Right ventricular (RV) strain offers crucial diagnostic insights in cardiovascular and pulmonary disorders. Nonetheless, the absence of established reference values impedes its clinical implementation. Utilizing CMR-feature tracking, age- and gender-dependent RV strains were systematically assessed in 175 heart-healthy Caucasians, 97 females, median 32.5 years. RV global longitudinal strain (GLS) was greater in females than males (median -26.8

Impaired diastolic function is associated with a variety of diseases such as myocarditis or dilated cardiomyopathy. Currently, echocardiography is the standard method for assessing diastolic function. Recently, it has been postulated that cardiovascular magnetic resonance (CMR) is an at least equivalent or superior alternative to echocardiography. To assess CMR-based age- and gender-dependent diastolic functional normal reference values, pulmonary venous and transmitral blood-flow parameters were examined in heart-healthy test persons. Flow-sensitive phase-contrast CMR imaging was performed in the right upper pulmonary vein (RUPV) and at the level of the mitral valve (MV) in 183 healthy subjects (age 10–70 years; 97 women, 86 men). The data was distributed as evenly as possible across all groups. Strong age-dependence was observed for PV S/D; r = 0.718, p < 0.001 (Pearson product–moment correlation) and for transmitral MV E/A; ρ = −0.736, p < 0.001 (Spearman’s Rho correlation). Moderate age-dependence was found for PV slope D-wave; r = 0.394, p < 0.001. Except for MV slope E-wave (male −292 cm/s2 interquartile range (IQR) −338; −243 vs. female −319 ± 82 cm/s2; p = 0.047), no gender-related differences were observed. In a subgroup (N = 100), CMR data were compared with echocardiographic data. Strong correlation was found between CMR and echocardiography for PV S/D; r = 0.545, p < 0.001 and MV E/A; ρ = 0.692, p < 0.001. Diastolic functional parameters change with age, while gender-differences are small. CMR and echocardiography showed similar PV S/D and MV E/A ratios, making CMR a promising alternative for assessing diastolic function.

Background: Right ventricular (RV) strain has provided valuable prognostic information for patients with cardiac amyloidosis (CA). However, the extent to which RV strain and strain rate can differentiate CA is not yet clinically established. CA underdiagnosis delays treatment strategies and exacerbates patient prognosis.Aims: Evaluation of cardiac magnetic resonance (CMR) quantified RV global and regional strain of CA and HCM patients along with CA subtypes.Methods: CMR feature tracking attained longitudinal, radial and circumferential global and regional strain in 47 control subjects (CTRL), 43 CA-, 20 hypertrophic cardiomyopathy-(HCM) patients. CA patients were subdivided in 21 transthyretin-related amyloidosis (ATTR) and 20 acquired immunoglobulin light chain (AL) patients. Strain data and baseline clinical parameters were statistically analysed with respect to diagnostic performance and discriminatory power between the different clinical entities.Results: Effective differentiation of CA from HCM patients was achieved utilizing global longitudinal (GLS: 16.5 +/- 3.9% vs.-21.3 +/- 6.7%, p = 0.032), radial (GRS: 11.7 +/- 5.3% vs. 16.5 +/- 7.1%, p < 0.001) and circumferential (GCS:-7.6 +/- 4.0% vs.-9.4 +/- 4.4%, p = 0.015) right ventricular strain. Highest strain-based hypertrophic phenotype differentiation was attained using GRS (AUC = 0.86). Binomial regression found right ventricular ejection fraction (RV-EF) (p = 0.017) to be a significant predictor of CA-HCM differentiation. CA subtypes had comparable cardiac strains.Conclusion: CMR-derived RV global strains and various regional longitudinal strains provide discriminative radiological features for CA-HCM differentiation. However, in terms of feasibility, cine-derived RV-EF quanti-fication may suffice for efficient differential diagnostic support.

