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Funding Acknowledgements Type of funding sources: Private company. Main funding source(s): GE Healthcare. Background Myocardial blood flow (MBF) analysis using stress cardiac magnetic resonance (CMR) has been shown to detect obstructive coronary artery disease (CAD); however, evaluation of its diagnostic performance has primarily been limited to single-center studies. AQUA-MBF (Assessment of QUAntitative MBF using stress CMR) is an international study with the goal of assessing the diagnostic performance of stress MBF for the detection of CAD. In this study, we aim to determine how stress MBF assessment compared against visual analysis (VA) of stress CMR images for the detection of CAD. Methods. 144 individuals (89 (62%) men, age 62±16 years, 97 (68%) hypertension, 54 (38%) diabetes, 92 (64%) hyperlipidemia) from 9 centers who underwent dual sequence stress CMR (1.5T or 3.0T GE Healthcare) and also had either a coronary computed tomography angiography (CTA, n=31), invasive coronary angiogram (ICA, n=95), or low pre-test probability for CAD (n=18) were included. CAD was defined as the presence of: (1) a stenosis ≥50% in the left main coronary artery or ≥70% in the 1 major vessel based on ICA or CTA or (2) an invasive fractional flow reserve (FFR) ≤ 0.8. Absence of obstructive coronary disease (NOCAD) was defined as a no history of myocardial infarction and stenosis <50% by ICA or CTA, 50–70% stenosis with FFR>0.8, or a young individual with no cardiac risk factors. Myocardial perfusion imaging was performed during first pass perfusion of a gadolinium-based contrast agent following the administration of adenosine or regadenoson with a low-resolution image acquired to assess the arterial input function and 2–3 short axis slices acquired to assess myocardial perfusion. VA was performed by 2 experienced cardiologists who assigned a grade of 1–5 based on the probability a study was abnormal. Stress MBF values were determined for each of the 16 myocardial segments using Fermi deconvolution (CircleCVI). The global stress MBF was calculated as the average value of two segments with the lowest values from each of the three coronary artery territories. Unpaired t-test was used to compare stress MBF values between CAD vs NOCAD. Receiver-operating characteristics curves were used to determine diagnostic performance. Results. 60 patients had CAD (20: 1-vessel, 26: 2-vessel, and 14: 3-vessel) (Figure 1A) while 84 had NOCAD (Figure 1B). The global stress MBF in CAD was lower than in NOCAD (1.63±0.52ml/g/min vs 2.41±0.68ml/g/min, p<0.0001) (Figure 2A). Stress MBF had a higher AUC than VA (reader 1 – 0.83 vs 0.73, p = 0.07: reader 2–0.83 vs 0.71, p = 0.02). The optimal stress MBF cut-off value for detecting CAD was 2.05ml/g/min (Figure 2B). Conclusions. In this multicenter study, we show that global stress MBF reported as a single value can identify patients with CAD at least as accurately as VA performed by physicians experienced in the interpretation of stress CMR images.

Background Prasugrel and ticagrelor are both effective anti-platelet drugs for patients with acute coronary syndrome. However, there has been limited data on the direct comparison of prasugrel and ticagrelor until the recent ISAR-REACT 5 trial. Purpose To compare the efficacy of prasugrel and ticagrelor in patients with acute coronary syndrome with respect to the primary composite endpoint of myocardial infarction (MI), stroke or cardiac cardiovascular death, and secondary endpoints including MI, stroke, cardiovascular death, major bleeding (Bleeding Academic Research Consortium (BARC) type 2 or above), and stent thrombosis within 1 year. Methods Meta-analysis was performed on randomised controlled trials (RCT) up to December 2019 that randomised patients with acute coronary syndrome to either prasugrel or ticagrelor. RCTs were identified from Medline, Embase and ClinicalTrials.gov using Cochrane library CENTRAL by 2 independent reviewers with “prasugrel” and “ticagrelor” as search terms. Effect estimates with confidence intervals were generated using the random effects model by extracting outcome data from the RCTs to compare the primary and secondary clinical outcomes. Cochrane risk-of-bias tool for randomised trials (Ver 2.0) was used for assessment of all eligible RCTs. Results 411 reports were screened, and we identified 11 eligible RCTs with 6098 patients randomised to prasugrel (n=3050) or ticagrelor (n=3048). The included trials had a follow up period ranging from 1 day to 1 year. 330 events on the prasugrel arm and 408 events on the ticagrelor arm were recorded. There were some concerns over the integrity of allocation concealment over 7 trials otherwise risk of other bias was minimal. Patients had a mean age of 61±4 (76% male; 50% with ST elevation MI; 35% with non-ST elevation MI; 15% with unstable angina; 25% with diabetes mellitus; 64% with hypertension; 51% with hyperlipidaemia; 42% smokers). There was no significant difference in risk between the prasugrel group and the ticagrelor group on the primary composite endpoint (Figure 1) (Risk Ratio (RR)=1.17; 95% CI=0.97–1.41; p=0.10, I2=0%). There was no significant difference between the use of prasugrel and ticagrelor with respect to MI (RR=1.24; 95% CI=0.81–1.90; p=0.31); stroke (RR=1.05; 95% CI=0.66–1.67; p=0.84); cardiovascular death (RR=1.01; 95% CI=0.75–1.36; p=0.95); BARC type 2 or above bleeding (RR=1.17; 95% CI =0.90–1.54; p=0.24); stent thrombosis (RR=1.58; 95% CI =0.90–2.76; p=0.11). Conclusion Compared with ticagrelor, prasugrel did not reduce the primary composite endpoint of MI, stroke and cardiovascular death within 1 year. There was also no significant difference in the risk of MI, stroke, cardiovascular death, major bleeding and stent thrombosis respectively. Figure 1. Primary Objective Funding Acknowledgement Type of funding source: None