{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,14]],"date-time":"2026-10-14T16:45:49Z","timestamp":1791996349676,"version":"4.4.0"},"reference-count":37,"publisher":"Wiley","issue":"5","license":[{"start":{"date-parts":[[2026,7,25]],"date-time":"2026-07-25T00:00:00Z","timestamp":1784937600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,7,25]],"date-time":"2026-07-25T00:00:00Z","timestamp":1784937600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Magnetic Resonance Imaging"],"published-print":{"date-parts":[[2026,11]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Cerebral microbleeds (CMBs) are a key imaging marker of cerebral amyloid angiopathy (CAA), but their individual spatial distribution and potential clustering remain poorly understood.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Purpose<\/jats:title>\n                    <jats:p>This study assessed whether CMBs exhibit patient\u2010specific, flow territory\u2010based clustering in sporadic (sCAA) and Dutch\u2010type hereditary CAA (D\u2010CAA). The arterial flow territory subdivision was chosen, considering the predilection of CMB location in the posterior cortex\u2014not limited to the occipital lobe\u2014and the prominent vascular role in CAA.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Study Type<\/jats:title>\n                    <jats:p>Retrospective cross\u2010sectional study.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Population<\/jats:title>\n                    <jats:p>Thirty\u2010three participants (17 (52%) female, 65\u2009\u00b1\u200912\u2009years old, 19 sCAA; 14 D\u2010CAA) without symptomatic intracerebral hemorrhage (sICH) and \u2265\u20091 CMB were included for the main analysis.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Field Strength\/Sequence<\/jats:title>\n                    <jats:p>3\u2009T MRI susceptibility\u2010weighted imaging, multi\u2010echo 3D gradient echo.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Assessment<\/jats:title>\n                    <jats:p>Spatial CMB patterns were evaluated by comparing observed versus expected CMB density within covariate\u2010matched subgroups, accounting for age, sex, CAA\u2010type, smoking, and hypertension. CMBs were manually annotated and assigned to six arterial flow territories (left\/right ACA, MCA, PCA) using a standardized atlas. A sensitivity analysis was performed on all participants (including sICH+ participants).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Statistical Tests<\/jats:title>\n                    <jats:p>Expected values were calculated by multiplying flow territory CMB proportions per covariate\u2010matched subgroup. Unweighted individual chi\u2010square statistics were calculated, and statistical significance was assessed via permutation testing (10,000 replications) per covariate group.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Across covariate\u2010matched subgroups, observed CMB counts significantly deviated from expected distributions, indicating substantial interindividual variability and within\u2010participant clustering (\n                      <jats:italic>\u03c7<\/jats:italic>\n                      <jats:sup>2<\/jats:sup>\n                      \u2009=\u20096920). The effect remained significant when including sICH+ participants (\n                      <jats:italic>\u03c7<\/jats:italic>\n                      <jats:sup>2<\/jats:sup>\n                      \u2009=\u2009102,027,\n                      <jats:italic>n<\/jats:italic>\n                      \u2009=\u200985; 44 sCAA; 41 D\u2010CAA). CMB densities differed across flow territories, with highest median densities in the right PCA, right MCA, and left PCA (0.173 (IQR\u2009=\u20090.387), 0.121 (IQR\u2009=\u20090.238), and 0.113 (IQR\u2009=\u20090.389) counts per cm\n                      <jats:sup>3<\/jats:sup>\n                      , respectively).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Data Conclusion<\/jats:title>\n                    <jats:p>These findings indicate CMBs in CAA are not identically distributed but show patient\u2010specific clustering within flow territories, suggesting variable regional vulnerability, potentially influenced by local pathology or vascular anatomy.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Evidence Level<\/jats:title>\n                    <jats:p>1.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Technical Efficacy<\/jats:title>\n                    <jats:p>Stage 2.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/jmri.70454","type":"journal-article","created":{"date-parts":[[2026,7,25]],"date-time":"2026-07-25T21:34:47Z","timestamp":1785015287000},"page":"1241-1249","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Clustering of Cerebral Microbleeds in Cerebral Amyloid Angiopathy: A Flow Territory\u2010Based Analysis"],"prefix":"10.1002","volume":"64","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1463-0997","authenticated-orcid":false,"given":"Manon R.","family":"Schipper","sequence":"first","affiliation":[{"name":"Department of Radiology Leiden University Medical Center  Leiden the Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Reinier G. J.","family":"van der Zwet","sequence":"additional","affiliation":[{"name":"Department of Neurology Leiden University Medical Center  Leiden the Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4283-0259","authenticated-orcid":false,"given":"Jelle J.","family":"Goeman","sequence":"additional","affiliation":[{"name":"Department of Biomedical Data Sciences Leiden University Medical Center  Leiden the Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3408-9379","authenticated-orcid":false,"given":"Thijs W.","family":"van Harten","sequence":"additional","affiliation":[{"name":"Department of Radiology Leiden University Medical Center  Leiden the Netherlands"},{"name":"Department of Neurology Massachusetts General Hospital, Harvard Medical School  Boston Massachusetts USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Emma A.","family":"Koemans","sequence":"additional","affiliation":[{"name":"Department of Neurology Leiden University Medical Center  Leiden the Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Marieke J. 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