{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,18]],"date-time":"2026-08-18T05:36:12Z","timestamp":1787031372869,"version":"build-2736575974"},"reference-count":34,"publisher":"Baishideng Publishing Group Inc.","issue":"7","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["World J Cardiol"],"abstract":"<jats:p>BACKGROUND<\/jats:p>\n                  <jats:p>A key cardiac magnetic resonance (CMR) challenge is breath-holding duration, difficult for cardiac patients.<\/jats:p>\n                  <jats:p>AIM<\/jats:p>\n                  <jats:p>To evaluate whether artificial intelligence-assisted compressed sensing CINE (AI-CS-CINE) reduces image acquisition time of CMR compared to conventional CINE (C-CINE).<\/jats:p>\n                  <jats:p>METHODS<\/jats:p>\n                  <jats:p>Cardio-oncology patients (n  = 60) and healthy volunteers (n  = 29) underwent sequential C-CINE and AI-CS-CINE with a 1.5-T scanner. Acquisition time, visual image quality assessment, and biventricular metrics (end-diastolic volume, end-systolic volume, stroke volume, ejection fraction, left ventricular mass, and wall thickness) were analyzed and compared between C-CINE and AI-CS-CINE with Bland\u2013Altman analysis, and calculation of intraclass coefficient (ICC).<\/jats:p>\n                  <jats:p>RESULTS<\/jats:p>\n                  <jats:p>In 89 participants (58.5 \u00b1 16.8 years, 42 males, 47 females), total AI-CS-CINE acquisition and reconstruction time (37 seconds) was 84% faster than C-CINE (238 seconds). C-CINE required repeats in 23% (20\/89) of cases (approximately 8 minutes lost), while AI-CS-CINE only needed one repeat (1%; 2 seconds lost). AI-CS-CINE had slightly lower contrast but preserved structural clarity. Bland-Altman plots and ICC (0.73 \u2264 r  \u2264 0.98) showed strong agreement for left ventricle (LV) and right ventricle (RV) metrics, including those in the cardiac amyloidosis subgroup (n  = 31). AI-CS-CINE enabled faster, easier imaging in patients with claustrophobia, dyspnea, arrhythmias, or restlessness. Motion-artifacted C-CINE images were reliably interpreted from AI-CS-CINE.<\/jats:p>\n                  <jats:p>CONCLUSION<\/jats:p>\n                  <jats:p>AI-CS-CINE accelerated CMR image acquisition and reconstruction, preserved anatomical detail, and diminished impact of patient-related motion. Quantitative AI-CS-CINE metrics agreed closely with C-CINE in cardio-oncology patients, including the cardiac amyloidosis cohort, as well as healthy volunteers regardless of left and right ventricular size and function. AI-CS-CINE significantly enhanced CMR workflow, particularly in challenging cases. The strong analytical concordance underscores reliability and robustness of AI-CS-CINE as a valuable tool.<\/jats:p>","DOI":"10.4330\/wjc.v17.i7.108745","type":"journal-article","created":{"date-parts":[[2025,7,22]],"date-time":"2025-07-22T01:58:53Z","timestamp":1753149533000},"source":"Crossref","is-referenced-by-count":4,"title":["Artificial intelligence-assisted compressed sensing CINE enhances the workflow of cardiac magnetic resonance in challenging patients"],"prefix":"10.4330","volume":"17","author":[{"given":"Huaijun","family":"Wang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Anne","family":"Schmieder","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mary","family":"Watkins","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Pengjun","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Joshua","family":"Mitchell","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"S Zyad","family":"Qamer","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gregory","family":"Lanza","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"2060","published-online":{"date-parts":[[2025,7,26]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","DOI":"10.1055\/a-0999-5716"},{"key":"B2","doi-asserted-by":"publisher","DOI":"10.1186\/s12968-020-00610-6"},{"key":"B3","doi-asserted-by":"publisher","DOI":"10.2214\/AJR.19.22076"},{"key":"B4","doi-asserted-by":"publisher","DOI":"10.1161\/CIRCIMAGING.122.014068"},{"key":"B5","doi-asserted-by":"publisher","DOI":"10.13104\/imri.2021.25.4.252"},{"key":"B6","doi-asserted-by":"publisher","DOI":"10.1148\/ryct.210109"},{"key":"B7","doi-asserted-by":"publisher","DOI":"10.1148\/radiol.223008"},{"key":"B8","doi-asserted-by":"publisher","DOI":"10.1002\/jmri.27436"},{"key":"B9","doi-asserted-by":"publisher","DOI":"10.1002\/mrm.21477"},{"key":"B10","doi-asserted-by":"publisher","DOI":"10.1259\/bjr.20150487"},{"key":"B11","doi-asserted-by":"publisher","DOI":"10.1007\/s00330-021-07830-z"},{"key":"B12","doi-asserted-by":"publisher","DOI":"10.1002\/mrm.21391"},{"key":"B13","doi-asserted-by":"publisher","DOI":"10.1148\/radiol.2020192173"},{"key":"B14","doi-asserted-by":"publisher","DOI":"10.1002\/jmri.28899"},{"key":"B15","doi-asserted-by":"publisher","DOI":"10.1002\/jmri.26534"},{"key":"B16","doi-asserted-by":"publisher","DOI":"10.1002\/mrm.27480"},{"key":"B17","doi-asserted-by":"publisher","DOI":"10.1002\/mrm.28420"},{"key":"B18","doi-asserted-by":"publisher","DOI":"10.1177\/096228029900800204"},{"key":"B19","doi-asserted-by":"crossref","unstructured":"Bland JM, Altman DG. 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