New concepts in atrial fibrillation pathophysiology

The current classification of atrial fibrillation (AF) is mainly focused on the clinical presentation according to the duration of AF episodes and the mode of termination, which incompletely reflect the severity and progressive nature of the underlying atrial disease. In this review article, “atrial cardiomyopathy” is discussed as a new concept in AF pathophysiology. Electrogram-, imaging-, and biomarker-derived measures and parameters to assess atrial cardiomyopathy, which will likely impact how AF is clinically classified and managed in the future, are presented

A Boolean Dilemma:True or False Aneurysm?

A feared complication of acute myocardial infarction is the formation of a cardiac pseudoaneurysm. We report a case of a gargantuan, arrhythmogenic left-ventricular pseudoaneurysm with contradictory morphological characteristics. The integrative use of high-resolution 3-dimensional magnetic resonance imaging and computed tomography proved essential for the diagnostic discrimination and successful therapeutic intervention. (Level of Difficulty: Advanced.)

Myocardial Scar Detection Using High-Resolution Free-Breathing 3D Dark-Blood and Standard Breath-Holding 2D Bright-Blood Late Gadolinium Enhancement MRI:A Comparison of Observer Confidence

Abstract:Objective:To compare observer confidence for myocardial scar detection using 3 different late gadolinium enhancement (LGE) data sets by 2 observers with different levels of experience.Materials and Methods:Forty-one consecutive patients, who were referred for 3D dark-blood LGE MRI before implantable cardioverter-defibrillator implantation or ablation therapy and who underwent 2D bright-blood LGE MRI within a time frame of 3 months, were prospectively included. From all 3D dark-blood LGE data sets, a stack of 2D short-axis slices was reconstructed. All acquired LGE data sets were anonymized and randomized and evaluated by 2 independent observers with different levels of experience in cardiovascular imaging (beginner and expert). Confidence in detection of ischemic scar, nonischemic scar, papillary muscle scar, and right ventricular scar for each LGE data set was scored using a using a 3-point Likert scale (1 = low, 2 = medium, or 3 = high). Observer confidence scores were compared using the Friedman omnibus test and Wilcoxon signed-rank post hoc test.Results:For the beginner observer, a significant difference in confidence regarding ischemic scar detection was observed in favor of reconstructed 2D dark-blood LGE compared with standard 2D bright-blood LGE (p = 0.030) while for the expert observer, no significant difference was found (p = 0.166). Similarly, for right ventricular scar detection, a significant difference in confidence was observed in favor of reconstructed 2D dark-blood LGE compared with standard 2D bright-blood LGE (p = 0.006) while for the expert observer, no significant difference was found (p = 0.662). Although not significantly different for other areas of interest, 3D dark-blood LGE and its derived 2D dark-blood LGE data set showed a tendency to score higher for all areas of interest at both experience levels.Conclusions:The combination of dark-blood LGE contrast and high isotropic voxels may contribute to increased observer confidence in myocardial scar detection, independent of observer's experience level but in particular for beginner observers

Correlation between Cardiac MRI and Voltage Mapping in Evaluating Atrial Fibrosis:A Systematic Review

PURPOSE: To provide an overview of existing literature on the association between late gadolinium enhancement (LGE) cardiac MRI and low voltage areas (LVA) obtained with electroanatomic mapping (EAM) or histopathology when assessing atrial fibrosis. MATERIALS AND METHODS: A systematic literature search was conducted in the PubMed, Embase, and Cochrane Library databases to identify all studies published until June 7, 2022, comparing LGE cardiac MRI to LVA EAM and/or histopathology for evaluation of atrial fibrosis. The study protocol was registered at PROSPERO (registration no. CRD42022338243). Two reviewers independently evaluated the studies for inclusion. Risk of bias and applicability for each included study were assessed using Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) criteria. Data regarding demographics, electrophysiology, LGE cardiac MRI, and study outcomes were extracted. RESULTS: The search yielded 1048 total results, of which 22 studies were included. Nineteen of the 22 included studies reported a significant correlation between high signal intensity at LGE cardiac MRI and LVA EAM or histopathology. However, there was great heterogeneity between included studies regarding study design, patient samples, cardiac MRI performance and postprocessing, and EAM performance. CONCLUSION: Current literature suggests a correlation between LGE cardiac MRI and LVA EAM or histopathology when evaluating atrial fibrosis but high heterogeneity between studies, demonstrating the need for uniform choices regarding cardiac MRI and EAM acquisition in future studies.Keywords: Cardiac, MR Imaging, Left Atrium Supplemental material is available for this article. © RSNA, 2022

