{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,29]],"date-time":"2026-09-29T09:15:14Z","timestamp":1790673314084,"version":"4.1.0"},"reference-count":81,"publisher":"Wiley","issue":"2","license":[{"start":{"date-parts":[[2019,8,23]],"date-time":"2019-08-23T00:00:00Z","timestamp":1566518400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"funder":[{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Magnetic Resonance in Med"],"published-print":{"date-parts":[[2020,2]]},"abstract":"<jats:sec><jats:title>Purpose<\/jats:title><jats:p>Quantitative myocardial perfusion mapping has advantages over qualitative assessment, including the ability to detect global flow reduction. However, it is not clinically available and remains a research tool. Building upon the previously described imaging sequence, this study presents algorithm and implementation of an automated solution for inline perfusion flow mapping with step by step performance characterization.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>Proposed workflow consists of motion correction (MOCO), arterial input function blood detection, intensity to gadolinium concentration conversion, and pixel\u2010wise mapping. A distributed kinetics model, blood\u2010tissue exchange model, is implemented, computing pixel\u2010wise maps of myocardial blood flow (mL\/min\/g), permeability\u2010surface\u2010area product (mL\/min\/g), blood volume (mL\/g), and interstitial volume (mL\/g).<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>Thirty healthy subjects (11 men; 26.4 \u00b1 10.4 years) were recruited and underwent adenosine stress perfusion cardiovascular MR. Mean MOCO quality score was 3.6 \u00b1 0.4 for stress and 3.7 \u00b1 0.4 for rest. Myocardial Dice similarity coefficients after MOCO were significantly improved (<jats:italic>P<\/jats:italic> &lt; 1e\u20106), 0.87 \u00b1 0.05 for stress and 0.86 \u00b1 0.06 for rest. Arterial input function peak gadolinium concentration was 4.4 \u00b1 1.3 mmol\/L at stress and 5.2 \u00b1 1.5 mmol\/L at rest. Mean myocardial blood flow at stress and rest were 2.82 \u00b1 0.47 mL\/min\/g and 0.68 \u00b1 0.16 mL\/min\/g, respectively. The permeability\u2010surface\u2010area product was 1.32 \u00b1 0.26 mL\/min\/g at stress and 1.09 \u00b1 0.21 mL\/min\/g at rest (<jats:italic>P<\/jats:italic> &lt; 1e\u20103). Blood volume was 12.0 \u00b1 0.8 mL\/100 g at stress and 9.7 \u00b1 1.0 mL\/100 g at rest (<jats:italic>P<\/jats:italic> &lt; 1e\u20109), indicating good adenosine vasodilation response. Interstitial volume was 20.8 \u00b1 2.5 mL\/100 g at stress and 20.3 \u00b1 2.9 mL\/100 g at rest (<jats:italic>P<\/jats:italic> = 0.50).<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusions<\/jats:title><jats:p>An inline perfusion flow mapping workflow is proposed and demonstrated on normal volunteers. Initial evaluation demonstrates this fully automated solution for the respiratory MOCO, arterial input function left ventricle mask detection, and pixel\u2010wise mapping, from free\u2010breathing myocardial perfusion imaging.<\/jats:p><\/jats:sec>","DOI":"10.1002\/mrm.27954","type":"journal-article","created":{"date-parts":[[2019,8,23]],"date-time":"2019-08-23T10:05:53Z","timestamp":1566554753000},"page":"712-730","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":46,"title":["Automatic in\u2010line quantitative myocardial perfusion mapping: Processing algorithm and implementation"],"prefix":"10.1002","volume":"83","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4561-5530","authenticated-orcid":false,"given":"Hui","family":"Xue","sequence":"first","affiliation":[{"name":"National Heart, Lung and Blood Institute National Institutes of Health Bethesda 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