Echo Research and Practice最新文献

Objective: To explore the diagnostic value of crucial parameters of echocardiography for fetal bicuspid aortic valve (BAV) and improve diagnostic accuracy.

Methods: Fetuses with a prenatal suspected diagnosis of BAV were followed, and confirmed and misdiagnosed cases were obtained. Prenatal echocardiography was reviewed and analyzed. ROC curves were plotted to evaluate the diagnostic capabilities of different echo signs.

Results: 14 cases were confirmed, and 7 patients were misdiagnosed. Some abnormal ultrasound signs were observed in both groups, including direct ultrasound signs of the aortic valve: Two commissures and a "fish-mouth" opening; Thickening, hyperechogenicity, or the presence of a raphe; Restricted motion or opening; Eccentric or a-linear valve leaflet closure line and indirect ultrasound signs: Increased supra-aortic valve velocity; Post-stenotic widening of the ascending aorta. The combination of "Increased supra-aortic valve velocity" and "Two commissures and a 'fish-mouth' opening" had the highest AUC (AUC: 0.893, 95%CI: 0.752-1.000, Sensitivity: 0.786, Specificity: 1.000).

Conclusions: We first found that the combination of "Increased supra-aortic valve velocity" and "Two commissures and a 'fish-mouth' opening" had the best diagnostic capability and could reduce the rate of misdiagnosis. Fetuses with BAV should be followed up prenatally for the aortic valve and ascending aorta as they progressively deteriorate with gestational age.

Background: Following the publication of international cardio-oncology (CO) imaging guidelines, standard echocardiographic monitoring parameters of left ventricular systolic function have been endorsed. Recommendations highlight that either two-dimensional (2D) or three-dimensional (3D) left ventricular ejection fraction (LVEF), alongside global longitudinal strain (GLS) should be routinely performed for surveillance of patients at risk of cancer therapy-related cardiac dysfunction (CTRCD). We studied the feasibility of 3D-LVEF, 2D-GLS and 2D-LVEF in a dedicated CO service.

Methods: This was a single-centre prospective analysis of consecutive all-comer patients (n = 105) referred to an NHS CO clinic. Using a dedicated Philips EPIQ CVx v7.0, with X5-1 3D-transducer and 3DQA software, we sought to acquire and analyse 2D- and 3D-LVEF and 2D-GLS, adhering to the British Society of Echocardiography (BSE) and British Cardio-Oncology Society (BCOS) transthoracic echocardiography protocol.

Results: A total of 105 patients were enrolled in the study; 5 were excluded due to carcinoid heart disease (n = 5). Calculation of 3D-LVEF was achieved in 40% (n = 40), 2D-GLS in 73% (n = 73), and 2D-LVEF in 81% (n = 81). LV quantification was not possible in 19% (n = 19) due to poor myocardial border definition. Strong correlation existed between 2D-LVEF and 3D-LVEF (r = 0.94, p < 0.0001). Bland-Altman plot demonstrated no statistical differences in that the mean deviation between 2D-LVEF and 3D-LVEF were consistent throughout a range of LVEF values. The most persistent obstacle to 3D-LVEF acquisition was insufficient myocardial border tracking (n = 30, 50%).

Conclusion: This study demonstrates the high feasibility of 2D-GLS and 2D-LVEF, even in those with challenging echocardiographic windows. The lower feasibility of 3D-LVEF limits its real-world clinical application, even though only a small difference in agreement with 2D-LVEF calculation was found when successfully performed.

Background: Cardiac resynchronization therapy (CRT) has an additive therapeutic influence on left ventricular function in heart failure patients, but the underlying mechanisms through which it works are not completely explained. Our aim was to further elucidate the role of this intervention via rotational mechanics using 2D speckle tracking echocardiography (2D-STE).