Quantification of mitral valve regurgitation from 4d flow mri using semiautomated flow tracking

Purpose: To compare the accuracy of semiautomated flow tracking with that of semiautomated valve tracking in the quantification of mitral valve (MV) regurgitation from clinical four-dimensional (4D) flow MRI data obtained in patients with mild, moderate, or severe MV regurgitation. Materials and Methods: The 4D flow MRI data were retrospectively collected from 30 patients (21 men; mean age, 61 years ± 10 [stan-dard deviation]) who underwent 4D flow MRI from 2006 to 2016. Ten patients had mild MV regurgitation, nine had moderate MV regurgitation, and 11 had severe MV regurgitation, as diagnosed by using semiquantitative echocardiography. The regurgitant volume (Rvol) across the MV was obtained using three methods: indirect quantification of Rvol (RvolINDIRECT ), semiautomated quantification of Rvol using valve tracking (RvolVALVE ), and semiautomated quantification of Rvol using flow tracking (RvolFLOW ). A second observer repeated the measurements. Aortic valve flow was quantified as well to test for intervalve consistency. The Wilcoxon signed rank test, orthogonal regression, Bland-Altman analysis, and coefficients of variation were used to assess agreement among measurements and between observers. Results: RvolFLOW was higher (median, 24.8 mL; interquartile range [IQR], 14.3–45.7 mL) than RvolVALVE (median, 9.9 mL; IQR, 6.0–16.9 mL; P < .001). Both RvolFLOW and RvolVALVE differed significantly from RvolINDIRECT (median, 19.1 mL; IQR, 4.1–47.5 mL; P = .03). RvolFLOW agreed more with RvolINDIRECT (ŷ = 0.78x + 12, r = 0.88) than with RvolVALVE (ŷ = 0.16x + 8.1, r = 0.53). Bland-Altman analysis revealed underestimation of RvolVALVE in severe MV regurgitation. Interobserver agreement was excellent for RvolFLOW (r = 0.95, coefficient of variation = 27%) and moderate for RvolVALVE (r = 0.72, coefficient of variation = 57%). Orthogonal regression demonstrated better intervalve consistency for flow tracking (ŷ = 1.2x-13.4, r = 0.82) than for valve tracking (ŷ = 2.7x-92.4, r = 0.67). Conclusion: Flow tracking enables more accurate 4D flow MRI–derived MV regurgitation quantification than valve tracking in terms of agreement with indirect quantification and intervalve consistency, particularly in severe MV regurgitation

Quantification of mitral valve regurgitation from 4d flow mri using semiautomated flow tracking

Purpose: To compare the accuracy of semiautomated flow tracking with that of semiautomated valve tracking in the quantification of mitral valve (MV) regurgitation from clinical four-dimensional (4D) flow MRI data obtained in patients with mild, moderate, or severe MV regurgitation. Materials and Methods: The 4D flow MRI data were retrospectively collected from 30 patients (21 men; mean age, 61 years ± 10 [stan-dard deviation]) who underwent 4D flow MRI from 2006 to 2016. Ten patients had mild MV regurgitation, nine had moderate MV regurgitation, and 11 had severe MV regurgitation, as diagnosed by using semiquantitative echocardiography. The regurgitant volume (Rvol) across the MV was obtained using three methods: indirect quantification of Rvol (RvolINDIRECT ), semiautomated quantification of Rvol using valve tracking (RvolVALVE ), and semiautomated quantification of Rvol using flow tracking (RvolFLOW ). A second observer repeated the measurements. Aortic valve flow was quantified as well to test for intervalve consistency. The Wilcoxon signed rank test, orthogonal regression, Bland-Altman analysis, and coefficients of variation were used to assess agreement among measurements and between observers. Results: RvolFLOW was higher (median, 24.8 mL; interquartile range [IQR], 14.3–45.7 mL) than RvolVALVE (median, 9.9 mL; IQR, 6.0–16.9 mL; P < .001). Both RvolFLOW and RvolVALVE differed significantly from RvolINDIRECT (median, 19.1 mL; IQR, 4.1–47.5 mL; P = .03). RvolFLOW agreed more with RvolINDIRECT (ŷ = 0.78x + 12, r = 0.88) than with RvolVALVE (ŷ = 0.16x + 8.1, r = 0.53). Bland-Altman analysis revealed underestimation of RvolVALVE in severe MV regurgitation. Interobserver agreement was excellent for RvolFLOW (r = 0.95, coefficient of variation = 27%) and moderate for RvolVALVE (r = 0.72, coefficient of variation = 57%). Orthogonal regression demonstrated better intervalve consistency for flow tracking (ŷ = 1.2x-13.4, r = 0.82) than for valve tracking (ŷ = 2.7x-92.4, r = 0.67). Conclusion: Flow tracking enables more accurate 4D flow MRI–derived MV regurgitation quantification than valve tracking in terms of agreement with indirect quantification and intervalve consistency, particularly in severe MV regurgitation

