Does Coronary Plaque Morphology Matter Beyond Plaque Burden?

PURPOSE OF REVIEW: Imaging of adverse coronary plaque features by coronary computed tomography angiography (CCTA) has advanced greatly and at a fast pace. We aim to describe the evolution, present and future in plaque analysis, and its value in comparison to plaque burden. RECENT FINDINGS: Recently, it has been demonstrated that in addition to plaque burden, quantitative and qualitative assessment of coronary plaque by CCTA can improve the prediction of future major adverse cardiovascular events in diverse coronary artery disease scenarios. The detection of high-risk non-obstructive coronary plaque can lead to higher use of preventive medical therapies such as statins and aspirin, help identify culprit plaque, and differentiate between myocardial infarction types. Even more, over traditional plaque burden, plaque analysis including pericoronary inflammation can potentially be useful tools for tracking disease progression and response to medical therapy. The identification of the higher risk phenotypes with plaque burden, plaque characteristics, or ideally both can allow the allocation of targeted therapies and potentially monitor response. Further observational data are now required to investigate these key issues in diverse populations, followed by rigorous randomized controlled trials.

Bezold-Jarisch reflex mediated syncope in pulmonary arterial hypertension: An illustrative case series.

We present a novel description of Bezold-Jarisch Reflex (BJR) during cardiopulmonary exercise testing (CPET) in three young female patients with Group 1 pulmonary arterial hypertension (PAH). These three cases presented within 26 months, representing only 0.8% of 11,387 tests on patients with PAH undergoing CPET during this time frame.

Potential clinical relevance of cardiac magnetic resonance to diagnose cardiac light chain amyloidosis.

BACKGROUND: While patients with cardiac transthyretin amyloidosis are easily diagnosed with bone scintigraphy, the detection of cardiac light chain (AL) amyloidosis is challenging. Cardiac magnetic resonance (CMR) analyses play an essential role in the differential diagnosis of cardiomyopathies; however, limited data are available from cardiac AL-Amyloidosis. Hence, the purpose of the present study was to analyze the potential role of CMR in the detection of cardiac AL-amyloidosis. METHODS: We included 35 patients with proved cardiac AL-amyloidosis and two control groups constituted by 330 patients with hypertrophic cardiomyopathy (HCM) and 70 patients with arterial hypertension (HT), who underwent CMR examination. The phenotype and degree of left ventricular (LV) hypertrophy and the amount and pattern of late gadolinium enhancement (LGE) were evaluated. In addition, global and regional LV strain parameters were also analyzed using feature-tracking techniques. Sensitivity and specificity of several CMR parameters were analyzed in diagnosing cardiac AL-amyloidosis. RESULTS: The sensitivity and specificity of diffuse septal subendocardial LGE in diagnosing cardiac AL-amyloidosis was 88% and 100%, respectively. Likewise, the sensitivity and specificity of septal myocardial nulling prior to blood pool was 71% and 100%, respectively. In addition, a LV end-diastolic septal wall thickness ≥ 15 mm had an optimal diagnostic performance to differentiate cardiac AL-amyloidosis from HT (sensitivity 91%, specificity 89%). On the other hand, a reduced global LV longitudinal strain (< 15%) plus apical sparing (apex-to-base longitudinal strain > 2) had a very low sensitivity (6%) in detecting AL-Amyloidosis, but with very high specificity (100%). CONCLUSIONS: The findings from this study suggest that CMR could have an optimal diagnostic performance in the diagnosis of cardiac AL-amyloidosis. Hence, further larger studies are warranted to validate the findings from this study.

Benchmarking off-the-shelf statistical shape modeling tools in clinical applications.

