Journal of Echocardiography最新文献

Background: Right ventricular (RV) dysfunction is a key determinant of mortality in heart failure with reduced left ventricular ejection fraction (HFrEF). RV stroke work index (RVSWI) is an established invasive parameter of RV function; however, echocardiographic methods for estimating RVSWI have not yet been fully established. We hypothesized that the pulmonary regurgitant (PR) velocity waveform-derived early-diastolic pulmonary artery-RV pressure gradient (PRPG) would allow an accurate estimation of RVSWI because of its fidelity to the original formula. This study aimed to investigate whether non-invasive estimation of RVSWI is feasible in patients with HFrEF.

Methods: In this retrospective study, 120 adult patients with HFrEF who underwent right heart catheterization within 24 h of echocardiography were included. RVSWI was calculated as (mean pulmonary artery pressure - mean right atrial pressure) × stroke volume index (SVI). Based on the continuous-wave Doppler velocity measurements of PR, echocardiographic estimation of RVSWI was calculated as PRPG × pulsed-wave Doppler-derived SVI (RVSWI_PR).

Results: The RVSWI_PR was significantly correlated with RVSWI (ρ = 0.670, p < 0.001). Bland-Altman analysis showed no direct fixed bias. Sensitivity analysis performed in 21 patients with HFrEF and severe tricuspid regurgitation, which is a challenging subgroup for non-invasive RV function assessment, showed similar results. In the receiver operating characteristic curve analyses to detect the patients with RVSWI < 250 mmHg∙mL/m², the area under the curve was 0.954, and a cut-off value of 371 mmHg∙mL/m² showed 100% sensitivity and 82% specificity.

Conclusions: RVSWI_PR, based on PR velocity waveform analysis, was useful for the non-invasive assessment of RVSWI in HFrEF.

Background: This study aims to present the Segmentation-based Myocardial Advanced Refinement Tracking (SMART) system, a novel artificial intelligence (AI)-based framework for transthoracic echocardiography (TTE) that incorporates motion tracking and left ventricular (LV) myocardial segmentation for automated LV mass (LVM) and global longitudinal strain (LVGLS) assessment.

Methods: The SMART system demonstrates LV speckle tracking based on motion vector estimation, refined by structural information using endocardial and epicardial segmentation throughout the cardiac cycle. This approach enables automated measurement of LVM_SMART and LVGLS_SMART. The feasibility of SMART is validated in 111 hypertrophic cardiomyopathy (HCM) patients (median age: 58 years, 69% male) who underwent TTE and cardiac magnetic resonance imaging (CMR).

Results: LVGLS_SMART showed a strong correlation with conventional manual LVGLS measurements (Pearson's correlation coefficient [PCC] 0.851; mean difference 0 [-2-0]). When compared to CMR as the reference standard for LVM, the conventional dimension-based TTE method overestimated LVM (PCC 0.652; mean difference: 106 [90-123]), whereas LVM_SMART demonstrated excellent agreement with CMR (PCC 0.843; mean difference: 1 [-11-13]). For predicting extensive myocardial fibrosis, LVGLS_SMART and LVM_SMART exhibited performance comparable to conventional LVGLS and CMR (AUC: 0.72 and 0.66, respectively). Patients identified as high risk for extensive fibrosis by LVGLS_SMART and LVM_SMART had significantly higher rates of adverse outcomes, including heart failure hospitalization, new-onset atrial fibrillation, and defibrillator implantation.

Conclusions: The SMART technique provides a comparable LVGLS evaluation and a more accurate LVM assessment than conventional TTE, with predictive values for myocardial fibrosis and adverse outcomes. These findings support its utility in HCM management.

Tricuspid regurgitation (TR), previously considered a secondary valvular disorder with limited clinical implications, is now recognized as a progressive and prognostically significant disease. The increasing prevalence due to aging populations and common comorbidities, such as atrial fibrillation and heart failure, has underscored the clinical urgency of addressing TR effectively. Transcatheter tricuspid valve interventions (TTVI) have emerged as valuable therapeutic alternatives, especially for patients at high surgical risk. This review addresses critical clinical questions regarding optimal intervention timing, patient selection, and treatment strategies, focusing particularly on disease progression, right-ventricular (RV) function, and recent clinical evidence. It emphasizes the importance of early identification and monitoring through echocardiographic and laboratory parameters, comprehensive risk stratification including pulmonary hypertension assessment, and the practical use of predictive tools such as TRISCORE. We summarize current guidelines for surgical versus transcatheter interventions and discuss advancements and limitations of transcatheter therapies, particularly transcatheter edge-to-edge repair (TEER) and transcatheter tricuspid valve replacement (TTVR). Ultimately, individualized decision-making based on anatomical considerations, RV function, and comorbidity burden is vital to maximizing therapeutic outcomes.

Background: Previous studies have reported that left atrial (LA) and left ventricular (LV) strain at rest can predict exercise-induced elevated LV filling pressure. However, head to head comparison of LA and LV strain is very limited. The purpose of this study was to compare the peak atrial longitudinal stain (PALS) and LV global longitudinal strain (GLS) in the prediction of exercise-induced elevated LV filling pressure.

Methods: From January 2018 to December 2022, 286 consecutive patients underwent treadmill stress echocardiography. Patients with atrial fibrillation, septal E/e' ≥ 15 at rest, and LV ejection fraction < 50% were excluded from the study. Patients lacking PALS or GLS and those with exercise-induced LV wall motion abnormality were also excluded. Finally, 204 patients were enrolled to the analysis. All patients underwent symptom-limited treadmill stress echocardiography, and exercise-induced elevated LV filling pressure was defined as post-exercise septal E/e' ≥ 15.