Transforming a pre-existing MRI environment into an interventional cardiac MRI suite

AIMS: To illustrate the practical and technical challenges along with the safety aspects when performing MRI‐guided electrophysiological procedures in a pre‐existing diagnostic magnetic resonance imaging (MRI) environment. METHODS AND RESULTS: A dedicated, well‐trained multidisciplinary interventional cardiac MRI team (iCMR team), consisting of electrophysiologists, imaging cardiologists, radiologists, anaesthesiologists, MRI physicists, electrophysiological (EP) and MRI technicians, biomedical engineers, and medical instrumentation technologists is a prerequisite for a safe and feasible implementation of CMR‐guided electrophysiological procedures (iCMR) in a pre‐existing MRI environment. A formal dry run “mock‐up” to address the entire spectrum of technical, logistic, and safety issues was performed before obtaining final approval of the Board of Directors. With this process we showed feasibility of our workflow, safety protocol, and bailout procedures during iCMR outside the conventional EP lab. The practical aspects of performing iCMR procedures in a pre‐existing MRI environment were addressed and solidified. Finally, the influence on neighbouring MRI scanners was evaluated, showing no interference. CONCLUSION: Transforming a pre‐existing diagnostic MRI environment into an iCMR suite is feasible and safe. However, performing iCMR procedures outside the conventional fluoroscopic lab, poses challenges with technical, practical, and safety aspects that need to be addressed by a dedicated multi‐disciplinary iCMR team

Histopathological validation of semi-automated myocardial scar quantification techniques for dark-blood late gadolinium enhancement magnetic resonance imaging

Aims To evaluate the performance of various semi-automated techniques for quantification of myocardial infarct size on both conventional bright-blood and novel dark-blood late gadolinium enhancement (LGE) images using histopathology as reference standard. Methods and results In 13 Yorkshire pigs, reperfused myocardial infarction was experimentally induced. At 7 weeks post-infarction, both bright-blood and dark-blood LGE imaging were performed on a 1.5 T magnetic resonance scanner. Following magnetic resonance imaging (MRI), the animals were sacrificed, and histopathology was obtained. The percentage of infarcted myocardium was assessed per slice using various semi-automated scar quantification techniques, including the signal threshold vs. reference mean (STRM, using 3 to 8 SDs as threshold) and full-width at half-maximum (FWHM) methods, as well as manual contouring, for both LGE methods. Infarct size obtained by histopathology was used as reference. In total, 24 paired LGE MRI slices and histopathology samples were available for analysis. For both bright-blood and dark-blood LGE, the STRM method with a threshold of 5 SDs led to the best agreement to histopathology without significant bias (-0.23%, 95% CI [-2.99, 2.52%], P = 0.862 and -0.20%, 95% CI [-2.12, 1.72%], P = 0.831, respectively). Manual contouring significantly underestimated infarct size on bright-blood LGE (-1.57%, 95% CI [-2.96, -0.18%], P = 0.029), while manual contouring on dark-blood LGE outperformed semi-automated quantification and demonstrated the most accurate quantification in this study (-0.03%, 95% CI [-0.22, 0.16%], P = 0.760). Conclusion The signal threshold vs. reference mean method with a threshold of 5 SDs demonstrated the most accurate semi-automated quantification of infarcted myocardium, without significant bias compared to histopathology, for both conventional bright-blood and novel dark-blood LGE