Right Ventricular Structure and Function in Adolescent Athletes: A 3D Echocardiographic Study.

The aim of this study was to characterize the right ventricular (RV) contraction pattern and its associations with exercise capacity in a large cohort of adolescent athletes using resting three-dimensional echocardiography (3DE). We enrolled 215 adolescent athletes (16±1 years, 169 males, 12±6 hours of training/week) and compared them to 38 age and sex-matched healthy, sedentary adolescents. We measured the 3DE-derived biventricular ejection fractions (EF). We also determined the relative contributions of longitudinal EF (LEF/RVEF) and radial EF (REF/RVEF) to the RVEF. Same-day cardiopulmonary exercise testing was performed to calculate VO2/kg. Both LV and RVEFs were significantly lower (athletes vs. controls; LVEF: 57±4 vs 61±3, RVEF: 55±5 vs 60±5%, p<0.001). Interestingly, while the relative contribution of radial shortening to the global RV EF was also reduced (REF/RVEF: 0.40±0.10 vs 0.49±0.06, p<0.001), the contribution of the longitudinal contraction was significantly higher in athletes (LEF/RVEF: 0.45±0.08 vs 0.40±0.07, p<0.01). The supernormal longitudinal shortening correlated weakly with a higher VO2/kg (r=0.138, P=0.044). Similarly to the adult athlete's heart, the cardiac adaptation of adolescent athletes comprises higher biventricular volumes and lower resting functional measures with supernormal RV longitudinal shortening. Characteristic exercise-induced structural and functional cardiac changes are already present in adolescence.

Machine Learning in Cardiovascular Imaging.

The number of cardiovascular imaging studies is growing exponentially, and so is the demand to improve the efficacy of the imaging workflow. Over the past decade, studies have demonstrated that machine learning (ML) holds promise to revolutionize cardiovascular research and clinical care. ML may improve several aspects of cardiovascular imaging, such as image acquisition, segmentation, image interpretation, diagnostics, therapy planning, and prognostication. In this review, we discuss the most promising applications of ML in cardiovascular imaging and also highlight the several challenges to its widespread implementation in clinical practice.

Geometrical remodeling of the mitral and tricuspid annuli in response to exercise training: a 3-D echocardiographic study in elite athletes.

Intense exercise exposes the heart to significant hemodynamic demands, resulting in adaptive changes in cardiac morphology and function. Nevertheless, the athletic adaptation of the atrioventricular valves remains to be elucidated. Our study aimed to characterize the geometry of mitral (MA) and tricuspid (TA) annuli in elite athletes using 3-D echocardiography. Thirty-four athletes presented with functional mitral regurgitation (FMR) were retrospectively identified and compared with 34 athletes without mitral regurgitation (MR) and 34 healthy, sedentary volunteers. 3-D echocardiographic datasets were used to quantify MA and TA geometry and leaflet tenting by dedicated softwares. MA and TA areas, as well as tenting volumes, were higher in athletes compared with controls. MA area was significantly higher in athletes with MR compared with those without (8.2 ± 1.0 vs. 7.2 ± 1.0 cm2/m2, P < 0.05). Interestingly, athletes with MR also presented with a significantly higher TA area (7.2 ± 1.1 vs. 6.5 ± 1.1 cm2/m2, P < 0.05). Nonplanar angle describing the MA's saddle shape was less obtuse in athletes without MR, whereas the values of athletes with MR were comparable with controls. The exercise-induced relative increases in left ventricular (35 ± 25%) and left atrial (40 ± 29%) volumes were similar; however, the increment in the MA area was disproportionately higher (63 ± 23%, overall P < 0.001). The relative increase in TA area (40 ± 23%) was also higher compared with the increment in right ventricular volume (34 ± 25%, P < 0.05). Atrioventricular annuli undergo a disproportionate remodeling in response to regular exercise. Athletic adaptation is characterized by both annular enlargement and increased leaflet tenting of both valves. There are differences in MA geometry in athletes presented with versus without FMR.NEW & NOTEWORTHY We have characterized the annular geometry of mitral and tricuspid valves in elite athletes using 3-D echocardiography. We have found that exercise-induced remodeling of the atrioventricular annuli comprises a disproportionate dilation of annular dimensions and increased leaflet tenting of both valves. Moreover, we have demonstrated a more pronounced saddle shape of the mitral annulus in athletes without mitral regurgitation, which was not present in those who had mild regurgitation.