Results: Forty eight of the 204 patients had post-exercise septal E/e' ≥ 15. Receiver operator characteristic curve analysis revealed the best cutoff value of 23.8% for PALS (sensitivity 67%, specificity 66%, respectively) and -17.7% for GLS (sensitivity 85%, specificity 65%, respectively) to predict post-exercise septal E/e' ≥ 15. Univariate logistic analysis demonstrated that higher age, impaired PALS, impaired GLS, and raised septal E/e' at rest were associated with post-exercise septal E/e' ≥ 15. However, multivariate logistic analysis revealed that age, GLS, and E/e' were independent predictors of post-exercise septal E/e' ≥ 15, but PALS was not.

Conclusions: Both impaired PALS and GLS at rest can predict post-exercise septal E/e' ≥ 15.0 modestly. However, multivariate logistic analysis has demonstrated that impaired GLS, not PALS, was an independent predictor of exercise-induced elevated LV filling pressure estimated by post-exercise septal E/e' ≥ 15.

Artificial intelligence (AI) is rapidly transforming the field of echocardiography. By leveraging machine learning, particularly deep learning, AI enhances image acquisition, interpretation, and diagnostic accuracy. It addresses long-standing limitations of echocardiography, such as operator dependency and inter-observer variability. AI-enabled systems, ranging from probe guidance to automated quantification tools, have improved image quality and reduced variability in key measurements such as left ventricular ejection fraction (LVEF). Recent studies show that AI can assist in disease classification, detect regional wall motion abnormalities, and predict disease progression with accuracy comparable to expert assessment. Despite these advances, several challenges remain. Concerns regarding data bias, limited generalizability across populations and devices, and the "black-box" nature of many AI models hinder clinical adoption. Ethical issues, including data privacy and unequal access to digital technologies, also require careful attention. Importantly, AI should be viewed not as a replacement for human expertise but as a tool to augment clinical decision-making and improve workflow efficiency. Looking ahead, integrating echocardiographic data with other clinical information through AI could enable earlier diagnosis and better patient management. As technology evolves, AI is expected to reinforce echocardiography's role as a non-invasive, widely available, and highly informative diagnostic modality. Continued research and rigorous validation are essential to ensure the safe, equitable, and effective use of AI in clinical echocardiography.

Purpose: We performed intraoperative pericardial three-dimensional echocardiography (IP3DE) for atrioventricular valve (AVV) repair in patients with congenital heart disease. In this study, we retrospectively reviewed the surgical cases of AVV repair and assessed the impact of IP3DE.

Methods: We reviewed the medical records of patients who underwent AVV repair at Nagano Children's Hospital. Patients were divided into two groups, the IP3DE group and the control group, which underwent two-dimensional transesophageal or transthoracic echocardiography. Clinical data, including the grade of regurgitation and re-intervention, were compared between the two groups.

Results: Forty-six patients in the IP3DE group and 35 in the control group were included. The preoperative median grade was 3 (maximum 2-minimum 4) and 3 (2-4) in the IP3DE and control groups, respectively. After surgery, median grade was decreased to 1 (1-4) and 2 (1-4) in the IP3DE and control groups, respectively. 80% and 54% of patients showed successful outcome (grade ≤ 2 after repair) in the IP3DE and control groups, respectively, which demonstrated that IP3DE contributed significantly to successful outcome (p < 0.05).

Conclusions: This study demonstrated, for the first time, the effectiveness of IP3DE in AVV repair in pediatric patients. IP3DE allows the visualization of clear 3D images and easy information sharing among cardiac vascular surgeons.

Background: Non-ST-elevation myocardial infarction (NSTEMI) is conventionally attributed to subtotal or transient occlusion. ECG is crucial but has limited sensitivity for detecting acute total occlusion in patients with NSTEMI. We propose that speckle tracking echocardiography-derived indices serve as early indicators of coronary artery occlusion in NSTEMI.

Methods: In this case-control study, 47 patients with first-time hemodynamically stable NSTEMI were enrolled and underwent echocardiography and coronary angiography. Patients were divided into acute occlusion and non-occlusion groups for analysis. Reproducibility analysis was done in a separate cohort of 22 patients with each patient undergoing three sets of strain echocardiography analysis: twice by the principal observer on two different instances (for intra-observer reproducibility) and once by second observer on the first instance (for inter-observer reproducibility).

Results: The study included 24 cases (patients with acute total occlusion) and 23 controls (patients without acute total occlusion). There was no difference between the two groups in relation to baseline characteristics. Left-ventricular global longitudinal strain (GLS) did not differ significantly between the two groups. Median longitudinal strain (LS) of the culprit artery territory was significantly lower in the cases group [8.1(7.1-12.6) vs 11.6(10.9-14.1), and p = 0.003]. The lowest recorded mean territorial (LRMT) LS of any territory in a given patient was significantly lower in the cases group compared to the control group [8.1(6.7-12.1) vs. 11(10.2-13), p = 0.04). The receiver-operator curve of LRMT LS showed an area under the curve of 0.74. A cut-off value 10.7 for LRMT LS had a sensitivity of 70.8% and specificity of 70% in detecting acute total occlusion. Reproducibility analysis of GLS and territorial strain (each territory separately) showed moderate-to-good [interclass correlation coefficient (ICC)) of ≥ 0.5] inter-observer and intra-observer reproducibility in most of parameters except in territorial strain of left circumflex artery territory which showed poor intra-observer reproducibility (ICC of 0.49).

Conclusion: The lowest recorded mean territorial LS in patients with NSTEMI showed promising sensitivity and specificity in detecting acute total occlusion.