Intraventricular Flow Simulations in Singular Right Ventricles Reveal Deteriorated Washout and Low Vortex Formation

Purpose Patients with a functionally univentricular heart represent one of the most common severe cardiac lesions with a prevalence of 3 per 10,000 live births. Hemodynamics of the singular ventricle is a major research topic in cardiology and there exists a relationship between fluid dynamical features and cardiac behavior in health and disease. The aim of the present work was to compare intraventricular flow in single right ventricle (SRV) patients and subjects with healthy left hearts (LV) through patient-specific CFD simulations. Methods Three-dimensional real-time echocardiographic images were obtained for five SRV patients and two healthy subjects and CFD simulations with a moving mesh methodology were performed. Intraventricular vortex formation and vortex formation time (VFT) as well as the turbulent kinetic energy (TKE) and ventricular washout were evaluated. Results The results show significantly lower values for the VFT and the TKE in SRV patients compared with healthy LV subjects. Furthermore, vortex formation does not progress to the apex in SRV patients. These findings were confirmed by a significantly lower washout in SRV patients. Conclusions The study pinpoints the intriguing role of intraventricular flows to characterize performance of SRVs that goes beyond standard clinical metrics such as ejection fraction.

Three-dimensional printing of atrial septal defect from echocardiographic images: feasibility, fidelity and potential applications

Objectives —We sought to investigate the technical feasibility, fidelity and the potential applications of three-dimensional(3D) printed atrial septal defect (ASD) models based on three-dimensional transesophageal echocardiography (3D-TEE) images preliminarily. Methods—We retrospectively collected 40 ASD patients’ 3D-TEE images. The 3D-TEE data were imported into post-processing software to create printable 3D digital models, the patient-specific models were then printed by the 3D printer. Fidelity of the 3D printed models were quantitatively evaluated by comparing the measurements from 3D ASD models and echocardiographic data. Results —Ultrasound-derived 3D ASD models were acquired in all the forty cases successfully. There was good consistency and no significant differences in ASD size parameters among 3D printed models, 2D-TEE images and 3D-TEE images（all P>0.05）. Also, it showed small difference among 3D printed models, 2D-TEE images and 3D-TEE images in the absolute difference value of ASD size parameters. There’s a highly significant correlation between the ASD parameters including the maximal diameter, the minimal diameter and circumference measured by 3D ASD printed models and the corresponding parameters of ASD occluders applied in actual surgical procedure. Simulation exercises in the 3D ASD printed models had an impressive effect based on the comprehensive assessment of the ASD parameters. Conclusions—It is feasible to use 3D-TEE images as the data source of ASD 3D printed models. Ultrasound-derived ASD 3D printed models show highly fidelity, which contributes to provide evidence for the clinical application of 3D printing technology in decision of ASD occlusion.

Deep Learning Analysis of Echocardiographic Images to Predict Positive Genotype in Patients With Hypertrophic Cardiomyopathy

Genetic testing provides valuable insights into family screening strategies, diagnosis, and prognosis in patients with hypertrophic cardiomyopathy (HCM). On the other hand, genetic testing carries socio-economical and psychological burdens. It is therefore important to identify patients with HCM who are more likely to have positive genotype. However, conventional prediction models based on clinical and echocardiographic parameters offer only modest accuracy and are subject to intra- and inter-observer variability. We therefore hypothesized that deep convolutional neural network (DCNN, a type of deep learning) analysis of echocardiographic images improves the predictive accuracy of positive genotype in patients with HCM. In each case, we obtained parasternal short- and long-axis as well as apical 2-, 3-, 4-, and 5-chamber views. We employed DCNN algorithm to predict positive genotype based on the input echocardiographic images. We performed 5-fold cross-validations. We used 2 reference models—the Mayo HCM Genotype Predictor score (Mayo score) and the Toronto HCM Genotype score (Toronto score). We compared the area under the receiver-operating-characteristic curve (AUC) between a combined model using the reference model plus DCNN-derived probability and the reference model. We calculated the p-value by performing 1,000 bootstrapping. We calculated sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). In addition, we examined the net reclassification improvement. We included 99 adults with HCM who underwent genetic testing. Overall, 45 patients (45%) had positive genotype. The new model combining Mayo score and DCNN-derived probability significantly outperformed Mayo score (AUC 0.86 [95% CI 0.79–0.93] vs. 0.72 [0.61–0.82]; p < 0.001). Similarly, the new model combining Toronto score and DCNN-derived probability exhibited a higher AUC compared to Toronto score alone (AUC 0.84 [0.76–0.92] vs. 0.75 [0.65–0.85]; p = 0.03). An improvement in the sensitivity, specificity, PPV, and NPV was also achieved, along with significant net reclassification improvement. In conclusion, compared to the conventional models, our new model combining the conventional and DCNN-derived models demonstrated superior accuracy to predict positive genotype in patients with HCM.