Statistical shape modeling (SSM) is widely used in biology and medicine as a new generation of morphometric approaches for the quantitative analysis of anatomical shapes. Technological advancements of in vivo imaging have led to the development of open-source computational tools that automate the modeling of anatomical shapes and their population-level variability. However, little work has been done on the evaluation and validation of such tools in clinical applications that rely on morphometric quantifications(e.g., implant design and lesion screening). Here, we systematically assess the outcome of widely used, state-of-the-art SSM tools, namely ShapeWorks, Deformetrica, and SPHARM-PDM. We use both quantitative and qualitative metrics to evaluate shape models from different tools. We propose validation frameworks for anatomical landmark/measurement inference and lesion screening. We also present a lesion screening method to objectively characterize subtle abnormal shape changes with respect to learned population-level statistics of controls. Results demonstrate that SSM tools display different levels of consistencies, where ShapeWorks and Deformetrica models are more consistent compared to models from SPHARM-PDM due to the groupwise approach of estimating surface correspondences. Furthermore, ShapeWorks and Deformetrica shape models are found to capture clinically relevant population-level variability compared to SPHARM-PDM models.

An Explainable Machine Learning Approach Reveals Prognostic Significance of Right Ventricular Dysfunction in Nonischemic Cardiomyopathy.

OBJECTIVES: The authors implemented an explainable machine learning (ML) model to gain insight into the association between cardiac magnetic resonance markers and adverse outcomes of cardiovascular hospitalization and all-cause death (composite endpoint) in patients with nonischemic dilated cardiomyopathy (NICM). BACKGROUND: Risk stratification of patients with NICM remains challenging. An explainable ML model has the potential to provide insight into the contributions of different risk markers in the prediction model. METHODS: An explainable ML model based on extreme gradient boosting (XGBoost) machines was developed using cardiac magnetic resonance and clinical parameters. The study cohorts consist of patients with NICM from 2 academic medical centers: Beth Israel Deaconess Medical Center (BIDMC) and Brigham and Women's Hospital (BWH), with 328 and 214 patients, respectively. XGBoost was trained on 70% of patients from the BIDMC cohort and evaluated based on the other 30% as internal validation. The model was externally validated using the BWH cohort. To investigate the contribution of different features in our risk prediction model, we used Shapley additive explanations (SHAP) analysis. RESULTS: During a mean follow-up duration of 40 months, 34 patients from BIDMC and 33 patients from BWH experienced the composite endpoint. The area under the curve for predicting the composite endpoint was 0.71 for the internal BIDMC validation and 0.69 for the BWH cohort. SHAP analysis identified parameters associated with right ventricular (RV) dysfunction and remodeling as primary markers of adverse outcomes. High risk thresholds were identified by SHAP analysis and thus provided thresholds for top predictive continuous clinical variables. CONCLUSIONS: An explainable ML-based risk prediction model has the potential to identify patients with NICM at risk for cardiovascular hospitalization and all-cause death. RV ejection fraction, end-systolic and end-diastolic volumes (as indicators of RV dysfunction and remodeling) were determined to be major risk markers.

Machine learning phenotyping of scarred myocardium from cine in hypertrophic cardiomyopathy.

AIMS: Cardiovascular magnetic resonance (CMR) with late-gadolinium enhancement (LGE) is increasingly being used in hypertrophic cardiomyopathy (HCM) for diagnosis, risk stratification, and monitoring. However, recent data demonstrating brain gadolinium deposits have raised safety concerns. We developed and validated a machine-learning (ML) method that incorporates features extracted from cine to identify HCM patients without fibrosis in whom gadolinium can be avoided. METHODS AND RESULTS: An XGBoost ML model was developed using regional wall thickness and thickening, and radiomic features of myocardial signal intensity, texture, size, and shape from cine. A CMR dataset containing 1099 HCM patients collected using 1.5T CMR scanners from different vendors and centres was used for model development (n=882) and validation (n=217). Among the 2613 radiomic features, we identified 7 features that provided best discrimination between +LGE and -LGE using 10-fold stratified cross-validation in the development cohort. Subsequently, an XGBoost model was developed using these radiomic features, regional wall thickness and thickening. In the independent validation cohort, the ML model yielded an area under the curve of 0.83 (95% CI: 0.77-0.89), sensitivity of 91%, specificity of 62%, F1-score of 77%, true negatives rate (TNR) of 34%, and negative predictive value (NPV) of 89%. Optimization for sensitivity provided sensitivity of 96%, F2-score of 83%, TNR of 19% and NPV of 91%; false negatives halved from 4% to 2%. CONCLUSION: An ML model incorporating novel radiomic markers of myocardium from cine can rule-out myocardial fibrosis in one-third of HCM patients referred for CMR reducing unnecessary gadolinium administration.

