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BackgroundThe use of apical views focused on the left atrium (LA) has improved the accuracy of LA volume evaluation by two-dimensional (2D) echocardiography. However, routine cardiovascular magnetic resonance (CMR) evaluation of LA volumes still uses standard 2- and 4-chamber cine images focused on the left ventricle (LV). To investigate the potential of LA-focused CMR cine images, we compared LA maximuml (LAVmax) and minimum (LAVmin) volumes, and emptying fraction (LAEF), calculated on both standard and LA-focused long-axis cine images, with LA volumes and LAEF obtained by short-axis cine stacks covering the LA. LA strain was also calculated and compared between standard and LA-focused images.MethodsLA volumes and LAEF were obtained from 108 consecutive patients by applying the biplane area-length algorithm to both standard and LA-focused 2- and 4-chamber cine images. Manual segmentation of a short-axis cine stack covering the LA was used as the reference method. In addition, LA strain reservoir (εs), conduit (εe) and booster pump (εa) were calculated using CMR feature-tracking.ResultsCompared to the reference method, the standard approach significantly underestimated LA volumes (LAVmax: bias − 13 ml; LOA =  + 11, − 37 ml; LAVmax i: bias − 7 ml/m2; LOA =  + 7, − 21 ml/m2; LAVmin; bias − 10 ml, LOA: + 9, − 28 ml; LAVmin i: bias − 5 ml/m2, LOA: + 5, − 16 ml/m2), and overestimated LA-EF (bias 5%, LOA: + 23, − 14%). Conversely, LA volumes (LAVmax: bias 0 ml; LOA: + 10, − 10 ml; LAVmax i: bias 0 ml/m2; LOA: + 5, − 6 ml/m2; LAVmin: bias − 2 ml; LOA: + 7, − 10 ml; LAVmin i: bias − 1 ml/m2; LOA: + 3, − 5 ml/m2) and LAEF (bias 2%, LOA: + 11, − 7%) by LA-focused cine images were similar to those measured using the reference method. LA volumes by LA-focused images were obtained faster than using the reference method (1.2 vs 4.5 min, p < 0.001). LA strain (εs: bias 7%, LOA = 25, − 11%; εe: bias 4%, LOA = 15, − 8%; εa: bias 3%, LOA = 14, − 8%) was significantly higher in standard vs. LA-focused images (p < 0.001).ConclusionLA volumes and LAEF measured using dedicated LA-focused long-axis cine images are more accurate than using standard LV-focused cine images. Moreover, LA strain is significantly lower in LA-focused vs. standard images.

Transthoracic echocardiography is the first-line imaging modality in the assessment of right-sided valve disease. The principle objectives of the echocardiographic study are to determine the aetiology, mechanism and severity of valvular dysfunction, as well as consequences on right heart remodelling and estimations of pulmonary artery pressure. Echocardiographic data must be integrated with symptoms, to inform optimal timing and technique of interventions. The most common tricuspid valve abnormality is regurgitation secondary to annular dilatation in the context of atrial fibrillation or left-sided heart disease. Significant pulmonary valve disease is most commonly seen in congenital heart abnormalities. The aetiology and mechanism of tricuspid and pulmonary valve disease can usually be identified by 2D assessment of leaflet morphology and motion. Colour flow and spectral Doppler are required for assessment of severity, which must integrate data from multiple imaging planes and modalities. Transoesophageal echo is used when transthoracic data is incomplete, although the anterior position of the right heart means that transthoracic imaging is often superior. Three-dimensional echocardiography is a pivotal tool for accurate quantification of right ventricular volumes and regurgitant lesion severity, anatomical characterisation of valve morphology and remodelling pattern, and procedural guidance for catheter-based interventions. Exercise echocardiography may be used to elucidate symptom status and demonstrate functional reserve. Cardiac magnetic resonance and CT should be considered for complimentary data including right ventricular volume quantification, and precise cardiac and extracardiac anatomy. This British Society of Echocardiography guideline aims to give practical advice on the standardised acquisition and interpretation of echocardiographic data relating to the pulmonary and tricuspid valves.