Results: We investigated 46 patients (65 ± 9 years) who received CRT. All enrolled patients were assessed on admission by 2D-STE and 6 min walk test (6 min WT) and followed in the outpatient device clinic by 2D-STE (at 1 week and 6 months post-implantation) and 6 min WT (at 6 months post-implantation). On their first appointment all biventricular systems were optimised by atrioventricular delay optimisation and by changing the temporal activation of ventricular electrodes aiming to reach the highest left ventricular effective stroke volume across all activation options. A new 2D-STE based index (twist integral) targeting to assess the rotational mechanics of the whole cardiac cycle was also measured to further explain the CRT response. Twenty-two (48%) patients were responders at 6-month follow-up and most of them had dilated cardiomyopathy. The commonest selected mode that was related with the greatest left ventricular performance response was the simultaneous activation of the 2 ventricular leads (39%). The strongest predictor of CRT response was the improvement of effective stroke volume between admission and first appointment at clinic, followed by the improvement of twist integral, the absence of coronary artery disease, and the improvement of peak systolic twist.

Conclusions: Additional CRT optimisation via changing the temporal activation of ventricular electrodes is beneficial for left ventricular performance in heart failure patients. The success of biventricular pacing may also be explained by the improvement of left ventricular rotational mechanics.

While the visual estimation of systolic left ventricular function by experienced examiners closely aligns with quantitative methodologies, the accuracy of visual estimation in determining the severity of valvular regurgitation using colour flow Doppler assessment of native heart valves remains largely unexplored. This study analysed the ability of 262 physicians to visually estimate the severity of 12 native valve regurgitations by grading colour Doppler transthoracic echocardiography loops in an online questionnaire. The assessments of the participants were compared to standardized quantitative evaluations conducted by certified echocardiography experts. Of the three valves to assess, evaluations by the participants showed the best correlation (Rs = 0.75, p < 0.0001) and agreement (percent agreement: 66.4%) with those of the experts in mitral valve regurgitation (MR). High agreement was observed for mild regurgitation across all valves (MR 94.5%, AR 80.3% and TR 88.7%), while consensus diminished in moderate (MR 55.9%, AR 49.5% and TR 55.0%) and severe regurgitation (MR 57.6%, AR 67.4%, TR 14.6%). The study underscores the potential utility of visual estimation of valvular regurgitation in clinical settings for identifying clinically relevant regurgitations. However, our findings also highlight the importance of integrating visual estimation with quantitative methods, particularly in moderate and severe cases of regurgitation.

In this paper we discuss the relevance of continuity equation based aortic valve area (AVA) calculation as a robust parameter suitable for accurate grading of aortic stenosis (AS) irrespective of flow conditions. Combining the AVA-based grading and echocardiography-based staging, can provide with the most comprehensive clinical assessment of patients with AS and preserved left ventricular systolic function to streamline management decisions.

Background: The left atrial (LA) volume has been demonstrated to be an important predictor of adverse outcome in patients with various cardiac conditions, including acute myocardial infarction (AMI). However, new treatment strategies in patients with AMI have led to better patient outcomes. We hypothesised that increased LA size could still predict mortality in patients with AMI despite improved treatment strategies.

Methods: We included patients with AMI in a prospective multicenter cohort study and the study patients were enrolled from 2014 to 2022. We recorded echocardiographic and clinical data during their index hospitalisation. Indexed LA volume (LAVi) was assessed in all patients and was used as a continuous variable in the univariate and multivariate Cox regression analysis. The study took place over a period of five years and median follow-up time was 3.8 years (range 3.1 to 5.0 years). The primary study outcomes were all-cause mortality and major adverse cardiac events (MACE). MACE was defined as hospital readmission due to myocardial infarction, cardiac arrest, stroke, heart failure, or onset of new atrial fibrillation.

Results: We included 487 patients (69 ± 12 years old, 26% female) with AMI. During the follow-up period all-cause mortality was 50 (10.3%) and patients who reached the primary outcomes were 153 (31.4%). The deceased patients had higher LAVi compared to survivors (40.0 ± 12.9 mL/m² vs. 29.7 ± 11.2 mL/m², p < 0.001). Factors associated with all-cause mortality and MACE were age, year of enrollment, left ventricular (LV) ejection fraction, LV global longitudinal strain (GLS), LV filling pressure, moderate or severe mitral regurgitation and LAVi. GLS and EF were segregated into two distinct models due to their moderately high correlation (r = 0.57, p < 0.001). LAVi remained as an independent echocardiographic predictor of primary outcomes after adjusting for the covariates above in two separates multivariable Cox regression models (hazard ratio 1.02/1.02 mL/m² [95% CI 1.01-1.03/1.01-1.03], p = 0.006/0.003).

