Association of Left Atrial Appendage Morphology and Function With Stroke and Transient Ischemic Attack in Atrial Fibrillation Patients.

We aimed to correlate left atrial appendage (LAA) structure and function with the history of stroke/transient ischemic attack (TIA) in patients with atrial fibrillation (AF). We analyzed the data of 649 patients with AF who were scheduled for catheter ablation. Patients underwent cardiac computed tomography and transesophageal echocardiography before ablation. The LAA morphologies depicted by cardiac computed tomography were categorized into 4 groups: cauliflower, chicken wing, swan, and windsock shapes. The mean age was 61.3 ± 10.5 years, 33.9% were women. The prevalence of stroke/TIA was 7.1%. After adjustment for the main risk factors, the LAA flow velocity ≤35.3 cm/s (odds ratio [OR] 2.18, 95% confidence interval [CI] 1.09 to 4.61, p = 0.033) and the swan LAA shape (OR 2.69, 95% CI 0.96 to 6.86, p = 0.047) independently associated with a higher risk of stroke/TIA, whereas the windsock LAA morphology proved to be protective (OR 0.32, 95% CI 0.12 to 0.77, p = 0.017) compared with the cauliflower LAA shape. Comparing the differences between the LAA morphology groups, we measured a significantly smaller LAA orifice area (389.3 ± 137.7 mm2 in windsock vs 428.3 ± 158.9 ml in cauliflower, p = 0.021) and LAA volume (7.4 ± 3.0 mm2 in windsock vs 8.5 ± 4.8 mm2 in cauliflower, p = 0.012) in patients with windsock LAA morphology, whereas the LAA flow velocity did not differ significantly. Reduced LAA function and swan LAA morphology were independently associated with a higher prevalence of stroke/TIA, whereas the windsock LAA shape proved to be protective. Comparing the differences between the various LAA morphology types, significantly lower LAA volume and LAA orifice area were measured in the windsock LAA shape than in the cauliflower LAA shape.

Assessment of paravalvular regurgitation after transcatheter aortic valve replacement using 2D multi-venc and 4D flow CMR.

AIMS: To compare the novel 2D multi-venc and 4D flow acquisitions with the standard 2D flow acquisition for the assessment of paravalvular regurgitation (PVR) after TAVR using cardiac magnetic resonance (CMR)-derived regurgitant fraction (RF). METHODS AND RESULTS: In this prospective study, patients underwent CMR one month after TAVR to assess PVR using 2D multi-venc and 4D flow, in addition to standard 2D flow. Scatterplots and Bland-Altman plots were used to assess correlation and visualize agreement between techniques. Reproducibility of measurements was assessed with intraclass correlation coefficients. The study included 21 patients (mean age, 80 years ± 5 [SD], 9 men). Mean RF was 11.7 ± 10.0% using standard 2D flow, 10.6 ± 7.0% using 2D multi-venc flow, and 9.6 ± 7.3% using 4D flow. There was a very strong correlation between the RFs assessed with 2D multi-venc and standard 2D flow (r = 0.88, p < 0.001), and a strong correlation between the RFs assessed with 4D flow and standard 2D flow (r = 0.74, p < 0.001). Bland-Altman plots revealed no significant bias between the RFs (2D multi-venc: 1.3%; 4D flow: 0.3%). Intra- and interobserver reproducibility for 2D multi-venc flow were 0.98 and 0.97, respectively; and 0.92 and 0.90 for 4D flow, respectively. CONCLUSION: 2D multi-venc and 4D flow produce accurate quantification of PVR after TAVR. The fast acquisition of the 2D multi-venc sequence, and the free-breathing acquisition with retrospective plane selection of the 4D flow sequence provide useful advantages in clinical practice, especially in the frail TAVR population.

Deep learning based automated left ventricle segmentation and flow quantification in 4D flow cardiac MRI.

