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Segmentations were performed using a trained semantic segmentation model.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Statistical Tests<\/jats:title>\n                    <jats:p>\n                      Linear Mixed Model with continuous dependent variables and fixed effects. Models included a random intercept for participants. Statistical significance was defined as\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u20090.05.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      The method enabled volumetric analysis of gastric content from 3D breath\u2010hold static acquisition and time\u2010resolved quantification of peristaltic parameters from real\u2010time FLASH2 imaging at high temporal resolution (here 6.24\u2009fps). Water emptied rapidly and exponentially (\n                      <jats:italic>t<\/jats:italic>\n                      <jats:sub>1\/2<\/jats:sub>\n                      \u2009=\u200914.77\u2009\u00b1\u200910.55\u2009min), while juice showed slower emptying (\n                      <jats:italic>t<\/jats:italic>\n                      <jats:sub>1\/2<\/jats:sub>\n                      \u2009=\u200964.24\u2009\u00b1\u200911.87\u2009min). Contraction frequencies (fasted: 2.76\u2009\u00b1\u20090.43\u2009cpm, fed: 2.89\u2009\u00b1\u20090.43\u2009cpm) and velocities (fasted: 1.67\u2009\u00b1\u20090.38\u2009mm\/s, fed: 1.72\u2009\u00b1\u20090.37\u2009mm\/s) were within physiological ranges, with fasting conditions characterized by stronger occlusion compared to the fed. Measurements taken from three patients proved that the workflow could be used in a clinical context.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Data Conclusion<\/jats:title>\n                    <jats:p>Real\u2010time MRI with AI\u2010based analysis enabled quantitative assessment of gastric emptying and motility, revealing physiological peristaltic parameters and state\u2010dependent differences in occlusion.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Evidence Level<\/jats:title>\n                    <jats:p>2.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Technical Efficacy<\/jats:title>\n                    <jats:p>Stage 1.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/jmri.70243","type":"journal-article","created":{"date-parts":[[2026,2,6]],"date-time":"2026-02-06T08:05:32Z","timestamp":1770365132000},"page":"1482-1495","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Quantitative Real\u2010Time\n                    <scp>MRI<\/scp>\n                    for the Assessment of Gastric Motility"],"prefix":"10.1002","volume":"63","author":[{"ORCID":"https:\/\/orcid.org\/0009-0002-0469-820X","authenticated-orcid":false,"given":"Lydia","family":"Neubauer","sequence":"first","affiliation":[{"name":"Department of Biopharmaceutics and Pharmaceutical Technology, Institute of Pharmacy University of Greifswald  Greifswald Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Leonie","family":"Forstreuter","sequence":"additional","affiliation":[{"name":"Department of Biopharmaceutics and Pharmaceutical Technology, Institute of Pharmacy 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