[...]it facilitates the planimetry of the anatomical orifice and 3D color-Doppler of the vena contracta.5 These enhance our ability to interpret the degree of stenosis6 and/or the cause of insufficiency with greater accuracy. A critical barrier lies in not dedicating enough time to study the PV and overlooking the crucial role of 3DE in assessing valve function, which is equally applicable to the PV.9 The future of PV imaging depends on the refinement of 3DE techniques via continuous research and development, expansion of its clinical applications, and improvement in its accessibility. Authorship Contributions: Concept- T.K.Ö., L.P.B.; Design- T.K.Ö.; Literature Review- T.K.Ö.; Writing- T.K.Ö., L.P.B.; Critical Review- T.K.Ö., L.P.B. Conflict of Interest: No conflict of interest was declared by the authors Kavalerchyk V, Aslan U, Kemaloğlu Öz T. Three-Dimensional Echocardiography: A Promising Tool for the Diagnosis of Quadricuspid Pulmonary Valve and Pulmonary Artery Aneurysm.

Purpose Our clinical observations showed clot formations in different regions of the left ventricle of the heart in some COVID-19 patients with normal myocardial motion and coronary artery. The aim of this study was to examine the changes caused by COVID-19 disease on blood flow inside the heart as a possible etiology of intracardiac clot formation. Methods In a synergic convergence of mathematics, computer science, and cardio-vascular medicine, we evaluated patients hospitalized due to COVID-19 without cardiac symptoms who underwent two-dimensional echocardiography. Patients with normal myocardial motions on echocardiography, normal coronary findings on noninvasive cardio-vascular diagnostic tests, and normal cardiac biochemical examinations but who presented with a clot in their left ventricle were included. To display the velocity vectors of the blood in the left ventricle, motion and deformation echocardiographic data were imported into MATLAB software. Results Analysis and output of the MATLAB program indicted anomalous blood flow vortices inside the left ventricular cavity, indicating irregular flow and turbulence of the blood inside the left ventricle in COVID-19 patients. Conclusion Our results suggest that in some COVID-19 patients, cardiac wall motion is not satisfactorily able to circulate the blood fluid in normal directions and that, despite normal myocardium, changes in the directions of blood flow inside the left ventricle might lead to clots in different zones. This phenomenon may be related to changes in blood properties, such as viscosity.

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.

Aims Exercise right heart catheterization (RHC) is considered the gold‐standard test to diagnose heart failure with preserved ejection fraction (HFpEF). However, exercise RHC is an insufficiently standardized technique, and current haemodynamic thresholds to define HFpEF are not universally accepted. We sought to describe the exercise haemodynamics profile of HFpEF cohorts reported in literature, as compared with control subjects. Methods and results We performed a systematic literature review until December 2020. Studies reporting pulmonary artery wedge pressure (PAWP) at rest and peak exercise were extracted. Summary estimates of all haemodynamic variables were evaluated, stratified according to body position (supine/upright exercise). The PAWP/cardiac output (CO) slope during exercise was extrapolated. Twenty‐seven studies were identified, providing data for 2180 HFpEF patients and 682 controls. At peak exercise, patients with HFpEF achieved higher PAWP (30 [29–31] vs. 16 [15–17] mmHg, P < 0.001) and mean right atrial pressure (P < 0.001) than controls. These differences persisted after adjustment for age, sex, body mass index, and body position. However, peak PAWP values were highly heterogeneous among the cohorts (I2 = 93%), with a relative overlap with controls. PAWP/CO slope was steeper in HFpEF than in controls (3.75 [3.20–4.28] vs. 0.95 [0.30–1.59] mmHg/L/min, P value < 0.0001), even after adjustment for covariates (P = 0.007). Conclusions Despite methodological heterogeneity, as well as heterogeneity of pooled haemodynamic estimates, the exercise haemodynamic profile of HFpEF patients is consistent across studies and characterized by a steep PAWP rise during exercise. More standardization of exercise haemodynamics may be advisable for a wider application in clinical practice.

Rapid development of artificial intelligence (AI) is gaining grounds in medicine. Its huge impact and inevitable necessity are also reflected in cardiovascular imaging. Although AI would probably never replace doctors, it can significantly support and improve their productivity and diagnostic performance. Many algorithms have already proven useful at all stages of the cardiac imaging chain. Their crucial practical applications include classification, automatic quantification, notification, diagnosis, and risk prediction. Consequently, more reproducible and repeatable studies are obtained, and personalized reports may be available to any patient. Utilization of AI also increases patient safety and decreases healthcare costs. Furthermore, AI is particularly useful for beginners in the field of cardiac imaging as it provides anatomic guidance and interpretation of complex imaging results. In contrast, lack of interpretability and explainability in AI carries a risk of harmful recommendations. This review was aimed at summarizing AI principles, essential execution requirements, and challenges as well as its recent applications in cardiovascular imaging.Rapid development of artificial intelligence (AI) is gaining grounds in medicine. Its huge impact and inevitable necessity are also reflected in cardiovascular imaging. Although AI would probably never replace doctors, it can significantly support and improve their productivity and diagnostic performance. Many algorithms have already proven useful at all stages of the cardiac imaging chain. Their crucial practical applications include classification, automatic quantification, notification, diagnosis, and risk prediction. Consequently, more reproducible and repeatable studies are obtained, and personalized reports may be available to any patient. Utilization of AI also increases patient safety and decreases healthcare costs. Furthermore, AI is particularly useful for beginners in the field of cardiac imaging as it provides anatomic guidance and interpretation of complex imaging results. In contrast, lack of interpretability and explainability in AI carries a risk of harmful recommendations. This review was aimed at summarizing AI principles, essential execution requirements, and challenges as well as its recent applications in cardiovascular imaging.