BACKGROUND: 4D flow MRI enables assessment of cardiac function and intra-cardiac blood flow dynamics from a single acquisition. However, due to the poor contrast between the chambers and surrounding tissue, quantitative analysis relies on the segmentation derived from a registered cine MRI acquisition. This requires an additional acquisition and is prone to imperfect spatial and temporal inter-scan alignment. Therefore, in this work we developed and evaluated deep learning-based methods to segment the left ventricle (LV) from 4D flow MRI directly. METHODS: We compared five deep learning-based approaches with different network structures, data pre-processing and feature fusion methods. For the data pre-processing, the 4D flow MRI data was reformatted into a stack of short-axis view slices. Two feature fusion approaches were proposed to integrate the features from magnitude and velocity images. The networks were trained and evaluated on an in-house dataset of 101 subjects with 67,567 2D images and 3030 3D volumes. The performance was evaluated using various metrics including Dice, average surface distance (ASD), end-diastolic volume (EDV), end-systolic volume (ESV), LV ejection fraction (LVEF), LV blood flow kinetic energy (KE) and LV flow components. The Monte Carlo dropout method was used to assess the confidence and to describe the uncertainty area in the segmentation results. RESULTS: Among the five models, the model combining 2D U-Net with late fusion method operating on short-axis reformatted 4D flow volumes achieved the best results with Dice of 84.52% and ASD of 3.14 mm. The best averaged absolute and relative error between manual and automated segmentation for EDV, ESV, LVEF and KE was 19.93 ml (10.39%), 17.38 ml (22.22%), 7.37% (13.93%) and 0.07 mJ (5.61%), respectively. Flow component results derived from automated segmentation showed high correlation and small average error compared to results derived from manual segmentation. CONCLUSIONS: Deep learning-based methods can achieve accurate automated LV segmentation and subsequent quantification of volumetric and hemodynamic LV parameters from 4D flow MRI without requiring an additional cine MRI acquisition.

Multisize Electrode Field-of-View: Validation by High Resolution Gadolinium-Enhanced Cardiac Magnetic Resonance.

BACKGROUND: Voltage mapping to detect ventricular scar is important for guiding catheter ablation, but the field-of-view of unipolar, bipolar, conventional, and microelectrodes as it relates to the extent of viable myocardium (VM) is not well defined. OBJECTIVES: The purpose of this study was to evaluate electroanatomic voltage-mapping (EAVM) with different-size electrodes for identifying VM, validated against high-resolution ex-vivo cardiac magnetic resonance (HR-LGE-CMR). METHODS: A total of 9 swine with early-reperfusion myocardial infarction were mapped with the QDOT microcatheter. HR-LGE-CMR (0.3-mm slices) were merged with EAVM. At each EAVM point, the underlying VM in multisize transmural cylinders and spheres was quantified from ex vivo CMR and related to unipolar and bipolar voltages recorded from conventional and microelectrodes. RESULTS: In each swine, 220 mapping points (Q1, Q3: 216, 260 mapping points) were collected. Infarcts were heterogeneous and nontransmural. Unipolar and bipolar voltage increased with VM volumes from >175 mm3 up to >525 mm3 (equivalent to a 5-mm radius cylinder with height >6.69 mm). VM volumes in subendocardial cylinders with 1- or 3-mm depth correlated poorly with all voltages. Unipolar voltages recorded with conventional and microelectrodes were similar (difference 0.17 ± 2.66 mV) and correlated best to VM within a sphere of radius 10 and 8 mm, respectively. Distance-weighting did not improve the correlation. CONCLUSIONS: Voltage increases with transmural volume of VM but correlates poorly with small amounts of VM, which limits EAVM in defining heterogeneous scar. Microelectrodes cannot distinguish thin from thick areas of subendocardial VM. The field-of-view for unipolar recordings for microelectrodes and conventional electrodes appears to be 8 to 10 mm, respectively, and unexpectedly similar.

Automatic Quantification of Local Plaque Thickness Differences as Assessed by Serial Coronary Computed Tomography Angiography Using Scan-Quality-Based Vessel-Specific Thresholds.

INTRODUCTION: The use of serial coronary computed tomography angiography (CCTA) allows for the early assessment of coronary plaque progression, a crucial factor in averting major adverse cardiac events (MACEs). Traditionally, serial CCTA is assessed using anatomical landmarks to match baseline and follow-up scans. Recently, a tool has been developed that allows for the automatic quantification of local plaque thickness differences in serial CCTA utilizing plaque contour delineation. The aim of this study was to determine thresholds of plaque thickness differences that define whether there is plaque progression and/or regression. These thresholds depend on the contrast-to-noise ratio (CNR). METHODS: Plaque thickness differences between two scans acquired at the same moment in time should always be zero. The negative and positive differences in plaque contour delineation in these scans were used along with the CNR in order to create calibration graphs on which a linear regression analysis was performed. This analysis was conducted on a cohort of 50 patients referred for a CCTA due to chest complaints. A total of 300 coronary vessels were analyzed. First, plaque contours were semi-automatically determined for all major epicardial coronary vessels. Second, manual drawings of seven regions of interest (ROIs) per scan were used to quantify the scan quality based on the CNR for each vessel. RESULTS: A linear regression analysis was performed on the CNR and negative and positive plaque contour delineation differences. Accounting for the standard error of the estimate, the linear regression analysis revealed that above 1.009 - 0.002 × CNR there is an increase in plaque thickness (progression), and below - 1.638 + 0.012 × CNR there is a decrease in plaque thickness (regression). CONCLUSION: This study demonstrates the feasibility of developing vessel-specific, quality-based thresholds for visualizing local plaque thickness differences evaluated by serial CCTA. These thresholds have the potential to facilitate the early detection of atherosclerosis progression.