Characterization of Aerosol Generation During Various Intensities of Exercise.

BACKGROUND: Characterization of aerosol generation during exercise can inform the development of safety recommendations in the face of COVID-19. RESEARCH QUESTION: Does exercise at various intensities produce aerosols in significant quantities? STUDY DESIGN AND METHODS: In this experimental study, subjects were eight healthy volunteers (six men, two women) who were 20 to 63 years old. The 20-minute test protocol of 5 minutes rest, four 3-minute stages of exercise at 25%, 50%, 75%, and 100% of age-predicted heart rate reserve, and 3 minutes active recovery was performed in a clean, controlled environment. Aerosols were measured by four particle counters that were place to surround the subject. RESULTS: Age averaged 41 ± 14 years. Peak heart rate was 173 ± 17 beat/min (97% predicted); peak maximal oxygen uptake was 33.9 ± 7.5 mL/kg/min; and peak respiratory exchange ratio was 1.22 ± 0.10. Maximal ventilation averaged 120 ± 23 L/min, while cumulative ventilation reached 990 ± 192 L. Concentrations increased exponentially from start to 20 minutes (geometric mean ± geometric SD particles/liter): Fluke >0.3 µm = 66 ± 1.8 → 1605 ± 3.8; 0.3-1.0 µm = 35 ± 2.2 → 1095 ± 4.6; Fluke 1.0-5.0 µm = 21 ± 2.0 → 358 ± 2.3; P-Trak anterior = 637 ± 2.3 → 5148 ± 3.0; P-Trak side = 708 ± 2.7 → 6844 ± 2.7; P-Track back = 519 ± 3.1 → 5853 ± 2.8. All increases were significant at a probability value of <.05. Exercise at or above 50% of predicted heart rate reserve showed statistically significant increases in aerosol concentration. INTERPRETATION: Our data suggest exercise testing is an aerosol-generating procedure and, by extension, other activities that involve exercise intensities at or above 50% of predicted heart rate reserve. Results can guide recommendations for safety of exercise testing and other indoor exercise activities.

Mitigation of Aerosols Generated During Exercise Testing With a Portable High-Efficiency Particulate Air Filter With Fume Hood.

BACKGROUND: The role of portable high-efficiency particulate air (HEPA) filters for supplemental aerosol mitigation during exercise testing is unknown and might be relevant during COVID-19 pandemic. RESEARCH QUESTION: What is the effect of portable HEPA filtering on aerosol concentration during exercise testing and its efficiency in reducing room clearance time in a clinical exercise testing laboratory? STUDY DESIGN AND METHODS: Subjects were six healthy volunteers aged 20 to 56 years. In the first experiment, exercise was performed in a small tent with controlled airflow with the use of a stationary cycle, portable HEPA filter with fume hood, and particle counter to document aerosol concentration. Subjects performed a four-stage maximal exercise test that lasted 12 min plus 5 min of pretest quiet breathing and 3 min of active recovery. First, they exercised without mitigation then with portable HEPA filter running. In a separate experiment, room aerosol clearance time was measured in a clinical exercise testing laboratory by filling it with artificially generated aerosols and measuring time to 99.9% aerosol clearance with heating, ventilation, and air conditioning (HVAC) only or HVAC plus portable HEPA filter running. RESULTS: In the exercise experiment, particle concentrations reached 1,722 ± 1,484/L vs 96 ± 124/L (P < .04) for all particles (>0.3 µm), 1,339 ± 1,281/L vs 76 ± 104/L (P < .05) for smaller particles (0.3 to 1.0 µm), and 333 ± 209/L vs 17 ± 19/L (P < .01) for larger particles (1.0 to 5.0 µm) at the end of the protocol in a comparison of mitigation vs portable HEPA filter. Use of a portable HEPA filter in a clinical exercise laboratory clearance experiment reduced aerosol clearance time 47% vs HVAC alone. INTERPRETATION: The portable HEPA filter reduced the concentration of aerosols generated during exercise testing by 96% ± 2% for all particle sizes and reduced aerosol room clearance time in clinical exercise testing laboratories. Portable HEPA filters therefore might be useful in clinical exercise testing laboratories to reduce the risk of COVID-19 transmission.

