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In this study, we present a novel postprocessing pipeline for vascular territorial imaging of cerebral arteries based on a noncontrast enhanced time\u2010resolved 4D magnetic resonance angiography (MRA).<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>Eight healthy participants, 1 Moyamoya patient, and 1 arteriovenous malformations patient were recruited. Territorial segmentation and relative blood flow rate calculations of cerebral arteries including left and right middle cerebral arteries and left and right posterior cerebral arteries were carried out based on the 4D MRA\u2010derived arterial arrival time maps of intracranial vessels.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>Among healthy young subjects, the average relative blood flow rate values corresponding to left and right middle cerebral arteries and left and right posterior cerebral arteries were 35.9 \u00b1 5.9%, 32.9 \u00b1 7.5%, 15.4 \u00b1 3.8%, and 15.9 \u00b1 2.5%, respectively. Excellent agreement was observed between relative blood flow rate values obtained from the proposed 4D MRA\u2010based method and reference 2D phase contrast MRI. Abnormal cerebral circulations were visualized and quantified on both patients using the developed technique.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>The vascular territorial imaging technique developed in this study allowed for the generation of territorial maps with user\u2010defined level of details within a clinically feasible scan time, and as such may provide useful information to assess cerebral circulation balance in different pathologies.<\/jats:p><\/jats:sec>","DOI":"10.1002\/mrm.28623","type":"journal-article","created":{"date-parts":[[2020,12,22]],"date-time":"2020-12-22T13:35:48Z","timestamp":1608644148000},"page":"2735-2746","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Semiautomatic cerebrovascular territory mapping based on dynamic ASL MR angiography without vessel\u2010encoded labeling"],"prefix":"10.1002","volume":"85","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3729-851X","authenticated-orcid":false,"given":"Soroush","family":"Heidari Pahlavian","sequence":"first","affiliation":[{"name":"USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine University of Southern California Los Angeles CA USA"},{"name":"Department of Neurology University of Southern California Los Angeles CA USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Oren","family":"Geri","sequence":"additional","affiliation":[{"name":"Razor Labs Tel Aviv Israel"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jonathan","family":"Russin","sequence":"additional","affiliation":[{"name":"Department of Neurosurgery Keck School of Medicine, University of Southern California Los Angeles CA USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Samantha J.","family":"Ma","sequence":"additional","affiliation":[{"name":"USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine University of Southern California Los Angeles CA USA"},{"name":"Department of Neurology University of Southern California Los Angeles CA USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Arun","family":"Amar","sequence":"additional","affiliation":[{"name":"Department of Neurosurgery Keck School of Medicine, University of Southern California Los Angeles CA USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0840-7062","authenticated-orcid":false,"given":"Danny J. 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