{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,29]],"date-time":"2026-09-29T17:49:28Z","timestamp":1790704168881,"version":"4.1.0"},"reference-count":27,"publisher":"Oxford University Press (OUP)","issue":"4","license":[{"start":{"date-parts":[[2025,10,25]],"date-time":"2025-10-25T00:00:00Z","timestamp":1761350400000},"content-version":"vor","delay-in-days":24,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100010454","name":"Bracco Diagnostics","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100010454","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,10,6]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Aims<\/jats:title>\n                    <jats:p>Gould\u2019s simplified retention model (GSRM), as implemented in the HeartSee software, demonstrates 10% same-day test-retest precision for PET-CT myocardial perfusion using a 50 or 20\u2005mL\/min Rb-82 infusions. HeartSee-GSRM also accurately quantifies resting myocardial blood flow (rMBF) in transmural scar (0.26\u2005mL\/min\/g), aligning with reference standards. However, the impact for varying infusion rates on precision and accuracy of a 1-tissue compartment model (1-TCM) as implemented within 4DM software remains unclear. We assessed whether varying infusion rates of Rb-82 impacts 1-TCM precision and accuracy.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods and results<\/jats:title>\n                    <jats:p>Ninety-eight volunteers (Normals, Clinicals, and Infarcts), underwent 3D PET-CT stress testing. Three resting scans and two stress scans were performed with randomized fast (F) 50\u2005mL\/min or slow (S) 20\u2005mL\/min Rb-82 infusions. rMBF and stress MBF (sMBF) were calculated using 4DM software (1-TCM). Repeatability coefficients (RC) and coefficients of variance (COV) were calculated. Accuracy was assessed by comparing rMBF in infarcted myocardium (from 1-TCM and GSRM) against established reference standard for transmural myocardial scar (TMS). Fast infusion yielded better precision. RC was lower for F-F vs. S-S resting pairs (24.3% vs. 32.9%), and COV was lower (12.9% vs. 17.4%, P = 0.03). No difference in rMBF or sMBF was found between infusion rates (rMBF: 0.93 vs. 0.94\u2005mL\/min\/g; sMBF: 2.23 vs. 2.30\u2005mL\/min\/g). HeartSee GSRM produced rMBF values consistent with TMS (&amp;lt;0.30\u2005mL\/min\/g), while 4DM 1-TCM overestimated rMBF (Fast: 0.79\u202f\u00b1\u202f0.33; Slow: 0.82\u202f\u00b1\u202f0.27\u202fmL\/min\/g, P = 0.791), for both infusion profiles.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>Fast infusion improves 4DM 1-TCM precision, but 4DM 1-TCM overestimates rMBF in TMS regardless of infusion rate. HeartSee GSRM remains accurate and precise across profiles.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/ehjimp\/qyaf132","type":"journal-article","created":{"date-parts":[[2025,10,23]],"date-time":"2025-10-23T12:22:21Z","timestamp":1761222141000},"source":"Crossref","is-referenced-by-count":1,"title":["The impact of fast vs. slow rubidium-82 infusion profile on precision and accuracy of PET myocardial blood flow perfusion metrics using a 1-tissue compartment model"],"prefix":"10.1093","volume":"3","author":[{"ORCID":"https:\/\/orcid.org\/0009-0004-9420-7308","authenticated-orcid":false,"given":"Adrienne","family":"Koos","sequence":"first","affiliation":[{"name":"Department of Internal Medicine, Ochsner Health , 1514 Jefferson Hwy, Jefferson, LA 70121 ,","place":["USA"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Richard V","family":"Milani","sequence":"additional","affiliation":[{"name":"Sutter Health, Center for Healthcare Innovation , San Francisco, CA ,","place":["USA"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2361-5409","authenticated-orcid":false,"given":"Cruz","family":"Velasco-Gonzalez","sequence":"additional","affiliation":[{"name":"Ochsner Center for Outcomes Research, Ochsner Health , New Orleans, LA ,","place":["USA"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9637-9507","authenticated-orcid":false,"given":"Daniel P","family":"Morin","sequence":"additional","affiliation":[{"name":"Department of Cardiovascular Diseases, John Ochsner Heart and Vascular Institute , New Orleans, LA ,","place":["USA"]},{"name":"Queensland University School of Medicine, Ochsner Clinical School , New Orleans, LA ,","place":["USA"]},{"name":"Division of Electrophysiology, University of California , San Francisco, CA 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