Long-term survival following upgrade compared with de novo cardiac resynchronization therapy implantation: a single-centre, high-volume experience.

AIMS: Patients with a pacemaker or implantable cardioverter-defibrillator are often considered for cardiac resynchronization therapy (CRT). However, limited comprehensive data are available regarding their long-term outcomes. METHODS AND RESULTS: Our retrospective registry included 2524 patients [1977 (78%) de novo, 547 (22%) upgrade patients] with mild to severe symptoms, left ventricular ejection fraction ≤35%, and QRS ≥ 130ms. The primary outcome was the composite of all-cause mortality, heart transplantation (HTX), or left ventricular assist device (LVAD) implantation; secondary endpoints were death from any cause and post-procedural complications. In our cohort, upgrade patients were older [71 (65-77) vs. 67 (59-73) years; P < 0.001], were less frequently females (20% vs. 27%; P = 0.002) and had more comorbidities than de novo patients. During the median follow-up time of 3.7 years, 1091 (55%) de novo and 342 (63%) upgrade patients reached the primary endpoint. In univariable analysis, upgrade patients exhibited a higher risk of mortality/HTX/LVAD than the de novo group [hazard ratio (HR): 1.41; 95% confidence interval (CI): 1.23-1.61; P < 0.001]. However, this difference disappeared after adjusting for covariates (adjusted HR: 1.12; 95% CI: 0.86-1.48; P = 0.402), or propensity score matching (propensity score-matched HR: 1.10; 95% CI: 0.95-1.29; P = 0.215). From device-related complications, lead dysfunction (3.1% vs. 1%; P < 0.001) and pocket infections (3.7% vs. 1.8%; P = 0.014) were more frequent in the upgrade group compared to de novo patients. CONCLUSION: In our retrospective analysis, upgrade patients had a higher risk of all-cause mortality than de novo patients, which might be attributable to their more significant comorbidity burden. The occurrence of lead dysfunction and pocket infections was more frequent in the upgrade group.

Machine learning-based mortality prediction of patients undergoing cardiac resynchronization therapy: the SEMMELWEIS-CRT score.

AIMS: Our aim was to develop a machine learning (ML)-based risk stratification system to predict 1-, 2-, 3-, 4-, and 5-year all-cause mortality from pre-implant parameters of patients undergoing cardiac resynchronization therapy (CRT). METHODS AND RESULTS: Multiple ML models were trained on a retrospective database of 1510 patients undergoing CRT implantation to predict 1- to 5-year all-cause mortality. Thirty-three pre-implant clinical features were selected to train the models. The best performing model [SEMMELWEIS-CRT score (perSonalizEd assessMent of estiMatEd risk of mortaLity With machinE learnIng in patientS undergoing CRT implantation)], along with pre-existing scores (Seattle Heart Failure Model, VALID-CRT, EAARN, ScREEN, and CRT-score), was tested on an independent cohort of 158 patients. There were 805 (53%) deaths in the training cohort and 80 (51%) deaths in the test cohort during the 5-year follow-up period. Among the trained classifiers, random forest demonstrated the best performance. For the prediction of 1-, 2-, 3-, 4-, and 5-year mortality, the areas under the receiver operating characteristic curves of the SEMMELWEIS-CRT score were 0.768 (95% CI: 0.674-0.861; P < 0.001), 0.793 (95% CI: 0.718-0.867; P < 0.001), 0.785 (95% CI: 0.711-0.859; P < 0.001), 0.776 (95% CI: 0.703-0.849; P < 0.001), and 0.803 (95% CI: 0.733-0.872; P < 0.001), respectively. The discriminative ability of our model was superior to other evaluated scores. CONCLUSION: The SEMMELWEIS-CRT score (available at semmelweiscrtscore.com) exhibited good discriminative capabilities for the prediction of all-cause death in CRT patients and outperformed the already existing risk scores. By capturing the non-linear association of predictors, the utilization of ML approaches may facilitate optimal candidate selection and prognostication of patients undergoing CRT implantation.