Sensitivity of Myocardial Radiomic Features to Imaging Parameters in Cardiac MR Imaging.

BACKGROUND: Cardiac magnetic resonance (MR) images are often collected with different imaging parameters, which may impact the calculated values of myocardial radiomic features. PURPOSE: To investigate the sensitivity of myocardial radiomic features to changes in imaging parameters in cardiac MR images. STUDY TYPE: Prospective. POPULATION: A total of 11 healthy participants/five patients. FIELD STRENGTH/ SEQUENCE: A 3 T/cine balanced steady-state free-precession, T1 -weighted spoiled gradient-echo, T2 -weighted turbo spin-echo, and quantitative T1 and T2 mapping. For each sequence, the flip angle, in-plane resolution, slice thickness, and parallel imaging technique were varied to study the sensitivity of radiomic features to alterations in imaging parameters. ASSESSMENT: Myocardial contours were manually delineated by experienced readers, and a total of 1023 radiomic features were extracted using PyRadiomics with 11 image filters and six feature families. STATISTICAL TESTS: Sensitivity was defined as the standardized mean difference (D effect size), and the robust features were defined at sensitivity < 0.2. Sensitivity analysis was performed on predefined sets of reproducible features. The analysis was performed using the entire cohort of 16 subejcts. RESULTS: 64% of radiomic features were robust (sensitivity < 0.2) to changes in any imaging parameter. In qualitative sequences, radiomic features were most sensitive to changes in in-plane spatial resolution (spatial resolution: 0.6 vs. flip angle: 0.19, parallel imaging: 0.18, slice thickness: 0.07; P < 0.01 for all); in quantitative sequences, radiomic features were least sensitive to changes in spatial resolution (spatial resolution: 0.07 vs. slice thickness: 0.16, flip angle: 0.24; P < 0.01 for all). In an individual feature level, no singular feature family/image filter was identified as robust (sensitivity < 0.2) across sequences; however, highly sensitive features were predominantly associated with high-frequency wavelet filters across all sequences (32/50 features). DATA CONCLUSION: In cardiac MR, a considerable number of radiomic features are sensitive to changes in sequence parameters. EVIDENCE LEVEL: 1 TECHNICAL EFFICACY: Stage 1.

Multi-domain convolutional neural network (MD-CNN) for radial reconstruction of dynamic cardiac MRI.

PURPOSE: Cardiac MR cine imaging allows accurate and reproducible assessment of cardiac function. However, its long scan time not only limits the spatial and temporal resolutions but is challenging in patients with breath-holding difficulty or non-sinus rhythms. To reduce scan time, we propose a multi-domain convolutional neural network (MD-CNN) for fast reconstruction of highly undersampled radial cine images. METHODS: MD-CNN is a complex-valued network that processes MR data in k-space and image domains via k-space interpolation and image-domain subnetworks for residual artifact suppression. MD-CNN exploits spatio-temporal correlations across timeframes and multi-coil redundancies to enable high acceleration. Radial cine data were prospectively collected in 108 subjects (50 ± 17 y, 72 males) using retrospective-gated acquisition with 80%:20% split for training/testing. Images were reconstructed by MD-CNN and k-t Radial Sparse-Sense(kt-RASPS) using an undersampled dataset (14 of 196 acquired views; relative acceleration rate = 14). MD-CNN images were evaluated quantitatively using mean-squared-error (MSE) and structural similarity index (SSIM) relative to reference images, and qualitatively by three independent readers for left ventricular (LV) border sharpness and temporal fidelity using 5-point Likert-scale (1-non-diagnostic, 2-poor, 3-fair, 4-good, and 5-excellent). RESULTS: MD-CNN showed improved MSE and SSIM compared to kt-RASPS (0.11 ± 0.10 vs. 0.61 ± 0.51, and 0.87 ± 0.07 vs. 0.72 ± 0.07, respectively; P < .01). Qualitatively, MD-CCN significantly outperformed kt-RASPS in LV border sharpness (3.87 ± 0.66 vs. 2.71 ± 0.58 at end-diastole, and 3.57 ± 0.6 vs. 2.56 ± 0.6 at end-systole, respectively; P < .01) and temporal fidelity (3.27 ± 0.65 vs. 2.59 ± 0.59; P < .01). CONCLUSION: MD-CNN reduces the scan time of cine imaging by a factor of 23.3 and provides superior image quality compared to kt-RASPS.