The association between antiplatelet therapy and changes in intraplaque hemorrhage in patients with mild to moderate symptomatic carotid stenosis: a longitudinal MRI study.

INTRODUCTION: Carotid atherosclerotic intraplaque hemorrhage (IPH) predicts stroke. Patients with a history of stroke are treated with antiplatelet agents to prevent secondary cardiovascular events. A positive association between previous antiplatelet use and IPH was reported in a cross-sectional analysis. We investigated changes in IPH over two years in patients who recently started versus those with continued antiplatelet use. METHODS: In the Plaque at Risk (PARISK) study, symptomatic patients with <70% ipsilateral carotid stenosis underwent carotid plaque MRI at baseline and after two years to determine IPH presence and volume. Participants were categorized into new users (starting antiplatelet therapy following the index event) and continued users (previous use of antiplatelet therapy before the index event). The association between previous antiplatelet therapy and the presence of IPH at baseline MRI was investigated using multivariable logistic regression analysis. IPH volume change over a period of two years, defined as the difference in volume between follow-up and baseline, was investigated in each group with a Wilcoxon signed-rank test. The IPH volume change was categorized as progression, regression, or no change. Using multivariable logistic regression, we investigated the association between new antiplatelet use and 1) newly developed ipsilateral or contralateral IPH and 2) IPH volume progression. RESULTS: A total of 108 patients underwent carotid MRI at baseline and follow-up. At baseline, previous antiplatelet therapy was associated with any IPH (OR=5.6, 95% CI: 1.3-23.1; p=0.02). Ipsilateral IPH volume did not change significantly during the two years in patients who continued receiving antiplatelet agents (86.4 mm3 [18.2-235.9] vs. 59.3 mm3 [11.4-260.3]; p=0.6) nor in the new antiplatelet users (n=31) (61.5 mm3 [0.0-166.9] vs. 27.7 mm3 [9.5-106.4]; p=0.4). Similar results of a nonsignificant change in contralateral IPH volume during those two years were observed in both groups (p>0.05). No significant associations were found between new antiplatelet use and newly developed IPH at two years (odds ratio (OR)=1.0, 95% CI:0.1-7.4) or the progression of IPH (ipsilateral: OR=2.4, 95% CI:0.3-19.1; contralateral: OR=0.3, 95% CI:0.01-8.5). CONCLUSION: Although the baseline association between IPH and previous antiplatelet therapy was confirmed in this larger cohort, the new onset of antiplatelet therapy after TIA/stroke was not associated with newly developed IPH or progression of IPH volume over the subsequent two years.

Automated segmentation of 3D cine cardiovascular magnetic resonance imaging.

Introduction: As the life expectancy of children with congenital heart disease (CHD) is rapidly increasing and the adult population with CHD is growing, there is an unmet need to improve clinical workflow and efficiency of analysis. Cardiovascular magnetic resonance (CMR) is a noninvasive imaging modality for monitoring patients with CHD. CMR exam is based on multiple breath-hold 2-dimensional (2D) cine acquisitions that should be precisely prescribed and is expert and institution dependent. Moreover, 2D cine images have relatively thick slices, which does not allow for isotropic delineation of ventricular structures. Thus, development of an isotropic 3D cine acquisition and automatic segmentation method is worthwhile to make CMR workflow straightforward and efficient, as the present work aims to establish. Methods: Ninety-nine patients with many types of CHD were imaged using a non-angulated 3D cine CMR sequence covering the whole-heart and great vessels. Automatic supervised and semi-supervised deep-learning-based methods were developed for whole-heart segmentation of 3D cine images to separately delineate the cardiac structures, including both atria, both ventricles, aorta, pulmonary arteries, and superior and inferior vena cavae. The segmentation results derived from the two methods were compared with the manual segmentation in terms of Dice score, a degree of overlap agreement, and atrial and ventricular volume measurements. Results: The semi-supervised method resulted in a better overlap agreement with the manual segmentation than the supervised method for all 8 structures (Dice score 83.23 ± 16.76% vs. 77.98 ± 19.64%; P-value ≤0.001). The mean difference error in atrial and ventricular volumetric measurements between manual segmentation and semi-supervised method was lower (bias ≤ 5.2 ml) than the supervised method (bias ≤ 10.1 ml). Discussion: The proposed semi-supervised method is capable of cardiac segmentation and chamber volume quantification in a CHD population with wide anatomical variability. It accurately delineates the heart chambers and great vessels and can be used to accurately calculate ventricular and atrial volumes throughout the cardiac cycle. Such a segmentation method can reduce inter- and intra- observer variability and make CMR exams more standardized and efficient.