Left Ventricular Systolic Function Has Strong Independent Genetic Background from Diastolic Function: A Classical Twin Study.

Background and Objectives: No data are available on whether the heritability of left ventricle (LV) systolic and diastolic parameters are independent of each other. Therefore, our aim was to assess the magnitude of common and independent genetic and environmental factors defining LV systolic and diastolic function. Materials and Methods: We analyzed 184 asymptomatic twins (65% female, mean age: 56 ± 9 years). Transthoracic echocardiography was performed to measure LV systolic (global longitudinal and circumferential strain; basal and apical rotation) and diastolic (early diastolic velocity of mitral inflow and lateral mitral annulus tissue; deceleration time and early diastolic strain rate) parameters using conventional and speckle-tracking echocardiography. Genetic structural equation models were evaluated to quantify the proportion of common and specific genetic (Ac, As) and environmental factors (Ec, Es) contributing to the phenotypes. Results: LV systolic parameters had no common genetic or environmental heritability (Ac range: 0-0%; Ec range: 0-0%; As range: 57-77%; Es range: 24-43%). Diastolic LV parameters were mainly determined by common genetic and environmental effects (Ac range: 9-40%; Ec range: 11-49%; As range: 0-29%; Es range: 0-51%). Systolic parameters had no common genetic or environmental factors (Ac = 0%; Ec = 0%) with diastolic metrics. Conclusions: Systolic LV parameters have a strong genetic predisposition to any impact. They share no common genetic or environmental factors with each other or with diastolic parameters, indicating that they may deteriorate specifically to given effects. However, diastolic functional parameters are mainly affected by common environmental influences, suggesting that pathological conditions may deteriorate them equally. Estimation of the genetic and environmental influence and interdependence on systolic and diastolic LV function may help the understanding of the pathomechanism of different heart failure classification types.

Right ventricular mechanical pattern in health and disease: beyond longitudinal shortening.

Right ventricular (RV) function has proven to be a prognostic factor in heart failure with reduced and preserved ejection fraction and in pulmonary hypertension. RV function is also a cornerstone in the management of novel clinical issues, such as mechanical circulatory support devices or grown-up congenital heart disease patients. Despite the notable amount of circumferentially oriented myofibers in the subepicardial layer of the RV myocardium, the non-longitudinal motion directions are often neglected in the everyday assessment of RV function by echocardiography. However, the complex RV contraction pattern incorporates different motion components along three anatomically relevant axes: longitudinal shortening with traction of the tricuspid annulus towards the apex, radial motion of free wall often referred as the "bellows effect", and anteroposterior shortening of the chamber by stretching the free wall over the septum. Advanced echocardiographic techniques, such as speckle-tracking and 3D echocardiography allow an in-depth characterization of RV mechanical pattern, providing better understanding of RV systolic and diastolic function. In our current review, we summarize the existing knowledge regarding RV mechanical adaptation to pressure- and/or volume-overloaded states and also other physiologic or pathologic conditions.

Exercise-induced shift in right ventricular contraction pattern: novel marker of athlete's heart?

