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We additionally scanned three subjects who had prepregnancy diabetes or chronic hypertension.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Field Strength\/Sequence<\/jats:title>\n                    <jats:p>The subjects underwent UtA and placenta MRI using noncontrast angiography and 4D flow at 1.5T.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Assessment<\/jats:title>\n                    <jats:p>UtA anatomy was described based on 4D flow\u2010derived noncontrast angiography, while UtA flow properties were characterized by net flow, systolic\/mean\/diastolic velocity, PI and RI through examination of 4D flow data. PI and RI are standard hemodynamic parameters routinely reported on Doppler US.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Statistical Tests<\/jats:title>\n                    <jats:p>Spearman's rank correlation, Wilcoxon signed rank tests, and Bland\u2010Altman plots were used to preliminarily investigate the relationships between flow parameters, gestational age, and Doppler US. or<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      4D flow MRI and UtA flow quantification was feasible in all subjects. There was considerable heterogeneity in UtA geometry in each subject between left and right UtAs and between subjects. Mean 4D flow\u2010based parameters were: mean bilateral flow rate\u2009=\u2009605.6\u2009\u00b1\u2009220.5\u2009mL\/min, PI\u2009=\u20090.72\u2009\u00b1\u20090.2, and RI\u2009=\u20090.47\u2009\u00b1\u20090.1. Bilateral flow did not change with gestational age. We found that MRI differed from US in terms of lower PI (mean difference \u20100.1) and RI (mean difference\u2009&lt;\u2009\u20100.1) with Wilcoxon signed rank test\n                      <jats:italic>P<\/jats:italic>\n                      \u2009=\u20090.05 and\n                      <jats:italic>P<\/jats:italic>\n                      \u2009=\u20090.13, respectively.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Data Conclusion<\/jats:title>\n                    <jats:p>4D flow MRI is a feasible approach for describing UtA anatomy and flow in pregnant subjects.<\/jats:p>\n                    <jats:p>\n                      <jats:bold>Level of Evidence:<\/jats:bold>\n                    <\/jats:p>\n                    <jats:p>\n                      <jats:bold>Technical Efficacy:<\/jats:bold>\n                      Stage 1\n                    <\/jats:p>\n                    <jats:p>J. Magn. Reson. Imaging 2019;49:59\u201368.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/jmri.26229","type":"journal-article","created":{"date-parts":[[2018,11,3]],"date-time":"2018-11-03T04:11:41Z","timestamp":1541218301000},"page":"59-68","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":18,"title":["Assessment of uterine artery geometry and hemodynamics in human pregnancy with 4d flow mri and its correlation with doppler ultrasound"],"prefix":"10.1002","volume":"49","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7376-2810","authenticated-orcid":false,"given":"Eileen","family":"Hwuang","sequence":"first","affiliation":[{"name":"Department of Bioengineering University of Pennsylvania Philadelphia Pennsylvania USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Marta","family":"Vidorreta","sequence":"additional","affiliation":[{"name":"Siemens Healthineers Tarrytown New York USA"},{"name":"Department of Neurology Hospital of the University of Pennsylvania Philadelphia Pennsylvania USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nadav","family":"Schwartz","sequence":"additional","affiliation":[{"name":"Department of Obstetrics and Gynecology Hospital of the University of Pennsylvania Philadelphia Pennsylvania USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Brianna F.","family":"Moon","sequence":"additional","affiliation":[{"name":"Department of Bioengineering University of Pennsylvania Philadelphia Pennsylvania USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kirpal","family":"Kochar","sequence":"additional","affiliation":[{"name":"Drexel University College of Medicine Philadelphia Pennsylvania USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Matthew Dylan","family":"Tisdall","sequence":"additional","affiliation":[{"name":"Department of Radiology Hospital of the University of Pennsylvania Philadelphia Pennsylvania USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"John A.","family":"Detre","sequence":"additional","affiliation":[{"name":"Department of Neurology Hospital of the University of Pennsylvania Philadelphia Pennsylvania USA"},{"name":"Department of Radiology Hospital of the University of Pennsylvania Philadelphia Pennsylvania USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Walter R.T.","family":"Witschey","sequence":"additional","affiliation":[{"name":"Department of Radiology Hospital of the University of Pennsylvania Philadelphia Pennsylvania USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2018,11,3]]},"reference":[{"key":"e_1_2_6_2_1","doi-asserted-by":"publisher","DOI":"10.1542\/neo.5-6-e252"},{"key":"e_1_2_6_3_1","doi-asserted-by":"publisher","DOI":"10.1111\/micc.12080"},{"key":"e_1_2_6_4_1","doi-asserted-by":"publisher","DOI":"10.1002\/uog.15917"},{"key":"e_1_2_6_5_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.placenta.2016.04.002"},{"key":"e_1_2_6_6_1","doi-asserted-by":"publisher","DOI":"10.1002\/jmri.22119"},{"key":"e_1_2_6_7_1","doi-asserted-by":"publisher","DOI":"10.1002\/jmri.23632"},{"key":"e_1_2_6_8_1","doi-asserted-by":"publisher","DOI":"10.1186\/1532-429X-13-7"},{"key":"e_1_2_6_9_1","doi-asserted-by":"publisher","DOI":"10.1186\/s12968-015-0174-5"},{"key":"e_1_2_6_10_1","doi-asserted-by":"publisher","DOI":"10.1002\/uog.12371"},{"key":"e_1_2_6_11_1","doi-asserted-by":"publisher","DOI":"10.1002\/jmri.21561"},{"key":"e_1_2_6_12_1","first-page":"1041","volume-title":"Handbook of MRI pulse sequences","author":"Bernstein MA","year":"2004"},{"key":"e_1_2_6_13_1","doi-asserted-by":"publisher","DOI":"10.1002\/mrm.1910390218"},{"key":"e_1_2_6_14_1","doi-asserted-by":"publisher","DOI":"10.1002\/mrm.21778"},{"key":"e_1_2_6_15_1","unstructured":"BockJ KreherBW HennigJ MarklM.Optimized pre\u2010processing of time\u2010resolved 2D and 3D phase contrast MRI data. 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