BackgroundCardiac magnetic resonance (CMR) imaging allows for multiparametric assessment of healthy pulmonary artery (PA) hemodynamics. Gender- and aging-associated PA stiffness and pressure alterations have remained clinically unestablished, however may demonstrate epidemiological differences in disease development. The aim of this study is to evaluate the role of CMR as a surrogate for catheter examinations by providing a comprehensive CMR assessment of sex- and age-related reference values for PA stiffness, flow, and pressure.Methods and ResultsPA hemodynamics were studied between gender and age groups (>/<50 years) using phase-contrast CMR. Corresponding correlation analyses were performed. 179 healthy volunteers with a median age of 32.6 years (range 11.3–68.2) were examined. Males demonstrated increased PA compliance (median [interquartile range] or mean ± standard deviation) (20.8 mm2/mmHg [16.6; 25.8] vs. 19.2 ± 7.1 mm2/mmHg; P < 0.033), higher pulse wave velocity (2.00 m/s [1.35; 2.87] vs. 1.73 m/s [1.19; 2.34]; P = 0.018) and a reduced full width half maximum (FWHM) (219 ± 22 ms vs. 235 ± 23 ms; P < 0.001) than females. Mean, systolic, diastolic PA pressure and pulmonary proportional pulse pressure were significantly elevated for males compared to females (P < 0.001). Older subjects (>50 years) exhibited reduced PA elasticity (41.7% [31.0; 52.9] vs. 66.4% [47.7; 83.0]; P < 0.001), reduced PA compliance (15.4 mm2/mmHg [12.3; 20.7] vs. 21.3 ± 6.8 mm2/mmHg; P < 0.001), higher pulse wave velocity (2.59 m/s [1.57; 3.59] vs. 1.76 m/s [1.24; 2.34]; P < 0.001) and a reduced FWHM (218 ± 29 ms vs. 231 ± 21 ms; P < 0.001) than younger subjects.ConclusionsVelocity-time profiles are dependent on age and gender. PA stiffness indices deteriorate with age. CMR has potential to serve as a surrogate for right heart catheterization.

Background: Hindered by its unspecific clinical and phenotypical presentation, cardiac sarcoidosis (CS) remains a challenging diagnosis. Objective: Utilizing cardiac magnetic resonance imaging (CMR), we acquired multi-chamber volumetrics and strain feature tracking for a support vector machine learning (SVM)-based diagnostic approach to CS. Method: Forty-five CMR-negative (CMR(−), 56.5(53.0;63.0)years), eighteen CMR-positive (CMR(+), 64.0(57.8;67.0)years) sarcoidosis patients and forty-four controls (CTRL, 56.5(53.0;63.0)years)) underwent CMR examination. Cardiac parameters were processed using the classifiers of logistic regression, KNN(K-nearest-neighbor), DT (decision tree), RF (random forest), SVM, GBoost, XGBoost, Voting and feature selection. Results: In a three-cluster analysis of CTRL versus vs. CMR(+) vs. CMR(−), RF and Voting classifier yielded the highest prediction rates (81.82%). The two-cluster analysis of CTRL vs. all sarcoidosis (All Sarc.) yielded high prediction rates with the classifiers logistic regression, RF and SVM (96.97%), and low prediction rates for the analysis of CMR(+) vs. CMR(−), which were augmented using feature selection with logistic regression (89.47%). Conclusion: Multi-chamber cardiac function and strain-based supervised machine learning provides a non-contrast approach to accurately differentiate between healthy individuals and sarcoidosis patients. Feature selection overcomes the algorithmically challenging discrimination between CMR(+) and CMR(−) patients, yielding high accuracy predictions. The study findings imply higher prevalence of cardiac involvement than previously anticipated, which may impact clinical disease management.