Age- and sex-specific reference values of biventricular flow components and kinetic energy by 4D flow cardiovascular magnetic resonance in healthy subjects.

BACKGROUND: Advances in four-dimensional flow cardiovascular magnetic resonance (4D flow CMR) have allowed quantification of left ventricular (LV) and right ventricular (RV) blood flow. We aimed to (1) investigate age and sex differences of 4D flow CMR-derived LV and RV relative flow components and kinetic energy (KE) parameters indexed to end-diastolic volume (KEiEDV) in healthy subjects; and (2) assess the effects of age and sex on these parameters. METHODS: We performed 4D flow analysis in 163 healthy participants (42% female; mean age 43 ± 13 years) of a prospective registry study (NCT03217240) who were free of cardiovascular diseases. Relative flow components (direct flow, retained inflow, delayed ejection flow, residual volume) and multiple phasic KEiEDV (global, peak systolic, average systolic, average diastolic, peak E-wave, peak A-wave) for both LV and RV were analysed. RESULTS: Compared with men, women had lower median LV and RV residual volume, and LV peak and average systolic KEiEDV, and higher median values of RV direct flow, RV global KEiEDV, RV average diastolic KEiEDV, and RV peak E-wave KEiEDV. ANOVA analysis found there were no differences in flow components, peak and average systolic, average diastolic and global KEiEDV for both LV and RV across age groups. Peak A-wave KEiEDV increased significantly (r = 0.458 for LV and 0.341 for RV), whereas peak E-wave KEiEDV (r = - 0.355 for LV and - 0.318 for RV), and KEiEDV E/A ratio (r = - 0.475 for LV and - 0.504 for RV) decreased significantly, with age. CONCLUSION: These data using state-of-the-art 4D flow CMR show that biventricular flow components and kinetic energy parameters vary significantly by age and sex. Age and sex trends should be considered in the interpretation of quantitative measures of biventricular flow. Clinical trial registration  https://www. CLINICALTRIALS: gov . Unique identifier: NCT03217240.

Aortic flow is associated with aging and exercise capacity.

Aims: Increased blood flow eccentricity in the aorta has been associated with aortic (AO) pathology, however, its association with exercise capacity has not been investigated. This study aimed to assess the relationships between flow eccentricity parameters derived from 2-dimensional (2D) phase-contrast (PC) cardiovascular magnetic resonance (CMR) imaging and aging and cardiopulmonary exercise test (CPET) in a cohort of healthy subjects. Methods and Results: One hundred and sixty-nine healthy subjects (age 44 ± 13 years, M/F: 96/73) free of cardiovascular disease were recruited in a prospective study (NCT03217240) and underwent CMR, including 2D PC at an orthogonal plane just above the sinotubular junction, and CPET (cycle ergometer) within one week. The following AO flow parameters were derived: AO forward and backward flow indexed to body surface area (FFi, BFi), average flow displacement during systole (FDsavg), late systole (FDlsavg), diastole (FDdavg), systolic retrograde flow (SRF), systolic flow reversal ratio (sFRR), and pulse wave velocity (PWV). Exercise capacity was assessed by peak oxygen uptake (PVO2) from CPET. The mean values of FDsavg, FDlsavg, FDdavg, SRF, sFRR, and PWV were 17 ± 6%, 19 ± 8%, 29 ± 7%, 4.4 ± 4.2 mL, 5.9 ± 5.1%, and 4.3 ± 1.6 m/s, respectively. They all increased with age (r = 0.623, 0.628, 0.353, 0.590, 0.649, 0.598, all P < 0.0001), and decreased with PVO2 (r = -0.302, -0.270, -0.253, -0.149, -0.219, -0.161, all P < 0.05). A stepwise multivariable linear regression analysis using left ventricular ejection fraction (LVEF), FFi, and FDsavg showed an area under the curve of 0.769 in differentiating healthy subjects with high-risk exercise capacity (PVO2 ≤ 14 mL/kg/min). Conclusion: AO flow haemodynamics change with aging and predict exercise capacity. Registration: NCT03217240.

Establishing minimally important differences for cardiac MRI end-points in pulmonary arterial hypertension.

