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Background: Recently, a novel left atrioventricular coupling index (LACI) has been introduced providing prognostic value to predict cardiovascular events beyond common risk factors in patients without cardiovascular disease. Since data on cardiovascular magnetic resonance (CMR)-derived LACI in patients following acute myocardial infarction (AMI) are scarce, we aimed to assess the diagnostic and prognostic implications of LACI in a large AMI patient cohort. Methods: In total, 1046 patients following AMI were included. After primary percutaneous coronary intervention CMR imaging and subsequent functional analyses were performed. LACI was defined by the ratio of the left atrial end-diastolic volume divided by the left ventricular (LV) end-diastolic volume. Major adverse cardiac events (MACE) including death, reinfarction or heart failure within 12 months after the index event were defined as primary clinical endpoint. Results: LACI was significantly higher in patients with MACE compared to those without MACE (p < 0.001). Youden Index identified an optimal LACI cut-off at 34.7% to classify patients at high-risk (p < 0.001 on log-rank testing). Greater LACI was associated with MACE on univariate regression modeling (HR 8.1, 95% CI 3.4–14.9, p < 0.001) and after adjusting for baseline confounders and LV ejection fraction (LVEF) on multivariate regression analyses (HR 3.1 95% CI 1.0–9, p = 0.049). Furthermore, LACI assessment enabled further risk stratification in high-risk patients with impaired LV systolic function (LVEF ≤ 35%; p < 0.001 on log-rank testing). Conclusion: Atrial-ventricular interaction using CMR-derived LACI is a superior measure of outcome beyond LVEF especially in high-risk patients following AMI. Trial registration ClinicalTrials.gov, NCT00712101 and NCT01612312 [ABSTRACT FROM AUTHOR]

Background: Myocardial deformation analyses using cardiovascular magnetic resonance (CMR) feature tracking (CMR-FT) have incremental value in the assessment of cardiac function beyond volumetric analyses. Since guidelines do not recommend specifc imaging parameters, we aimed to defne optimal spatial and temporal resolutions for CMR cine images to enable reliable post-processing. Methods: Intra- and inter-observer reproducibility was assessed in 12 healthy subjects and 9 heart failure (HF) patients. Cine images were acquired with diferent temporal (20, 30, 40 and 50 frames/cardiac cycle) and spatial reso‑ lutions (high in-plane 1.5×1.5 mm through-plane 5 mm, standard 1.8×1.8 x 8mm and low 3.0×3.0 x 10mm). CMR-FT comprised left ventricular (LV) global and segmental longitudinal/circumferential strain (GLS/GCS) and associated systolic strain rates (SR), and right ventricular (RV) GLS. Results: Temporal but not spatial resolution did impact absolute strain and SR. Maximum absolute changes between lowest and highest temporal resolution were as follows: 1.8% and 0.3%/s for LV GLS and SR, 2.5% and 0.6%/s for GCS and SR as well as 1.4% for RV GLS. Changes of strain values occurred comparing 20 and 30 frames/cardiac cycle including LV and RV GLS and GCS (p<0.001–0.046). In contrast, SR values (LV GLS/GCS SR) changed signifcantly com‑ paring all successive temporal resolutions (p<0.001–0.013). LV strain and SR reproducibility was not afected by either temporal or spatial resolution, whilst RV strain variability decreased with augmentation of temporal resolution. Conclusion: Temporal but not spatial resolution signifcantly afects strain and SR in CMR-FT deformation analyses. Strain analyses require lower temporal resolution and 30 frames/cardiac cycle ofer consistent strain assessments, whilst SR measurements gain from further increases in temporal resolution. [ABSTRACT FROM AUTHOR]

