cogswell","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Prashanthi","family":"Vemuri","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2024,7,10]]},"reference":[{"key":"1525_CR1","doi-asserted-by":"publisher","first-page":"689","DOI":"10.1016\/S1474-4422(10)70104-6","volume":"9","author":"L Pantoni","year":"2010","unstructured":"Pantoni L. 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