BACKGROUND: Cardiac magnetic resonance (CMR) is the gold standard technique to assess biventricular volumes and function, and is increasingly being considered as an end-point in clinical studies. Currently, with the exception of right ventricular (RV) stroke volume and RV end-diastolic volume, there is only limited data on minimally important differences (MIDs) reported for CMR metrics. Our study aimed to identify MIDs for CMR metrics based on US Food and Drug Administration recommendations for a clinical outcome measure that should reflect how a patient "feels, functions or survives". METHODS: Consecutive treatment-naïve patients with pulmonary arterial hypertension (PAH) between 2010 and 2022 who had two CMR scans (at baseline prior to treatment and 12 months following treatment) were identified from the ASPIRE registry. All patients were followed up for 1 additional year after the second scan. For both scans, cardiac measurements were obtained from a validated fully automated segmentation tool. The MID in CMR metrics was determined using two distribution-based (0.5sd and minimal detectable change) and two anchor-based (change difference and generalised linear model regression) methods benchmarked to how a patient "feels" (emPHasis-10 quality of life questionnaire), "functions" (incremental shuttle walk test) or "survives" for 1-year mortality to changes in CMR measurements. RESULTS: 254 patients with PAH were included (mean±sd age 53±16 years, 79% female and 66% categorised as intermediate risk based on the 2022 European Society of Cardiology/European Respiratory Society risk score). We identified a 5% absolute increase in RV ejection fraction and a 17 mL decrease in RV end-diastolic or end-systolic volumes as the MIDs for improvement. Conversely, a 5% decrease in RV ejection fraction and a 10 mL increase in RV volumes were associated with worsening. CONCLUSIONS: This study establishes clinically relevant CMR MIDs for how a patient "feels, functions or survives" in response to PAH treatment. These findings provide further support for the use of CMR as a clinically relevant clinical outcome measure and will aid trial size calculations for studies using CMR.

Plain language summaryPulmonary arterial hypertension (PAH) is a disease of the vessels of the lung that causes their narrowing and stiffening. As a result, the heart pumping blood into these diseased lung vessels has to work harder and eventually gets worn out. PAH can affect patients' ability to function in daily activities and impact their quality of life. It also reduces their life expectancy dramatically. Patients are, therefore, often monitored and undergo several investigations to adapt treatment according to their situation. These investigations include a survey of how a patient feels (the emPHasis-10 questionnaire), functions (walking test) and how well the heart is coping with the disease (MRI of the heart). Until now, it is unclear how changes on MRI of the heart reflect changes in how a patient feels and functions. Our study identified patients that had the emPHasis-10 questionnaire, walking test and MRI of the heart at both the time of PAH diagnosis and one year later. This allowed us to compare how the changes in the different tests relate to each other. And because previous research identified thresholds for important changes in the emPHasis-10 questionnaire and the walking tests, we were able to use these tests as a benchmark for changes in the MRI of the heart. Our study identified thresholds for change on heart MRI that might indicate whether a patient has improved or worsened. This finding might have implications for how patients are monitored in clinical practice and future research on PAH treatments.

Sex-specific associations in multiparametric 3 T MRI measurements in adult livers.

BACKGROUND: MRI relaxometry mapping and proton density fat fraction (PDFF) have been proposed for the evaluation of hepatic fibrosis. However, sex-specific relationships of age and body fat with these MRI parameters have not been studied in detail among adults without clinically manifest hepatic disease. We aimed to determine the sex-specific correlation of multiparametric MRI parameters with age and body fat and to evaluate their interplay associations. METHODS: 147 study participants (84 women, mean age 48±14 years, range 19-85 years) were prospectively enrolled. 3 T MRI including T1, T2 and T1ρ mapping and PDFF and R2* map were acquired. Visceral and subcutaneous fat were measured on the fat images from Dixon water-fat separation sequence. RESULTS: All MRI parameters demonstrated sex difference except for T1ρ. PDFF was more related to visceral than subcutaneous fat. Per 100 ml gain of visceral or subcutaneous fat is associated with 1 or 0.4% accretion of liver fat, respectively. PDFF and R2* were higher in men (both P = 0.01) while T1 and T2 were higher in women (both P < 0.01). R2* was positively but T1 and T2 were negatively associated with age in women (all P < 0.01), while T1ρ was positively related to age in men (P < 0.05). In all studies, R2* was positively and T1ρ was negatively associated with PDFF (both P <0.0001). CONCLUSION: Visceral fat plays an essential role in the elevated liver fat. When using MRI parametric measures for liver disease evaluation, the interplay between these parameters should be considered.

Deep Learning Segmentation of the Right Ventricle in Cardiac MRI: The M&Ms Challenge.