Data about the functional adaptation of the right ventricle (RV) to intense exercise are limited. Our aim was to characterize the RV mechanical pattern in top-level athletes using three-dimensional echocardiography. A total of 60 elite water polo athletes (19 ± 4 yr, 17 ± 6 h of training/wk, 50% women and 50% men) and 40 healthy sedentary control subjects were enrolled. We measured the RV end-diastolic volume index (RVEDVi) and ejection fraction (RVEF) using dedicated software. Furthermore, we determined RV global longitudinal (RV GLS) and circumferential strain (RV GCS) and the relative contribution of longitudinal ejection fraction (LEF) and radial ejection fraction (REF) to RVEF using the ReVISION method. Athletes also underwent cardiopulmonary exercise testing [O2 consumption (V̇o2)/kg]. Athletes had significantly higher RVEDVi compared with control subjects (athletes vs. control subjects, 88 ± 11 vs. 65 ± 10 ml/m2, P < 0.001); however, they also demonstrated lower RVEF (56 ± 4% vs. 61 ± 5%, P < 0.001). RV GLS was comparable between the two groups (-22 ± 5% vs. -23 ± 5%, P = 0.24), whereas RV GCS was significantly lower in athletes (-21 ± 4% vs. -26 ± 7%, P < 0.001). Athletes had higher LEF and lower REF contribution to RVEF (LEF/RVEF: 0.50 ± 0.07 vs. 0.42 ± 0.07, P < 0.001; REF/RVEF: 0.33 ± 0.08 vs. 0.45 ± 0.08, P < 0.001). Moreover, the pattern of RV functional shift correlated with V̇o2/kg (LEF/RVEF: r = 0.30, P < 0.05; REF/RVEF: r = -0.27, P < 0.05). RV mechanical adaptation to long-term intense exercise implies a functional shift; the relative contribution of longitudinal motion to global function was increased, whereas the radial shortening was significantly decreased, in athletes. Moreover, this functional pattern correlates with aerobic exercise performance, representing a potential new resting marker of an athlete's heart. NEW & NOTEWORTHY Intensive regular physical exercise results in significant changes of right ventricular morphology and function. By separate quantification of the right ventricular longitudinal and radial function, a relative dominance of longitudinal motion and a decrease in radial motion can be observed compared with sedentary controls. Moreover, this contraction pattern correlates with cardiopulmonary fitness. According to these results, this functional shift of the right ventricle may represent a novel marker of an athlete's heart.

Comparison of speckle-tracking echocardiography with invasive hemodynamics for the detection of characteristic cardiac dysfunction in type-1 and type-2 diabetic rat models.

BACKGROUND: Measurement of systolic and diastolic function in animal models is challenging by conventional non-invasive methods. Therefore, we aimed at comparing speckle-tracking echocardiography (STE)-derived parameters to the indices of left ventricular (LV) pressure-volume (PV) analysis to detect cardiac dysfunction in rat models of type-1 (T1DM) and type-2 (T2DM) diabetes mellitus. METHODS: Rat models of T1DM (induced by 60 mg/kg streptozotocin, n = 8) and T2DM (32-week-old Zucker Diabetic Fatty rats, n = 7) and corresponding control animals (n = 5 and n = 8, respectively) were compared. Echocardiography and LV PV analysis were performed. LV short-axis recordings were used for STE analysis. Global circumferential strain, peak strain rate values in systole (SrS), isovolumic relaxation (SrIVR) and early diastole (SrE) were measured. LV contractility, active relaxation and stiffness were measured by PV analysis. RESULTS: In T1DM, contractility and active relaxation were deteriorated to a greater extent compared to T2DM. In contrast, diastolic stiffness was impaired in T2DM. Correspondingly, STE described more severe systolic dysfunction in T1DM. Among diastolic STE parameters, SrIVR was more decreased in T1DM, however, SrE was more reduced in T2DM. In T1DM, SrS correlated with contractility, SrIVR with active relaxation, while in T2DM SrE was related to cardiac stiffness, cardiomyocyte diameter and fibrosis. CONCLUSIONS: Strain and strain rate parameters can be valuable and feasible measures to describe the dynamic changes in contractility, active relaxation and LV stiffness in animal models of T1DM and T2DM. STE corresponds to PV analysis and also correlates with markers of histological myocardial remodeling.

Dominance of free wall radial motion in global right ventricular function of heart transplant recipients.

