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Background/objective Constrictive pericarditis (CP) is an important cause of heart failure; however, with accurate diagnosis and directed treatment it is potentially curable. Cardiac magnetic resonance imaging (CMR) has played a diagnostic role, primarily by allowing assessment of pericardial morphology but with limited depiction of physiological changes. We sought to examine the feasibility of a novel CMR approach that enables real-time phase contrast (RT-PC) assessment of discordant respirophasic changes in trans-mitral and tricuspid flow velocity the signature findings in CP due to enhanced ventricular interdependence. Method Patients referred to the CMR lab pre-pericardectomy or for assessment of suspected CP were included. Following routine CMR examination for CP, transmitral (MV) and tricuspid valve (TV) flow velocities were simultaneously obtained by through-plane RT-PC imaging during unrestricted respiration using a slice position to include both valves (Figure 1) with the following parameters: TR/TE=13.7ms/2.5ms, water excitation pulse with flip angle=25, 10mm slice thickness, 160x120 matrix, EPI factor=15, TSENSE rate=2, slice thickness=10mm, and VENC=150cm/s. Shared velocity encoding was used to achieve an effective temporal

Accurate measurement of spatially variant noise in dynamic magnetic resonance (MR) images acquired using parallel imaging methods is problematic. We propose a new method based on the random matrix theory to accurately assess the noise level. The method is validated using numerical simulation and in-vivo dynamic cardiac MR images., Comment: This paper has been withdrawn by the authors, due to a crucial error in Eqn. 2

Dimensional reduction of high dimensional data can be achieved by keeping only the relevant eigenmodes after principal component analysis. However, differentiating relevant eigenmodes from the random noise eigenmodes is problematic. A new method based on the random matrix theory and a statistical goodness-of-fit test is proposed in this paper. It is validated by numerical simulations and applied to real-time magnetic resonance cardiac cine images., Comment: 7 pages, 5 figures