Giant right atrium, what does it hide? Case presentation

Background Malformation of the right atrium is a rare cardiac abnormality and is usually reported as isolated malformation in the literature. Case presentation Prenatal giant atrial dilatation in an asymptomatic infant was treated surgically at 18 months of age, due to potential risk of thrombosis and arrhythmias. Post-surgical echocardiographic images illustrate residual atrial elevated pressure. Conclusions Sometimes, as seems in our case, right atrial dilatation hides an associated restrictive right ventricle.

Cardiac Ultrasound under Speckle Tracking Technology Based Analysis of Efficacy of Respiratory Rehabilitation on Chronic Obstructive Pulmonary Disease

The study shined spotlight on the effect of respiratory rehabilitation training on chronic obstructive pulmonary disease (COPD), which was evaluated using speckle ultrasound algorithm-based cardiac ultrasound. Then, 90 patients with stable COPD, who were admitted to the hospital from January 2018 to December 2019, were randomly rolled into three groups, namely, the fast inhalation and slow exhalation (A) group, abdominal breathing (B) group, and control (C) group. For group A, on the basis of the conventional treatment, the method of rapid inhalation and slow exhalation was adopted. The group B (n = 30) adopted the abdominal breathing method besides the conventional treatment. In addition, the group C (n = 30) received only conventional treatment. Finally, the efficacy and parameters of the three treatment methods were compared. The echocardiographic parameters and echocardiographic images were calculated and processed by the speckle tracking method. Three kinds of operators were used to track the myocardial spots successfully, and the corresponding points in the image were obtained and calculated. It was found that there was no significant difference in the degree of dyspnea, exercise endurance, lung function, respiratory muscle function, and quality of life (QOL) before treatment P > 0.05 . After treatment, in contrast with group C, the previously mentioned indicators in groups A and B were obviously better P < 0.05 . Further, both the echocardiographic images and echocardiographic parameters of groups A and B were obviously improved, and there was no obvious difference between groups A and B. Hence, some degree of respiratory rehabilitation was very effective in the diagnosis of patients with chronic pulmonary obstruction. In conclusion, the speckle tracking algorithm-based cardiac ultrasound improves the image quality. At the same time, respiratory rehabilitation training is effective on COPD and worthy of clinical promotion.

Machine Learning Augmented Echocardiography for Diastolic Function Assessment

Cardiac diastolic dysfunction is prevalent and is a diagnostic criterion for heart failure with preserved ejection fraction—a burgeoning global health issue. As gold-standard invasive haemodynamic assessment of diastolic function is not routinely performed, clinical guidelines advise using echocardiography measures to determine the grade of diastolic function. However, the current process has suboptimal accuracy, regular indeterminate classifications and is susceptible to confounding from comorbidities. Advances in artificial intelligence in recent years have created revolutionary ways to evaluate and integrate large quantities of cardiology data. Imaging is an area of particular strength for the sub-field of machine-learning, with evidence that trained algorithms can accurately discern cardiac structures, reliably estimate chamber volumes, and output systolic function metrics from echocardiographic images. In this review, we present the emerging field of machine-learning based echocardiographic diastolic function assessment. We summarise how machine-learning has made use of diastolic parameters to accurately differentiate pathology, to identify novel phenotypes within diastolic disease, and to grade diastolic function. Perspectives are given about how these innovations could be used to augment clinical practice, whilst areas for future investigation are identified.

Echocardiographic Diagnostics of Heart Tumors

The article focuses on ultrasound diagnosis of cardiac tumors (CT). In recent time, the frequency of detecting cardiac neoplasm has been growing. Correct diagnosis at an early stage of the process would allow timely treatment. Before the introduction of two-dimensional echocardiography (EchoCG), life-time diagnosis of CT was very rare. This article describes major echocardiographic criteria for most common benign, malignant, and metastatic CTs. The article is illustrated with original echocardiographic images.