Aims Atrial fibrillation (AF) ablation protocols using energy delivery with very high power and short duration (vHPSD) have been introduced to improve lesion formation. This study reports procedural data of vHPSD ablation in AF patients and analyses characteristics of ablation-induced left atrial (LA) scar formation from cardiac magnetic resonance imaging (MRI). Methods and results Sixty consecutive patients undergoing index pulmonary vein isolation following our institutional Q4U-AF workflow were prospectively enrolled. Ablation was conducted using a contact force sensing catheter allowing for vHPSD ablation using a temperature-controlled ablation mode. Thirty patients underwent cardiac late gadolinium enhancement MRI of the LA 3 months after ablation to assess LA scar. Mean procedural duration was 66.5 +/- 14.8 min. Mean ablation time was 4.7 +/- 0.9 min with a mean number of 69.9 +/- 14.2 applications. First-pass isolation was achieved in 51 patients (85%) for the right pulmonary veins (RPVs), in 37 patients (61.7%) for the left pulmonary veins (LPVs), and in 34 patients (56.7%) for both pulmonary veins (PVs). Magnetic resonance imaging at 3 months post-ablation demonstrated a mean scar width of 14.4 +/- 2.6 mm around RPVs and 11.9 +/- 1.9 mm at LPVs (P > 0.05). Complete PV encirclement was observed in 76.7% for RPVs, in 76.7% for LPVs, and in 66.7% for both PV pairs. During a mean follow-up of 4.7 +/- 1.4 months, arrhythmia recurrence was observed in 3.3% of the patients. Conclusion Pulmonary vein isolation following a novel vHPSD workflow resulted in short procedure duration and high acute and mid-term efficacy. Magnetic resonance imaging demonstrated durable and transmural PV lesions with homogeneous and contiguous scar formation.

Left-atrial (LA) strain is the result of complex hemodynamics, which may be better characterized using a multiparametric approach. Cardiovascular magnetic resonance (CMR) feature tracking was used to perform a comprehensive LA strain assessment of 183 enrolled healthy volunteers (11–70 years, 97 females, median 32.9 ± 28.3 years). Novel strain dependencies were assessed using multi-parametric regression (MPR) analyses. LA volumetric data, left ventricular strain, transmitral and pulmonary venous blood flow parameters were utilized to create clusters for MPR of all subjects and a heart rate controlled subgroup (pulse: 60–75/min, N = 106). The LA reservoir(r) and conduit(c) strains of the total cohort were significantly elevated (p ≤ 0.001) in women (r: 49.7 ± 12.9%, c: 32.0 ± 11.0%) compared to men (r: 42.9 ± 11.4%, c: 26.1 IQ 10.5%). In contrast, there were no gender-specific differences (p > 0.05) for subgroup LA reservoir, conduit and booster(b) strains (all, r: 47.3 ± 12.7%; c: 29.0 IQ 15.5%; b: 17.6 ± 5.4%) and strain rates (all, 2.1 IQ 1.0 s −1 ; − 2.9 IQ 1.5 s −1 ; − 2.3 IQ 1.0 s −1 ). MPR found large effect sizes (|R 2 |≥ 0.26) for correlations between strain and various cardiac functional parameters. Largest effect size was found for the association between LA conduit strain and LA indexed booster volume, LA total ejection fraction, left ventricular global radial strain and E-wave (|R 2 |= 0.437). In addition to providing normal values for sex-dependent LA strain and strain rate, no gender differences were found with modified heart rate. MPR analyses of LA strain/strain rate and various cardiac functional parameters revealed that heart rate control improved goodness-of-fit for the overall model.

Background: Cardiac amyloidosis (CA) manifests in a hypertrophic phenotype with a poor prognosis, making differentiation from hypertrophic cardiomyopathy (HCM) challenging and delaying early treatment. The extent to which magnetic resonance imaging (MRI) quantifies the right atrial strain (RAS) and strain rate (RASR), providing valuable diagnostic information, is not yet clinically established. Aims: This study assesses diagnostic differences in the longitudinal RAS and RASR between CA and HCM patients, control subjects (CTRL) and CA subtypes in addition to the impact of atrial fibrillation (AF) on the right atrial function in CA patients. The RAS and RASR of tricuspid regurgitation (TR) patients are used to assess the potential for diagnostic overlap. Methods: RAS and RASR quantification was conducted via MRI feature-tracking for biopsy-confirmed CA patients with subtypes identified. Strain parameters were compared for CTRL, HCM and TR patients. Post hoc testing identified intergroup differences. Results: In total, 41 CA patients were compared to 47 CTRL, 20 HCM and 31 TR patients. Reservoir (R), conduit and booster RAS and RASRs allow for significant differentiation (p < 0.001) between CA and HCM patients (R: 10.6 ± 14.3% vs. R: 33.5 ± 16.3%) and CTRL (R: 44.6 ± 15.7%). Booster and reservoir RAS and RASRs qualified as reliable diagnostic tests (AUC > 0.8). CA patients with AF, in contrast to sinus rhythm, demonstrated a significantly impaired reservoir RAS and RASR and booster RASR. The discriminative power of RAS for CA vs. TR was insufficient (R: 10.6% ± 14.3% vs. 7.0% ± 6.0%, p = 0.069). Differentiation between 21 transthyretin and 20 light-chain amyloidosis subtypes was not achievable (R: 0.7% ± 1.0% vs. 0.7% ± 1.0%, p = 0.827). Conclusion: The MRI-derived RAS and RASR are impaired in CA patients and may support noninvasive differentiation between CA, HCM and CTRL.