Conclusions: Our study demonstrated that LA dilatation is an independent echocardiographic predictor of mortality and MACE in patients with AMI despite improved treatment strategies. This finding highlights the potential of using LAVi as a marker for prognostication in these patients.

Background: Hypertrophic cardiomyopathy (HCM) can cause myocardial fibrosis, which can be a substrate for fatal ventricular arrhythmias and subsequent sudden cardiac death. Although late gadolinium enhancement (LGE) on cardiac magnetic resonance (CMR) represents myocardial fibrosis and is associated with sudden cardiac death in patients with HCM, CMR is resource-intensive, can carry an economic burden, and is sometimes contraindicated. In this study for patients with HCM, we aimed to distinguish between patients with positive and negative LGE on CMR using deep learning of echocardiographic images.

Methods: In the cross-sectional study of patients with HCM, we enrolled patients who underwent both echocardiography and CMR. The outcome was positive LGE on CMR. Among the 323 samples, we randomly selected 273 samples (training set) and employed deep convolutional neural network (DCNN) of echocardiographic 5-chamber view to discriminate positive LGE on CMR. We also developed a reference model using clinical parameters with significant differences between patients with positive and negative LGE. In the remaining 50 samples (test set), we compared the area under the receiver-operating-characteristic curve (AUC) between a combined model using the reference model plus the DCNN-derived probability and the reference model.

Results: Among the 323 CMR studies, positive LGE was detected in 160 (50%). The reference model was constructed using the following 7 clinical parameters: family history of HCM, maximum left ventricular (LV) wall thickness, LV end-diastolic diameter, LV end-systolic volume, LV ejection fraction < 50%, left atrial diameter, and LV outflow tract pressure gradient at rest. The discriminant model combining the reference model with DCNN-derived probability significantly outperformed the reference model in the test set (AUC 0.86 [95% confidence interval 0.76-0.96] vs. 0.72 [0.57-0.86], P = 0.04). The sensitivity, specificity, positive predictive value, and negative predictive value of the combined model were 0.84, 0.76, 0.78, and 0.83, respectively.

Conclusion: Compared to the reference model solely based on clinical parameters, our new model integrating the reference model and deep learning-based analysis of echocardiographic images demonstrated superiority in distinguishing LGE on CMR in patients with HCM. The novel deep learning-based method can be used as an assistive technology to facilitate the decision-making process of performing CMR with gadolinium enhancement.

Background: Obstructive sleep apnoea (OSA) is present in 40-80% of patients with cardiovascular morbidity and is associated with adverse effects on cardiovascular health. Continuous positive airway pressure (CPAP) maintains airway patency during sleep and is hypothesised to improve cardiac function. In the present study, we report on the impact of 12 weeks of CPAP and improvements in echocardiographic parameters of the right ventricle (RV).

Methods: Nineteen newly diagnosed patients with OSA and a respiratory disturbance index (RDI) greater than 10 were enrolled. Echocardiography was performed before treatment and with a follow-up assessment after 12 weeks of CPAP. Echocardiographic and Doppler measurements were made following the American Society for Echocardiography guidelines. The primary outcome was isovolumetric acceleration (IVA). Secondary outcomes include tricuspid annular plane systolic excursion (TAPSE), fractional area change (FAC), RV % strain, TEI index and RV dimension (RVD1).

Results: There was significant improvement in isovolumetric acceleration of 0.5ms² (P = 0.0012 (95% CI -0.72, -0.20)) and significant improvement of 2.05 mm in TAPSE (p = 0.0379 (95% CI -3.98 - -0.13). There was no significant difference in FAC, RV % strain, TEI index or RVD1 with twelve weeks of CPAP therapy.