Assessment of right ventricular (RV) function using conventional echocardiography might be inadequate as the radial motion of the RV free wall is often neglected. Our aim was to quantify the longitudinal and the radial components of RV function using three-dimensional (3D) echocardiography in heart transplant (HTX) recipients. Fifty-one HTX patients in stable cardiovascular condition without history of relevant rejection episode or chronic allograft vasculopathy and 30 healthy volunteers were enrolled. RV end-diastolic (EDV) volume and total ejection fraction (TEF) were measured by 3D echocardiography. Furthermore, we quantified longitudinal (LEF) and radial ejection fraction (REF) by decomposing the motion of the RV using the ReVISION method. RV EDV did not differ between groups (HTX vs control; 96 ± 27 vs 97 ± 2 mL). In HTX patients, TEF was lower, however, tricuspid annular plane systolic excursion (TAPSE) decreased to a greater extent (TEF: 47 ± 7 vs 54 ± 4% [-13%], TAPSE: 11 ± 5 vs 21 ± 4 mm [-48%], P < .0001). In HTX patients, REF/TEF ratio was significantly higher compared to LEF/TEF (REF/TEF vs LEF/TEF: 0.58 ± 0.10 vs 0.27 ± 0.08, P < .0001), while in controls the REF/TEF and LEF/TEF ratio was similar (0.45 ± 0.07 vs 0.47 ± 0.07). Current results confirm the superiority of radial motion in determining RV function in HTX patients. Parameters incorporating the radial motion are recommended to assess RV function in HTX recipients.

Quantification of the relative contribution of the different right ventricular wall motion components to right ventricular ejection fraction: the ReVISION method.

Three major mechanisms contribute to right ventricular (RV) pump function: (i) shortening of the longitudinal axis with traction of the tricuspid annulus towards the apex; (ii) inward movement of the RV free wall; (iii) bulging of the interventricular septum into the RV and stretching the free wall over the septum. The relative contribution of the aforementioned mechanisms to RV pump function may change in different pathological conditions.Our aim was to develop a custom method to separately assess the extent of longitudinal, radial and anteroposterior displacement of the RV walls and to quantify their relative contribution to global RV ejection fraction using 3D data sets obtained by echocardiography.Accordingly, we decomposed the movement of the exported RV beutel wall in a vertex based manner. The volumes of the beutels accounting for the RV wall motion in only one direction (either longitudinal, radial, or anteroposterior) were calculated at each time frame using the signed tetrahedron method. Then, the relative contribution of the RV wall motion along the three different directions to global RV ejection fraction was calculated either as the ratio of the given direction's ejection fraction to global ejection fraction and as the frame-by-frame RV volume change (∆V/∆t) along the three motion directions.The ReVISION (Right VentrIcular Separate wall motIon quantificatiON) method may contribute to a better understanding of the pathophysiology of RV mechanical adaptations to different loading conditions and diseases.

[Assessment of the right ventricular anatomy and function by advanced echocardiography: pathological and physiological insights]. / A jobb kamrai anatómia és funkció korszeru echokardiográfiás vizsgálata: patológiás és fiziológiás eltérések.

Accurate assessment of right ventricular geometry and function is of high clinical importance. However, several limitations have to be taken into consideration if using conventional echocardiographic parameters. Advanced echocardiographic techniques, such as speckle-tracking analysis or 3D echocardiography are reliable and simple tools providing a cost-effective and non-invasive alternative of current modalities used to characterize the right ventricle. There is a growing interest in the diagnostic and prognostic value of these methods regarding pathological (right ventricular infarction, pulmonary hypertension, arrhythmogenic right ventricular dysplasia, follow-up of heart transplantation) and even physiological (athlete's heart) alterations of the right ventricle. Orv. Hetil., 2016, 157(29), 1139-1146.

A deep patient-similarity learning framework for the assessment of diastolic dysfunction in elderly patients.

AIMS: Age-related changes in cardiac structure and function are well recognized and make the clinical determination of abnormal left ventricular (LV) diastolic dysfunction (LVDD) particularly challenging in the elderly. We investigated whether a deep neural network (DeepNN) model of LVDD, previously validated in a younger cohort, can be implemented in an older population to predict incident heart failure (HF). METHODS AND RESULTS: A previously developed DeepNN was tested on 5596 older participants (66-90 years; 57% female; 20% Black) from the Atherosclerosis Risk in Communities Study. The association of DeepNN predictions with HF or all-cause death for the American College of Cardiology Foundation/American Heart Association Stage A/B (n = 4054) and Stage C/D (n = 1542) subgroups was assessed. The DeepNN-predicted high-risk compared with the low-risk phenogroup demonstrated an increased incidence of HF and death for both Stage A/B and Stage C/D (log-rank P < 0.0001 for all). In multi-variable analyses, the high-risk phenogroup remained an independent predictor of HF and death in both Stages A/B {adjusted hazard ratio [95% confidence interval (CI)] 6.52 [4.20-10.13] and 2.21 [1.68-2.91], both P < 0.0001} and Stage C/D [6.51 (4.06-10.44) and 1.03 (1.00-1.06), both P < 0.0001], respectively. In addition, DeepNN showed incremental value over the 2016 American Society of Echocardiography/European Association of Cardiovascular Imaging (ASE/EACVI) guidelines [net re-classification index, 0.5 (CI 0.4-0.6), P < 0.001; C-statistic improvement, DeepNN (0.76) vs. ASE/EACVI (0.70), P < 0.001] overall and maintained across stage groups. CONCLUSION: Despite training with a younger cohort, a deep patient-similarity-based learning framework for assessing LVDD provides a robust prediction of all-cause death and incident HF for older patients.