We aimed to assess the relationship of left atrial appendage (LAA) fibrosis with atrial fibrillation (AF) and postoperative events in patients receiving coronary artery bypass graft surgery (CABG).

Background: This study challenges state-of-the-art cardiac amyloidosis (CA) diagnostics by feeding multi-chamber strain and cardiac function into supervised machine (SVM) learning algorithms. Methods: Forty-three CA (32 males; 79 years (IQR 71; 85)), 20 patients with hypertrophic cardiomyopathy (HCM, 10 males; 63.9 years (±7.4)) and 44 healthy controls (CTRL, 23 males; 56.3 years (IQR 52.5; 62.9)) received cardiovascular magnetic resonance imaging. Left atrial, right atrial and right ventricular strain parameters and cardiac function generated a 41-feature matrix for decision tree (DT), k-nearest neighbor (KNN), SVM linear and SVM radial basis function (RBF) kernel algorithm processing. A 10-feature principal component analysis (PCA) was conducted using SVM linear and RBF. Results: Forty-one features resulted in diagnostic accuracies of 87.9% (AUC = 0.960) for SVM linear, 90.9% (0.996; Precision = 94%; Sensitivity = 100%; F1-Score = 97%) using RBF kernel, 84.9% (0.970) for KNN, and 78.8% (0.787) for DT. The 10-feature PCA achieved 78.9% (0.962) via linear SVM and 81.8% (0.996) via RBF SVM. Explained variance presented bi-atrial longitudinal strain and left and right atrial ejection fraction as valuable CA predictors. Conclusion: SVM RBF kernel achieved competitive diagnostic accuracies under supervised conditions. Machine learning of multi-chamber cardiac strain and function may offer novel perspectives for non-contrast clinical decision-support systems in CA diagnostics.

Aims: The present study aims to evaluate magnetic-resonance-imaging (MRI)-assessed left atrial strain (LAS) and left atrial strain rate (LASR) as potential parameters for the diagnosis of cardiac amyloidosis (CA), the distinction of clinical subtypes and differentiation from other cardiomyopathies. Methods and results: LAS and LASR were assessed by MRI feature tracking in patients with biopsy-proven CA. LAS and LASR of patients with CA were compared to healthy subjects and patients with hypertrophic cardiomyopathy. LAS and LASR were also analyzed concerning differences between patients with transthyretin (ATTR) and light chain amyloidosis (AL). A total of 44 patients with biopsy-proven CA, 19 patients with hypertrophic cardiomyopathy and 24 healthy subjects were included. In 22 CA patients (50%), histological examination identified ATTR as CA subtype and AL in the remaining patients. No significant difference was observed for reservoir, conduit or booster LAS in patients with AL or ATTR. Reservoir LAS, conduit LAS and booster LAS were significantly reduced in patients with CA and HCM as compared to healthy subjects (p < 0.001). Reservoir LAS and booster LAS were significantly reduced in CA as compared to HCM patients (p < 0.001). A linear correlation was observed between LA global reservoir strain and LA-EF (p < 0.001, r = 0.5), conduit strain and global longitudinal LV strain (p < 0.001, r = 0.5), global booster strain rate and LA-EF (p < 0.001, r = 0.6) and between global booster strain rate and LA area at LVED (p < 0.0001, 0.5). Conclusions: LAS and LASR are severely impaired in patients with CA. The MRI-based assessment of LAS and LASR might allow non-invasive diagnosis and categorization of CA and its distinct differentiation from other hypertrophic phenotypes.