Background Data about the right ventricular (RV) mechanics adaptation to volume overload in patients with repaired tetralogy of Fallot (rToF) are limited. Accordingly, we sought to assess the mechanics of the functional remodeling occurring in the RV of rToF with severe pulmonary regurgitation. Methods We used three-dimensional transthoracic echocardiography (3DTE) to obtain RV data sets from 33 rToF patients and 30 age- and sex- matched controls. A 3D mesh model of the RV was generated, and RV global and regional longitudinal (LS) and circumferential (CS) strain components, and the relative contribution of longitudinal (LEF), radial (REF) and anteroposterior (AEF) wall motion to global RV ejection fraction (RVEF) were computed using the ReVISION method. Results Corresponding to decreased global RVEF (45 ± 6% vs 55 ± 5%, p < 0.0001), rToF patients demonstrated lower absolute values of LEF (17 ± 4 vs 28 ± 4), REF (20 ± 5 vs 25 ± 4) and AEF (17 ± 5 vs 21 ± 4) than controls (p < 0.01). However, only the relative contribution of LEF to global RVEF (0.39 ± 0.09 vs 0.52 ± 0.05, p < 0.0001) was significantly decreased in rToF, whereas the contribution of REF (0.45 ± 0.08 vs 0.46 ± 0.04, p > 0.05) and AEF (0.38 ± 0.09 vs 0.39 ± 0.04, p > 0.05) to global RVEF was similar to controls. Accordingly, rToF patients showed lower 3D RV global LS (-16.94 ± 2.9 vs -23.22 ± 2.9, p < 0.0001) and CS (-19.79 ± 3.3 vs -22.81 ± 3.5, p < 0.01) than controls. However, looking at the regional RV deformation, the 3D CS was lower in rToF than in controls only in the basal RV free-wall segment (p < 0.01). 3D RV LS was reduced in all RV free-wall segments in rToF (p < 0.0001), but similar to controls in the septum (p > 0.05). Conclusions 3DTE allows a quantitative evaluation of the mechanics of global RVEF. In rToF with chronic volume overload, the relative contribution of the longitudinal shortening to global RVEF is affected more than either the radial or the anteroposterior components.

Despite standardization efforts, vendors still use specific proprietary software algorithms for echocardiographic strain measurements, which result in high inter-vendor variability. Using vendor-independent software could be one solution. Little is known, however, how vendor specific image characteristics can influence tracking results of such software. We therefore investigated the reproducibility, accuracy, and scar detection ability of strain measurements on images from different vendors by using a vendor-independent software. A vendor-independent software (TomTec Image Arena) was used to analyse datasets of 63 patients which were obtained on machines from four different ultrasound machine vendors (GE, Philips, Siemens, Toshiba). We measured the tracking feasibility, inter-vendor bias, the relative test-re-test variability and scar discrimination ability of strain measurements. Cardiac magnetic resonance delayed enhancement images were used as the reference standard of scar definition. Tracking feasibility on vendor datasets were significantly different (p < 0.001). Variability of global longitudinal strain (GLS) measurements was similar among the vendors whereas variability of segmental longitudinal strain (SLS) showed modest difference. Relative test-re-test variability of GLS and SLS showed no relevant differences. No significant difference in scar detection capability was observed. Average GLS and SLS values were similar among vendors. Reproducibility of GLS measurements showed no difference among vendors and was in acceptable range. SLS reproducibility was high but similar for all vendors. No relevant difference was found for identifying regional dysfunction. Tracking feasibility showed a substantial difference among images from different vendors. Our findings demonstrate that tracking results depend mainly on the software used and show little influence from vendor specific image characteristics.