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Transl. Med."],"published-print":{"date-parts":[[2026,3,25]]},"abstract":"<jats:p>Relentless mechanical work of the heart is powered by continuous oxygen consumption. How the heart uses oxygen is a defining feature of its health. Invasive studies have established that impaired oxygen consumption by the myocardium predicts contractile dysfunction and adverse outcomes. Despite its importance, noninvasive quantification of myocardial oxygen use remains limited. Magnetic resonance imaging (MRI) signal is known to be sensitive to blood oxygenation and has the potential to quantify myocardial oxygen consumption noninvasively, without exogenous contrast agents and free of ionizing radiation. However, its clinical translation has been impeded by the need for complex biophysical calibration, vulnerability to imaging artifacts and consistent vital motions, and the requirement of lengthy acquisition times. Here, we introduce a rapid, self-calibrated cardiac MRI framework that overcomes these barriers through high-resolution, motion-resolved coronary sinus oximetry, which can quantify myocardial oxygen extraction of the whole heart within 3 minutes. We optimized the imaging parameters via numerical simulations and validated them against invasive coronary sinus catheterization in a porcine model. We combined the method with clinical MRI sequences and demonstrated the feasibility of quantifying myocardial oxygen consumption and myocardial oxygen efficiency in patients with and without heart failure secondary to myocardial infarction in a single institution. This needle-free approach establishes a practical framework for noninvasive characterization of myocardial oxygen metabolism. It holds the potential to facilitate early disease detection, inform personalized therapeutic strategies, and guide the development of cardiometabolic therapies aimed at addressing the ongoing heart failure epidemic.<\/jats:p>","DOI":"10.1126\/scitranslmed.ady6269","type":"journal-article","created":{"date-parts":[[2026,3,25]],"date-time":"2026-03-25T17:58:21Z","timestamp":1774461501000},"update-policy":"https:\/\/doi.org\/10.34133\/aaas_crossmark","source":"Crossref","is-referenced-by-count":0,"title":["Quantifying myocardial oxygen consumption and efficiency with motion-resolved cardiac MRI"],"prefix":"10.1126","volume":"18","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5616-0431","authenticated-orcid":true,"given":"Li-Ting","family":"Huang","sequence":"first","affiliation":[{"name":"Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA."},{"name":"Department of Medical Imaging, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan 704, Taiwan."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-8866-7716","authenticated-orcid":true,"given":"Chia-Chi","family":"Yang","sequence":"additional","affiliation":[{"name":"Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8626-5824","authenticated-orcid":true,"given":"Guan","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Radiology, First Hospital of China Medical University, Shenyang 110001, Liaoning, China."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-0177-8804","authenticated-orcid":true,"given":"Henghui","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Radiology, First Hospital of China Medical University, Shenyang 110001, Liaoning, China."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-3610-2954","authenticated-orcid":true,"given":"Ranran","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Radiology, First Hospital of China Medical University, Shenyang 110001, Liaoning, China."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8911-7907","authenticated-orcid":true,"given":"Hao","family":"Ho","sequence":"additional","affiliation":[{"name":"Department of Statistics, University of California at Los Angeles, Los Angeles, CA 90095, USA."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2332-170X","authenticated-orcid":true,"given":"Archana","family":"Malagi","sequence":"additional","affiliation":[{"name":"Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-2890-2442","authenticated-orcid":true,"given":"Yuheng","family":"Huang","sequence":"additional","affiliation":[{"name":"Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA."},{"name":"Cardiovascular Imaging Research Center, Medical Imaging Research Institute, Department of Radiology &amp; 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