Significant Disagreement Between Conventional Parameters and 3D Echocardiography-Derived Ejection Fraction in the Detection of Right Ventricular Systolic Dysfunction and Its Association With Outcomes.

AIMS: Conventional echocardiographic parameters such as tricuspid annular plane systolic excursion (TAPSE), fractional area change (FAC), and free-wall longitudinal strain (FWLS) offer limited insights into the complexity of right ventricular (RV) systolic function, while 3D echocardiography-derived RV ejection fraction (RVEF) enables a comprehensive assessment. We investigated the discordance between TAPSE, FAC, FWLS, and RVEF in RV systolic function grading and associated outcomes. METHODS: We analyzed two- and three-dimensional echocardiography data from 2 centers including 750 patients followed up for all-cause mortality. Right ventricular dysfunction was defined as RVEF <45%, with guideline-recommended thresholds (TAPSE <17 mm, FAC <35%, FWLS >-20%) considered. RESULTS: Among patients with normal RVEF, significant proportions exhibited impaired TAPSE (21%), FAC (33%), or FWLS (8%). Conversely, numerous patients with reduced RVEF had normal TAPSE (46%), FAC (26%), or FWLS (41%). Using receiver-operating characteristic analysis, FWLS exhibited the highest area under the curve of discrimination for RV dysfunction (RVEF <45%) with 59% sensitivity and 92% specificity. Over a median 3.7-year follow-up, 15% of patients died. Univariable Cox regression identified TAPSE, FAC, FWLS, and RVEF as significant mortality predictors. Combining impaired conventional parameters showed that outcomes are the worst if at least 2 parameters are impaired and gradually better if only one or none of them are impaired (log-rank P < .005). CONCLUSION: Guideline-recommended cutoff values of conventional echocardiographic parameters of RV systolic function are only modestly associated with RVEF-based assessment. Impaired values of FWLS showed the closest association with the RVEF cutoff. Our results emphasize a multiparametric approach in the assessment of RV function, especially if 3D echocardiography is not available.

Deep Learning-Derived Myocardial Strain.

BACKGROUND: Echocardiographic strain measurements require extensive operator experience and have significant intervendor variability. Creating an automated, open-source, vendor-agnostic method to retrospectively measure global longitudinal strain (GLS) from standard echocardiography B-mode images would greatly improve post hoc research applications and may streamline patient analyses. OBJECTIVES: This study was seeking to develop an automated deep learning strain (DLS) analysis pipeline and validate its performance across multiple applications and populations. METHODS: Interobserver/-vendor variation of traditional GLS, and simulated effects of variation in contour on speckle-tracking measurements were assessed. The DLS pipeline was designed to take semantic segmentation results from EchoNet-Dynamic and derive longitudinal strain by calculating change in the length of the left ventricular endocardial contour. DLS was evaluated for agreement with GLS on a large external dataset and applied across a range of conditions that result in cardiac hypertrophy. RESULTS: In patients scanned by 2 sonographers using 2 vendors, GLS had an intraclass correlation of 0.29 (95% CI: -0.01 to 0.53, P = 0.03) between vendor measurements and 0.63 (95% CI: 0.48-0.74, P < 0.001) between sonographers. With minor changes in initial input contour, step-wise pixel shifts resulted in a mean absolute error of 3.48% and proportional strain difference of 13.52% by a 6-pixel shift. In external validation, DLS maintained moderate agreement with 2-dimensional GLS (intraclass correlation coefficient [ICC]: 0.56, P = 0.002) with a bias of -3.31% (limits of agreement: -11.65% to 5.02%). The DLS method showed differences (P < 0.0001) between populations with cardiac hypertrophy and had moderate agreement in a patient population of advanced cardiac amyloidosis: ICC was 0.64 (95% CI: 0.53-0.72), P < 0.001, with a bias of 0.57%, limits of agreement of -4.87% to 6.01% vs 2-dimensional GLS. CONCLUSIONS: The open-source DLS provides lower variation than human measurements and similar quantitative results. The method is rapid, consistent, vendor-agnostic, publicly released, and applicable across a wide range of imaging qualities.