In recent years, several deep learning models have been proposed to accurately quantify and diagnose cardiac pathologies. These automated tools heavily rely on the accurate segmentation of cardiac structures in MRI images. However, segmentation of the right ventricle is challenging due to its highly complex shape and ill-defined borders. Hence, there is a need for new methods to handle such structure's geometrical and textural complexities, notably in the presence of pathologies such as Dilated Right Ventricle, Tricuspid Regurgitation, Arrhythmogenesis, Tetralogy of Fallot, and Inter-atrial Communication. The last MICCAI challenge on right ventricle segmentation was held in 2012 and included only 48 cases from a single clinical center. As part of the 12th Workshop on Statistical Atlases and Computational Models of the Heart (STACOM 2021), the M&Ms-2 challenge was organized to promote the interest of the research community around right ventricle segmentation in multi-disease, multi-view, and multi-center cardiac MRI. Three hundred sixty CMR cases, including short-axis and long-axis 4-chamber views, were collected from three Spanish hospitals using nine different scanners from three different vendors, and included a diverse set of right and left ventricle pathologies. The solutions provided by the participants show that nnU-Net achieved the best results overall. However, multi-view approaches were able to capture additional information, highlighting the need to integrate multiple cardiac diseases, views, scanners, and acquisition protocols to produce reliable automatic cardiac segmentation algorithms.

Artificial Intelligence as a Diagnostic Tool in Non-Invasive Imaging in the Assessment of Coronary Artery Disease.

Coronary artery disease (CAD) remains a leading cause of mortality and morbidity worldwide, and it is associated with considerable economic burden. In an ageing, multimorbid population, it has become increasingly important to develop reliable, consistent, low-risk, non-invasive means of diagnosing CAD. The evolution of multiple cardiac modalities in this field has addressed this dilemma to a large extent, not only in providing information regarding anatomical disease, as is the case with coronary computed tomography angiography (CCTA), but also in contributing critical details about functional assessment, for instance, using stress cardiac magnetic resonance (S-CMR). The field of artificial intelligence (AI) is developing at an astounding pace, especially in healthcare. In healthcare, key milestones have been achieved using AI and machine learning (ML) in various clinical settings, from smartwatches detecting arrhythmias to retinal image analysis and skin cancer prediction. In recent times, we have seen an emerging interest in developing AI-based technology in the field of cardiovascular imaging, as it is felt that ML methods have potential to overcome some limitations of current risk models by applying computer algorithms to large databases with multidimensional variables, thus enabling the inclusion of complex relationships to predict outcomes. In this paper, we review the current literature on the various applications of AI in the assessment of CAD, with a focus on multimodality imaging, followed by a discussion on future perspectives and critical challenges that this field is likely to encounter as it continues to evolve in cardiology.

Head-to-Head Comparison of T1 Mapping and Electroanatomical Voltage Mapping in Patients With Ventricular Arrhythmias.

BACKGROUND: Electroanatomical voltage mapping (EAVM) has been compared with late gadolinium enhancement cardiovascular magnetic resonance (LGE-CMR), which cannot delineate diffuse fibrosis. T1-mapping CMR overcomes the limitations of LGE-CMR, but it has not been directly compared against EAVM. OBJECTIVES: This study aims to assess the relationship between left ventricular (LV) endocardial voltage obtained by EAVM and extracellular volume (ECV) obtained by T1 mapping. METHODS: The study investigated patients who underwent endocardial EAVM for ventricular arrhythmias (CARTO 3, Biosense Webster) together with preprocedural contrast-enhanced T1 mapping (Ingenia 3T, Philips Healthcare). After image integration, EAVM datapoints were projected onto LGE-CMR and ECV-encoded images. Average values of unipolar voltage (UV), bipolar voltage (BV), LGE transmurality, and ECV were merged from corresponding cardiac segments (6 per slice) and pooled for analysis. RESULTS: The analysis included data from 628 segments from 18 patients (57 ± 13 years of age, 17% females, LV ejection fraction 48% ± 14%, nonischemic/ischemic cardiomyopathy/controls: 8/6/4 patients). Based on the 95th and 5th percentile values obtained from the controls, ECV >33%, BV <2.9 mV, and UV <6.7 mV were considered abnormal. There was a significant inverse association between voltage and ECV, but only in segments with abnormal ECV. Increased ECV could predict abnormal BV and UV with acceptable accuracy (area under the curve of 0.78 [95% CI: 0.74-0.83] and 0.84 [95% CI: 0.79-0.88]). CONCLUSIONS: This study found a significant inverse relationship between LV endocardial voltage and ECV. Real-time integration of T1 mapping may guide catheter mapping and may allow identification of areas of diffuse fibrosis potentially related to ventricular arrhythmias.

Deep learning-based prediction of intra-cardiac blood flow in long-axis cine magnetic resonance imaging.