Conclusion: The present study highlights significant improvement in TAPSE and IVA with 12 weeks of CPAP treatment and no significant improvement in FAC, RVD1 and RV % strain. These data indicate favourable characteristics on both load dependent and load independent markers of RV function with CPAP.

Background: Current risk stratification tools for acute myocardial infarction (AMI) have limitations, particularly in predicting mortality. This study utilizes cardiac ultrasound radiomics (i.e., ultrasomics) to risk stratify AMI patients when predicting all-cause mortality.

Results: The study included 197 patients: (a) retrospective internal cohort (n = 155) of non-ST-elevation myocardial infarction (n = 63) and ST-elevation myocardial infarction (n = 92) patients, and (b) external cohort from the multicenter Door-To-Unload in ST-segment-elevation myocardial infarction [DTU-STEMI] Pilot Trial (n = 42). Echocardiography images of apical 2, 3, and 4-chamber were processed through an automated deep-learning pipeline to extract ultrasomic features. Unsupervised machine learning (topological data analysis) generated AMI clusters followed by a supervised classifier to generate individual predicted probabilities. Validation included assessing the incremental value of predicted probabilities over the Global Registry of Acute Coronary Events (GRACE) risk score 2.0 to predict 1-year all-cause mortality in the internal cohort and infarct size in the external cohort. Three phenogroups were identified: Cluster A (high-risk), Cluster B (intermediate-risk), and Cluster C (low-risk). Cluster A patients had decreased LV ejection fraction (P < 0.01) and global longitudinal strain (P = 0.03) and increased mortality at 1-year (log rank P = 0.05). Ultrasomics features alone (C-Index: 0.74 vs. 0.70, P = 0.04) and combined with global longitudinal strain (C-Index: 0.81 vs. 0.70, P < 0.01) increased prediction of mortality beyond the GRACE 2.0 score. In the DTU-STEMI clinical trial, Cluster A was associated with larger infarct size (> 10% LV mass, P < 0.01), compared to remaining clusters.

Conclusions: Ultrasomics-based phenogroup clustering, augmented by TDA and supervised machine learning, provides a novel approach for AMI risk stratification.

Background: Due to the lack of oestrogen, premature ovarian insufficiency (POI) is an independent risk factor for ischaemic heart disease and overall cardiovascular disease. This study aimed to apply layer-specific myocardial strain for early quantitative evaluation of subclinical left ventricular myocardial systolic function changes in patients with POI.

Methods: Forty-eight newly diagnosed, untreated patients with POI (POI group) and fifty healthy female subjects matched for age, height and weight (control group) were enrolled. Standard transthoracic echocardiography was used to measure conventional parameters and layer-specific strain parameters.The layer-specific strain parameters included subendomyocardial global longitudinal strain (GLSendo), mid-layer myocardial global longitudinal strain (GLSmid), subepimyocardial global longitudinal strain (GLSepi), subendomyocardial global circumferential strain (GCSendo), mid-layer myocardial global circumferential strain (GCSmid), and subepimyocardial global circumferential strain (GCSepi).

Results: There were no significant differences in age, body mass index (BMI), blood pressure, or left ventricular ejection fraction (LVEF) between the two groups. The end-diastolic interventricular septal thickness (IVST) was greater in the POI group (8.29 ± 1.32 vs. 7.66 ± 0.82, P = 0.008), and the POI group had lower E, E/A, and lateral e' (all P < 0.05). As for systolic functions,the POI group had lower GLSendo, GLSmid, GLSepi, GCSendo, GCSmid, and GCSepi (all P < 0.05).The intraobserver and interobserver coefficients of GLSendo, GLSmid, GLSepi, GCSendo, GCSmid, and GCSepi were greater than 0.900.

Conclusions: POI patients with normal LVEF may suffer from subclinical left ventricular myocardial systolic dysfunction. Echocardiography of layer-specific myocardial strain could more sensitively detect subclinical impairment of left ventricular systolic function in POI patients.