Association of Right Ventricular Functional Parameters With Adverse Cardiopulmonary Outcomes: A Meta-analysis.

AIMS: We aimed to confirm that three-dimensional echocardiography-derived right ventricular ejection fraction (RVEF) is better associated with adverse cardiopulmonary outcomes than the conventional echocardiographic parameters. METHODS: We performed a meta-analysis of studies reporting the impact of unit change of RVEF, tricuspid annular plane systolic excursion (TAPSE), fractional area change (FAC), and free-wall longitudinal strain (FWLS) on clinical outcomes (all-cause mortality and/or adverse cardiopulmonary outcomes). Hazard ratios (HRs) were rescaled by the within-study SDs to represent standardized changes. Within each study, we calculated the ratio of HRs related to a 1 SD reduction in RVEF versus TAPSE, or FAC, or FWLS, to quantify the association of RVEF with adverse outcomes relative to the other metrics. These ratios of HRs were pooled using random-effects models. RESULTS: Ten independent studies were identified as suitable, including data on 1,928 patients with various cardiopulmonary conditions. Overall, a 1 SD reduction in RVEF was robustly associated with adverse outcomes (HR = 2.64 [95% CI, 2.18-3.20], P < .001; heterogeneity: I2 = 65%, P = .002). In studies reporting HRs for RVEF and TAPSE, or RVEF and FAC, or RVEF and FWLS in the same cohort, head-to-head comparison revealed that RVEF showed significantly stronger association with adverse outcomes per SD reduction versus the other 3 parameters (vs TAPSE, HR = 1.54 [95% CI, 1.04-2.28], P = .031; vs FAC, HR = 1.45 [95% CI, 1.15-1.81], P = .001; vs FWLS, HR = 1.44 [95% CI, 1.07-1.95], P = .018). CONCLUSION: Reduction in three-dimensional echocardiography-derived RVEF shows stronger association with adverse clinical outcomes than conventional right ventricular functional indices; therefore, it might further refine the risk stratification of patients with cardiopulmonary diseases.

There is more than just longitudinal strain: Prognostic significance of biventricular circumferential mechanics.

Introduction: Despite the significant contribution of circumferential shortening to the global ventricular function, data are scarce concerning its prognostic value on long-term mortality. Accordingly, our study aimed to assess both left (LV) and right ventricular (RV) global longitudinal (GLS) and global circumferential strain (GCS) using three-dimensional echocardiography (3DE) to determine their prognostic importance. Methods: Three hundred fifty-seven patients with a wide variety of left-sided cardiac diseases were retrospectively identified (64 ± 15 years, 70% males) who underwent clinically indicated 3DE. LV and RV GLS, and GCS were quantified. To determine the prognostic power of the different patterns of biventricular mechanics, we divided the patient population into four groups. Group 1 consisted of patients with both LV GLS and RV GCS above the respective median values; Group 2 was defined as patients with LV GLS below the median while RV GCS above the median, whereas in Group 3, patients had LV GLS values above the median, while RV GCS was below median. Group 4 was defined as patients with both LV GLS and RV GCS below the median. Patients were followed up for a median of 41 months. The primary endpoint was all-cause mortality. Results: Fifty-five patients (15%) met the primary endpoint. Impaired values of both LV GCS (HR, 1.056 [95% CI, 1.027-1.085], p < 0.001) and RV GCS (1.115 [1.068-1.164], p < 0.001) were associated with increased risk of death by univariable Cox regression. Patients with both LV GLS and RV GCS below the median (Group 4) had a more than 5-fold increased risk of death compared with those in Group 1 (5.089 [2.399-10.793], p < 0.001) and more than 3.5-fold compared with those in Group 2 (3.565 [1.256-10.122], p = 0.017). Interestingly, there was no significant difference in mortality between Group 3 (with LV GLS above the median) and Group 4, but being categorized into Group 3 versus Group 1 still held a more than 3-fold risk (3.099 [1.284-7.484], p = 0.012). Discussion: The impaired values of both LV and RV GCS are associated with long-term all-cause mortality, emphasizing the importance of assessing biventricular circumferential mechanics. Reduced RV GCS is associated with significantly increased risk of mortality even if LV GLS is preserved.