PURPOSE: We aimed to design and evaluate a deep learning-based method to automatically predict the time-varying in-plane blood flow velocity within the cardiac cavities in long-axis cine MRI, validated against 4D flow. METHODS: A convolutional neural network (CNN) was implemented, taking cine MRI as the input and the in-plane velocity derived from the 4D flow acquisition as the ground truth. The method was evaluated using velocity vector end-point error (EPE) and angle error. Additionally, the E/A ratio and diastolic function classification derived from the predicted velocities were compared to those derived from 4D flow. RESULTS: For intra-cardiac pixels with a velocity > 5 cm/s, our method achieved an EPE of 8.65 cm/s and angle error of 41.27°. For pixels with a velocity > 25 cm/s, the angle error significantly degraded to 19.26°. Although the averaged blood flow velocity prediction was under-estimated by 26.69%, the high correlation (PCC = 0.95) of global time-varying velocity and the visual evaluation demonstrate a good agreement between our prediction and 4D flow data. The E/A ratio was derived with minimal bias, but with considerable mean absolute error of 0.39 and wide limits of agreement. The diastolic function classification showed a high accuracy of 86.9%. CONCLUSION: Using a deep learning-based algorithm, intra-cardiac blood flow velocities can be predicted from long-axis cine MRI with high correlation with 4D flow derived velocities. Visualization of the derived velocities provides adjunct functional information and may potentially be used to derive the E/A ratio from conventional CMR exams.

The Importance of Mitral Valve Prolapse Doming Volume in the Assessment of Left Ventricular Stroke Volume with Cardiac MRI.

There remains a debate whether the ventricular volume within prolapsing mitral valve (MV) leaflets should be included in the left ventricular (LV) end-systolic volume, and therefore factored in LV stroke volume (SV), in cardiac magnetic resonance (CMR) assessments. This study aims to compare LV volumes during end-systolic phases, with and without the inclusion of the volume of blood on the left atrial aspect of the atrioventricular groove but still within the MV prolapsing leaflets, against the reference LV SV by four-dimensional flow (4DF). A total of 15 patients with MV prolapse (MVP) were retrospectively enrolled in this study. We compared LV SV with (LV SVMVP) and without (LV SVstandard) MVP left ventricular doming volume, using 4D flow (LV SV4DF) as the reference value. Significant differences were observed when comparing LV SVstandard and LV SVMVP (p < 0.001), and between LV SVstandard and LV SV4DF (p = 0.02). The Intraclass Correlation Coefficient (ICC) test demonstrated good repeatability between LV SVMVP and LV SV4DF (ICC = 0.86, p < 0.001) but only moderate repeatability between LV SVstandard and LV SV4DF (ICC = 0.75, p < 0.01). Calculating LV SV by including the MVP left ventricular doming volume has a higher consistency with LV SV derived from the 4DF assessment. In conclusion, LV SV short-axis cine assessment incorporating MVP dooming volume can significantly improve the precision of LV SV assessment compared to the reference 4DF method. Hence, in cases with bi-leaflet MVP, we recommend factoring in MVP dooming into the left ventricular end-systolic volume to improve the accuracy and precision of quantifying mitral regurgitation.

Automated 4D flow cardiac MRI pipeline to derive peak mitral inflow diastolic velocities using short-axis cine stack: two centre validation study against echocardiographic pulse-wave doppler.

BACKGROUND: Measurement of peak velocities is important in the evaluation of heart failure. This study compared the performance of automated 4D flow cardiac MRI (CMR) with traditional transthoracic Doppler echocardiography (TTE) for the measurement of mitral inflow peak diastolic velocities. METHODS: Patients with Doppler echocardiography and 4D flow cardiac magnetic resonance data were included retrospectively. An established automated technique was used to segment the left ventricular transvalvular flow using short-axis cine stack of images. Peak mitral E-wave and peak mitral A-wave velocities were automatically derived using in-plane velocity maps of transvalvular flow. Additionally, we checked the agreement between peak mitral E-wave velocity derived by 4D flow CMR and Doppler echocardiography in patients with sinus rhythm and atrial fibrillation (AF) separately. RESULTS: Forty-eight patients were included (median age 69 years, IQR 63 to 76; 46% female). Data were split into three groups according to heart rhythm. The median peak E-wave mitral inflow velocity by automated 4D flow CMR was comparable with Doppler echocardiography in all patients (0.90 ± 0.43 m/s vs 0.94 ± 0.48 m/s, P = 0.132), sinus rhythm-only group (0.88 ± 0.35 m/s vs 0.86 ± 0.38 m/s, P = 0.54) and in AF-only group (1.33 ± 0.56 m/s vs 1.18 ± 0.47 m/s, P = 0.06). Peak A-wave mitral inflow velocity results had no significant difference between Doppler TTE and automated 4D flow CMR (0.81 ± 0.44 m/s vs 0.81 ± 0.53 m/s, P = 0.09) in all patients and sinus rhythm-only groups. Automated 4D flow CMR showed a significant correlation with TTE for measurement of peak E-wave in all patients group (r = 0.73, P < 0.001) and peak A-wave velocities (r = 0.88, P < 0.001). Moreover, there was a significant correlation between automated 4D flow CMR and TTE for peak-E wave velocity in sinus rhythm-only patients (r = 0.68, P < 0.001) and AF-only patients (r = 0.81, P = 0.014). Excellent intra-and inter-observer variability was demonstrated for both parameters. CONCLUSION: Automated dynamic peak mitral inflow diastolic velocity tracing using 4D flow CMR is comparable to Doppler echocardiography and has excellent repeatability for clinical use. However, 4D flow CMR can potentially underestimate peak velocity in patients with AF.