Background: Cardiovascular Magnetic Resonance (CMR) myocardial perfusion imaging has the potential to evolve into a method allowing full quantification of myocardial blood flow (MBF) in clinical routine. Multiple quantification pathways have been proposed. However at present it remains unclear which algorithm is the most accurate. An isolated perfused, magnetic resonance (MR) compatible pig heart model allows very accurate titration of MBF and in combination with high-resolution assessment of fluorescently-labeled microspheres represents a near optimal platform for validation. We sought to investigate which algorithm is most suited to quantify myocardial perfusion by CMR at 1.5 and 3 Tesla using state of the art CMR perfusion techniques and quantification algorithms. Methods: First-pass perfusion CMR was performed in an MR compatible blood perfused pig heart model. We acquired perfusion images at physiological flow ("rest"), reduced flow ("ischaemia") and during adenosine-induced hyperaemia ("hyperaemia") as well as during coronary occlusion. Perfusion CMR was performed at 1.5 Tesla (n = 4 animals) and at 3 Tesla (n = 4 animals). Fluorescently-labeled microspheres and externally controlled coronary blood flow served as reference standards for comparison of different quantification strategies, namely Fermi function deconvolution (Fermi), autoregressive moving average modelling (ARMA), exponential basis deconvolution (Exponential) and B-spline basis deconvolution (B-spline). Results: All CMR derived MBF estimates significantly correlated with microsphere results. The best correlation was achieved with Fermi function deconvolution both at 1.5 Tesla (r = 0.93, p < 0.001) and at 3 Tesla (r = 0.9, p < 0.001). Fermi correlated significantly better with the microspheres than all other methods at 3 Tesla (p < 0.002). B-spline performed worse than Fermi and Exponential at 1.5 Tesla and showed the weakest correlation to microspheres (r = 0.74, p < 0.001). All other comparisons were not significant. At 3 Tesla exponential deconvolution performed worst (r = 0.49, p < 0.001). (Continued on next page) Conclusions: CMR derived quantitative blood flow estimates correlate with true myocardial blood flow in a controlled animal model. Amongst the different techniques, Fermi function deconvolution was the most accurate technique at both field strengths. Perfusion CMR based on Fermi function deconvolution may therefore emerge as a useful clinical tool providing accurate quantitative blood flow assessment. [ABSTRACT FROM AUTHOR]

An abstract on quantification of the ischemic burden on cardiac magnetic resonance perfusion maps by perfusion threshold analysis is presented.

An abstract of the article "Quantitative assessment of magnetic resonance derived perfusion measurements using advanced techniques: comparison with microspheres in an explanted pig heart system," by Andreas Schuster and colleagues is presented.

An abstract to the article "The intra-observer reproducibility of cardiovascular magnetic resonance myocardial feature tracking strain assessment is independent of field strength," by Andreas Schuster, Geraint Morton, Shazia T. Hussain, Roy Jogiya, Shelby Kutty, and colleagues presented.

An abstract of the conference paper "Direct comparison of MR and CT perfusion utilizing a myocardial perfusion phantom," by James Otton and colleagues is presented.

An abstract of the conference paper "Cardiac magnetic resonance imaging of isolated perfused pig hearts in a 3T clinical MR scanner," by Eike Nagel, and colleagues is presented.

An abstract of the conference paper "Cardiac magnetic resonance myocardial feature tracking detects quantitative wall motion during dobutamine stress," by Andreas Schuster and colleagues is presented.

An abstract of the conference paper "Quantification of transmural perfusion gradients by high-resolution MR versus fractional flow reserve for the assessment of coronary artery stenosis," by Amedeo Chiribiri and colleagues is presented.

An abstract of the conference paper "Transmural perfusion gradient analysis by high resolution MR versus fractional flow reserve for the assessment of coronary artery stenosis," by Amedeo Chiribiri and colleagues is presented.

An abstract of the conference paper "Cardiac magnetic resonance myocardial feature tracking correlates with natural radial strain and corresponds to inotropic stimulation," by Andreas Schuster and colleagues is presented.

An abstract of the paper "Myocardial Feature Tracking for Viability Assessment in Ischemic Cardiomyopathy," by Andreas Schuster and colleagues is presented.