Association Between Left Ventricular Mechanical Deformation and Myocardial Fibrosis in Nonischemic Cardiomyopathy.

Background In patients with nonischemic cardiomyopathy, nonischemic fibrosis detected by late gadolinium enhancement (LGE) cardiovascular magnetic resonance is related to adverse cardiovascular outcomes. However, its relationship with left ventricular (LV) mechanical deformation parameters remains unclear. We sought to investigate the association between LV mechanics and the presence, location, and extent of fibrosis in patients with nonischemic cardiomyopathy. Methods and Results We retrospectively identified 239 patients with nonischemic cardiomyopathy (67% male; 55±14 years) referred for a clinical cardiovascular magnetic resonance. LGE was present in 109 patients (46%), most commonly (n=52; 22%) in the septum. LV deformation parameters did not differentiate between LGE-positive and LGE-negative groups. Global longitudinal, radial, and circumferential strains, twist and torsion showed no association with extent of fibrosis. Patients with septal fibrosis had a more depressed LV ejection fraction (30±12% versus 35±14%; P=0.032) and more impaired global circumferential strain (-7.9±3.5% versus -9.7±4.4%; P=0.045) and global radial strain (10.7±5.2% versus 13.3±7.7%; P=0.023) than patients without septal LGE. Global longitudinal strain was similar in both groups. While patients with septal-only LGE (n=28) and free wall-only LGE (n=32) had similar fibrosis burden, the septal-only LGE group had more impaired LV ejection fraction and global circumferential, longitudinal, and radial strains (all P<0.05). Conclusions There is no association between LV mechanical deformation parameters and presence or extent of fibrosis in patients with nonischemic cardiomyopathy. Septal LGE was associated with poor global LV function, more impaired global circumferential and radial strains, and more impaired global strain rates.

High-intensity endurance training is associated with left atrial fibrosis.

INTRODUCTION: Endurance athletes are at higher risk for developing atrial fibrillation as compared to the general population. The exact mechanism to explain this observation is incompletely understood. Our study aimed to determine whether degree of left atrial fibrosis detected by late gadolinium-enhancement magnetic resonance imaging (LGE-MRI) differed between Masters athletes and non-athlete controls. METHODS: We recruited 20 endurance healthy Masters athletes and 20 healthy control subjects who underwent cardiac MRI. Healthy controls were recruited during screening colonoscopies and Masters athletes were recruited through word of mouth and at competitions. The two groups were age and gender matched. None of the participants were known to have an arrhythmia. Fibrosis, as measured by late gadolinium-enhancement, was measured in each participant by blinded readers. The degree of left atrial fibrosis was compared between the two groups. All participants were recruited from the Salt Lake City region and scanned at the University of Utah healthcare complex. RESULTS: Left ventricular function was normal in all study participants. Left atrial volumes were significantly larger in the athletes (74.2 ml ±â€¯14.4) as compared to the healthy control subjects (60.8 mL ±â€¯21.4) (P = .02). Mean left atrial fibrosis score, reported as a percentage of the LA, was 15.5% ±â€¯5.9 in the athlete cohort compared to 9.6% ±â€¯4.9 in the controls (P = .002). CONCLUSIONS: To our knowledge this is the first study that describes, characterizes and specifically quantifies fibrotic changes within the left atrium of highly trained endurance athletes. Increased atrial fibrosis seen in this population may be an early indicator for endurance athletes at risk of developing atrial arrhythmias.