Association between renal sympathetic denervation and arterial stiffness: the ASORAS study.

OBJECTIVES: Renal sympathetic denervation (RDN) reduces blood pressure (BP). However, one out of three patients does not exhibit a significant BP response to the therapy. This study investigates the association between noninvasive vascular stiffness indices and RDN-mediated BP reduction. METHODS: In this prospective, single-arm pilot study, patients with systolic office BP at least 140 mmHg, mean 24-h systolic ambulatory blood pressure (ABP) at least 130 mmHg and at least three prescribed antihypertensive drugs underwent radiofrequency RDN. The primary efficacy endpoint was temporal evolution of mean 24-h systolic ABP throughout 1-year post RDN (measured at baseline and 3-6-12 months). Effect modification was studied for baseline ultrasound carotid-femoral and magnetic resonance (MR) pulse wave velocity (PWV), MR aortic distensibility, cardiac MR left ventricular parameters and clinical variables. Statistical analyses were performed using linear mixed-effects models, and effect modification was assessed using interaction terms. RESULTS: Thirty patients (mean age 62.5 ±â€Š10.7 years, 50% women) with mean 24-h ABP 146.7/80.8 ±â€Š13.7/12.0 mmHg were enrolled. Following RDN, mean 24-h systolic ABP changed with -8.4 (95% CI: -14.5 to -2.3) mmHg/year ( P  = 0.007). Independent effect modifiers were CF-PWV [+2.7 (0.3 to 5.1) mmHg/year change in outcome for every m/s increase in CF-PWV; P  = 0.03], daytime diastolic ABP [-0.4 (-0.8 to 0.0) mmHg/year per mmHg; P  = 0.03], age [+0.6 (0.2 to 1.0) mmHg/year per year of age; P  = 0.006], female sex [-14.0 (-23.1 to -5.0) mmHg/year as compared with men; P  = 0.003] and BMI [+1.2 (0.1 to 2.2) mmHg/year per kg/m 2 ; P  = 0.04]. CONCLUSION: Higher CF-PWV at baseline was associated with a smaller reduction in systolic ABP following RDN. These findings could contribute to improve identification of RDN responders.

Impact of body mass index and diabetes on myocardial fat content, interstitial fibrosis and function.

PURPOSE: We hypothesize that both increased myocardial steatosis and interstitial fibrosis contributes to subclinical myocardial dysfunction in patients with increased body mass index and diabetes mellitus. BACKGROUND: Increased body weight and diabetes mellitus are both individually associated with a higher incidence of heart failure with preserved ejection fraction. However, it is unclear how increased myocardial steatosis and interstitial fibrosis interact to influence myocardial composition and function. METHODS: A total of 100 subjects (27 healthy lean volunteers, 21 healthy but overweight volunteers, and 52 asymptomatic overweight patients with diabetes) were prospectively recruited to measure left ventricular (LV) myocardial steatosis (LV-myoFat) and interstitial fibrosis (by extracellular volume [ECV]) using magnetic resonance imaging, and then used to determine their combined impact on LV global longitudinal strain (GLS) analysis by 2-dimensional (2D) speckle tracking echocardiography on the same day. RESULTS: On multivariable analysis, both increased body mass index and diabetes were independently associated with increased LV-myoFat. In turn, increased LV-myoFat was independently associated with increased LV ECV. Both increased LV-myoFat and LV ECV were independently associated with impaired 2D LV GLS. CONCLUSION: Patients with increased body weight and patients with diabetes display excessive myocardial steatosis, which is related to a greater burden of myocardial interstitial fibrosis. LV myocardial contractile function was determined by both the extent of myocardial steatosis and interstitial fibrosis, and was independent of increasing age. Further study is warranted to determine how weight loss and improved diabetes management can improve myocardial composition and function.