Deep Learning-Based Prediction of Right Ventricular Ejection Fraction Using 2D Echocardiograms.

BACKGROUND: Evidence has shown the independent prognostic value of right ventricular (RV) function, even in patients with left-sided heart disease. The most widely used imaging technique to measure RV function is echocardiography; however, conventional 2-dimensional (2D) echocardiographic assessment is unable to leverage the same clinical information that 3-dimensional (3D) echocardiography-derived right ventricular ejection fraction (RVEF) can provide. OBJECTIVES: The authors aimed to implement a deep learning (DL)-based tool to estimate RVEF from 2D echocardiographic videos. In addition, they benchmarked the tool's performance against human expert reading and evaluated the prognostic power of the predicted RVEF values. METHODS: The authors retrospectively identified 831 patients with RVEF measured by 3D echocardiography. All 2D apical 4-chamber view echocardiographic videos of these patients were retrieved (n = 3,583), and each subject was assigned to either the training or the internal validation set (80:20 ratio). Using the videos, several spatiotemporal convolutional neural networks were trained to predict RVEF. The 3 best-performing networks were combined into an ensemble model, which was further evaluated in an external data set containing 1,493 videos of 365 patients with a median follow-up time of 1.9 years. RESULTS: The ensemble model predicted RVEF with a mean absolute error of 4.57 percentage points in the internal and 5.54 percentage points in the external validation set. In the latter, the model identified RV dysfunction (defined as RVEF <45%) with an accuracy of 78.4%, which was comparable to an expert reader's visual assessment (77.0%; P = 0.678). The DL-predicted RVEF values were associated with major adverse cardiac events independent of age, sex, and left ventricular systolic function (HR: 0.924 [95% CI: 0.862-0.990]; P = 0.025). CONCLUSIONS: Using 2D echocardiographic videos alone, the proposed DL-based tool can accurately assess RV function, with similar diagnostic and prognostic power as 3D imaging.

Phenogrouping and risk stratification of patients undergoing cardiac resynchronization therapy upgrade using topological data analysis.

Choosing the optimal device during cardiac resynchronization therapy (CRT) upgrade can be challenging. Therefore, we sought to provide a solution for identifying patients in whom upgrading to a CRT-defibrillator (CRT-D) is associated with better long-term survival than upgrading to a CRT-pacemaker (CRT-P). To this end, we first applied topological data analysis to create a patient similarity network using 16 clinical features of 326 patients without prior ventricular arrhythmias who underwent CRT upgrade. Then, in the generated circular network, we delineated three phenogroups exhibiting significant differences in clinical characteristics and risk of all-cause mortality. Importantly, only in the high-risk phenogroup was upgrading to a CRT-D associated with better survival than upgrading to a CRT-P (hazard ratio: 0.454 (0.228-0.907), p = 0.025). Finally, we assigned each patient to one of the three phenogroups based on their location in the network and used this labeled data to train multi-class classifiers to enable the risk stratification of new patients. During internal validation, an ensemble of 5 multi-layer perceptrons exhibited the best performance with a balanced accuracy of 0.898 (0.854-0.942) and a micro-averaged area under the receiver operating characteristic curve of 0.983 (0.980-0.986). To allow further validation, we made the proposed model publicly available ( https://github.com/tokmarton/crt-upgrade-risk-stratification ).