Magnetic resonance imaging-guided cryoballoon ablation for left atrial substrate modification in patients with atrial fibrillation.

BACKGROUND: Cryoballoon ablation (CBA) for pulmonary vein isolation (PVI) is an established modality for the treatment of atrial fibrillation (AF). We report feasibility of left atrial (LA) substrate modification in addition to PVI both using the cryoballoon. METHODS: LA substrates and CBA-induced scar were assessed at baseline and 3 months after ablation using late gadolinium enhancement magnetic resonance imaging (LGE-MRI). Common periprocedural data including postablation LGE-MRI for evaluation of esophageal thermal injury, and CBA-associated complications were collected. Freedom from AF recurrence at 12 months was assessed using Holter and 30-day rhythm monitors. RESULTS: In 26 patients (64 ± 11 years, 69% male; 27% persistent AF, CHADSVASC score: 2.3 ± 1.5; left ventricular ejection fraction: 56 ± 10%, oral anticoagulation with warfarin/direct oral anticoagulants: n = 11/15), referred for first-time AF ablation, CBA of the pulmonary veins and extrapulmonary LA substrates was performed (median: 12 [interquartile range {IQR}: 7-14] freezes over 1675 seconds [IQR: 1168-2160]). On LGE-MRI, significant postablation cryoballoon-induced LA scar (median: 19.4% [IQR: 13.4-24.7] in comparison to baseline preablation LA-LGE (median: 10.6% [IQR 3.1-13.1]; P = .01) was found. Freedom from AF recurrence at 12 months was 74.5% with median time-to-recurrence of 242 days (IQR: 172-298). In 15 of 26 (58%) patients, esophageal enhancement on the postablation MRI was present with full recovery after 3 months. No major periprocedural complications were observed. CONCLUSION: LA substrate modification in addition to PVI using LGE-MRI-guided CBA is feasible but still experimental. The efficacy and safety have to be investigated in a prospective randomized trial.

How are ECG parameters related to cardiac magnetic resonance images? Electrocardiographic predictors of left ventricular hypertrophy and myocardial fibrosis in hypertrophic cardiomyopathy.

BACKGROUND: Structural myocardial changes in hypertrophic cardiomyopathy (HCM) are associated with different abnormalities on electrocardiographs (ECGs). The diagnostic value of the ECG voltage criteria used to screen for left ventricular hypertrophy (LVH) may depend on the presence and degree of myocardial fibrosis. Fibrosis can cause other changes in ECG parameters, such as pathological Q waves, fragmented QRS (fQRS), or repolarization abnormalities. METHODS: We investigated 146 patients with HCM and 35 healthy individuals who underwent cardiac magnetic resonance imaging (CMR; with late gadolinium enhancement [LGE] in HCM patients) and standard 12-lead ECGs. On the ECG, depolarization and repolarization abnormalities, the Sokolow-Lyon index, the Cornell index, and the Romhilt-Estes score were evaluated. The left ventricular ejection fraction, volumes, and myocardial mass (LVM) were quantified. Myocardial fibrosis was quantified on LGE images. RESULTS: The sensitivity of the Romhilt-Estes score was the highest (75%), and this hypertrophy criterion had the strongest correlation with the LVM index (p < .0001; r = .41). The amount of fibrosis was negatively correlated with the Cornell index (p = .015; r = -.201) and the Sokolow-Lyon index (p = .005; r = -.23), and the Romhilt-Estes score was independent of fibrosis (p = .757; r = 0.026). fQRS and strain pattern predicted more fibrosis, while the Cornell index was a negative predictor of myocardial fibrosis (p < .0001). Among others, the strain pattern was an independent predictor of the LVM (p < .0001). CONCLUSION: The Romhilt-Estes score is the most sensitive ECG criterion for detecting LVH in HCM patients, as myocardial fibrosis does not affect this criterion. The presence of fQRS and strain pattern predicts myocardial fibrosis.

The impact of sex, age and training on biventricular cardiac adaptation in healthy adult and adolescent athletes: Cardiac magnetic resonance imaging study.

AIMS: Physiological cardiac adaptation in athletes is influenced by multiple factors. This study aimed to investigate the impact of sex, age, body size, sports type and training volume on cardiac adaptation in healthy athletes with cardiac magnetic resonance imaging. METHODS: A total of 327 athletes (242 male) were studied (adults ≥18 years old; adolescents 14-18 years old). Left and right ventricular ejection fractions, end-diastolic volume, end-systolic volume, stroke volumes and masses were measured. Left ventricular end-diastolic volume/left ventricular mass, right ventricular end-diastolic volume/right ventricular mass and derived right/left ventricular ratios were determined to study balanced ventricular adaptation. Athletes were categorised as skill, power, mixed and endurance athletes. RESULTS: Male athletes had higher left and right ventricular volumes and masses in both adult (n = 215 (145 male); 24 ± 5 years old) and adolescent (n = 112 (97 male); 16 ± 1 years old) groups compared with women (all P < 0.05). In adults, male sex, age, body surface area, weekly training hours, mixed and endurance sports correlated with higher ventricular volumes and masses (all P < 0.05); and a combination of age, sex, training hours, endurance and mixed sports explained 30% of the variance of the left ventricular end-diastolic volume index (r = 0.30), right ventricular end-diastolic volume index (r = 0.34), right ventricular mass index (r = 0.30); and as much as 53% of the left ventricular mass index (r = 0.53) (all P < 0.0001). In adolescents, positive correlations were found between training hours and left ventricular hypertrophy (r = 0.39, P < 0.0001), and biventricular dilation (left ventricular end-diastolic volume r = 0.34, P = 0.0008; right ventricular end-diastolic volume r = 0.36, P = 0.0004). In adolescents, age and body surface area did not correlate with cardiac magnetic resonance parameters. CONCLUSION: There are significant sex differences in the physiological adaptation of adult and adolescent athlete's heart; and male sex, higher training volume and endurance sports are major determinants of sports adaptation in adults.

Biventricular pacing during cardiac magnetic resonance imaging.

AIMS: We aimed to assess the effect of cardiac resynchronization on left ventricular (LV) function, volumes, geometry, and mechanics in order to demonstrate reverse remodelling using cardiac magnetic resonance (CMR) with resynchronization on. METHODS AND RESULTS: New York Heart Association (NYHA) Class II-III patients on optimal medical therapy with LV ejection fraction (LVEF) ≤35%, and complete LBBB with broad QRS (>150 ms) were prospectively recruited. Cardiac magnetic resonance examination was performed at baseline and at 6-month follow-up, applying both biventricular and AOO pacing. The following data were measured: conventional CMR parameters, remodelling indices, global longitudinal, circumferential, radial strain, global dyssynchrony [mechanical dispersion (MD) defined as the standard deviation of time to peak longitudinal/circumferential strain in 16 LV segments], and regional dyssynchrony (maximum differences in time between peak septal and lateral transversal displacement). Thirteen patients (64 ± 7 years, 38% male) were enrolled. Comparing the baseline and follow-up CMR parameters measured during biventricular pacing, significant increase in LVEF, and decrease in LV end-diastolic volume index (LVEDVi) and LV end-systolic volume index (LVESVi) were found. Left ventricular remodelling indices, global longitudinal, circumferential, and radial strain values showed significant improvement. Circumferential MD decreased (20.5 ± 5.5 vs. 13.4 ± 3.4, P < 0.001), while longitudinal MD did not change. Regional dyssynchrony drastically improved (362 ± 96 vs. 104 ± 66 ms, P < 0.001). Applying AOO pacing resulted in an immediate deterioration in LVEF, LVESVi, circumferential strain, global and regional dyssynchrony. CONCLUSION: Cardiac magnetic resonance imaging during biventricular pacing is feasible and enables a more precise quantification of LV function, morphology, and mechanics. As a result, it may contribute to a better understanding of the effects of resynchronization therapy and might improve responder rate in the future.

Left atrial functional and structural changes associated with ablation of atrial fibrillation - Cardiac magnetic resonance study.

INTRODUCTION: Left atrial (LA) volumes are related to success of atrial fibrillation (AF) ablation, but the relation to other functional and structural parameters is less well understood. Our goal was to detect potential functional and structural predictors of arrhythmia recurrence after ablation using cardiac magnetic resonance imaging (CMRi) and to non-invasively assess the relation between LA functional and structural remodeling pre- and post-ablation. METHODS: A total of 55 patients (38 male, age 67 ± 10 years) underwent CMRi prior to and then within 24-h and 3-months after ablation. LA volumes (LAV) and function (as assessed by ejection fraction and peak longitudinal atrial strain (PLAS)) were measured by feature-tracking CMRi, and LA fibrosis/scarring was quantified using late­gadolinium enhancement (LGE) imaging. RESULTS: Atrial function was lower acutely in patients with recurrence versus those with non-recurrence: [R vs NR: EFTotal 27.8 ± 10.3% vs 38.1 ± 11% p = 0.002; EFActive 10.5 ± 8% vs 19.1 ± 12% p = 0.007; EFPassive 19.4 ± 8 vs 25.8 ± 10 p = 0.021; PLAS 13 ± 5.9% vs 20.2 ± 7% p = 0.004]. With univariate analysis, baseline minimum volume (MinLAV, MinLAVi), several baseline functional parameters (EFTotal, EFPassive, EFActive, PLAS), and LA-LGE were predictors of recurrence [all p < 0.05]. Acute function (EFTotal, EFPassive, EFActive, PLAS) also predicted recurrence (p < 0.01). Lower pre-ablation EFTotal, EFPassive, and PLAS correlated with higher amount of pre-ablation LA-LGE (p < 0.05). In a multivariate model including MinLAV, EFActive and LA-LGE (all at baseline), LA-LGE was the only independent predictor of recurrence (p = 0.0322). CONCLUSION: Pre-ablation function inversely correlated with LA-LGE and was related to success of AF ablation. Multi-parametric and longitudinal assessment of LA function and structure could be helpful in selection of optimal treatment strategies for AF patients by predicting outcomes.

Left atrial fibrosis progression detected by LGE-MRI after ablation of atrial fibrillation.

BACKGROUND: Left atrial (LA) fibrosis is thought to be a substrate for atrial fibrillation (AF) and can be quantified by late gadolinium enhancement magnetic resonance imaging (LGE-MRI). Fibrosis formation in LA is a dynamic process and may either progress or regress following AF ablation. We examined the impact of postablation progression in LA fibrosis on AF recurrence. METHODS: LA enhancement in LGE-MRI was quantified in 127 consecutive patients who underwent first time AF ablation. Serial LGE-MRIs were done prior to AF ablation, 3 months postablation and at least 12 months after second LGE-MRI. Transient postablation lesion (TL) was defined as atrial enhancement caused by ablation lesions that was detected on the first (3 month) but not on the second postablation LGE-MRI. New fibrosis (NF) was defined as atrial enhancement detected on the most recent LGE-MRI, at least 15 months after the ablation procedure. AF recurrence and its correlation with TL and NF was assessed in all patients during the follow-up period. RESULTS: An increase of 1% NF increased the chance of postablation AF recurrence by 3% (hazard ratio [HR] 1.03, 95% CI 1-1.06, P = .05). TL had no significant impact on recurrence (P = .057). After adjusting for cardiovascular risk factors, HR increased as NF became greater. Greater volume of NF (≥21%) corresponded with lower arrhythmia-free survival (37% vs 62%, P = .01). CONCLUSION: NF formation postablation of AF is a novel marker of long-term procedural outcome. Extensive NF is associated with significantly higher risk of atrial arrhythmia recurrence.