Abstract
The digital analysis of heart sounds has revealed itself as an evolving field of study. In recent years, numerous approaches to create decision support systems were attempted. This paper proposes two novel algorithms: one for the segmentation of heart sounds into heart cycles and another for detecting heart murmurs. The segmentation algorithm, based on the autocorrelation function to find the periodic components of the PCG signal had a sensitivity and positive predictive value of 89.2% and 98.6%, respectively. The murmur detection algorithm is based on features collected from different domains and was evaluated in two ways: a random division between train and test set and a division according to patients. The first returned sensitivity and specificity of 98.42% and 97.21% respectively for a minimum error of 2.19%. The second division had a far worse performance with a minimum error of 33.65%. The operating point was chosen at sensitivity 69.67% and a specificity 46.91% for a total error of 38.90% by varying the percentage of segments classified as murmurs needed for a positive murmur classification.

Abstract
Objectives: This study sought to evaluate whether velocity of naturally occurring myocardial shear waves (SW) could relate to myocardial stiffness (MS) in vivo. Background: Cardiac SW imaging has been proposed as a noninvasive tool to assess MS. SWs occur after mechanical excitation of the myocardium (e.g., mitral valve closure [MVC] and aortic valve closure [AVC]), and their propagation velocity is theoretically related to MS, thus providing an opportunity to assess stiffness at end-diastole (ED) and end-systole. However, given that SW propagation in vivo is complex, it remains unclear whether natural SW velocity effectively relates to MS. Methods: This study prospectively enrolled 50 healthy volunteers (HV) (43.7 ± 17.1 years of age) and 18 patients with cardiac amyloidosis (CA) (68.0 ± 9.8 years of age). HV were divided into 3 age groups: group I, 20 to 39 years of age (n = 24); group II, 40 to 59 years of age (n = 11); and group III, 60 to 80 years of age (n = 15). Parasternal long-axis views were acquired using an experimental scanner. Tissue (Doppler) acceleration maps were extracted from an anatomical M-mode along the midline of the left ventricular septum. Results: SW propagation velocity was significantly higher in CA patients than in HV after both MVC (3.54 ± 0.93 m/s vs. 6.33 ± 1.63 m/s, respectively; p < 0.001) and AVC (3.75 ± 0.76 m/s vs. 5.63 ± 1.13 m/s, respectively; p < 0.001). Similarly, SW propagation velocity differed significantly among age groups in HV, with a significantly higher value for group III than for group I, both occurring after MVC (p < 0.001) and AVC (p < 0.01). Moreover, SW propagation velocity after MVC was found to be significantly higher in patients with an increasing grade of diastolic dysfunction (p < 0.001). Finally, positive correlation was found between SW velocities after MVC and mitral inflow-to-mitral relaxation velocity ratio (E/E') (r = 0.74; p = 0.002). Conclusions: End-diastole SW velocities were significantly higher in patients with CA, patients with a higher grade of diastolic dysfunction, and elderly volunteers. These findings thus suggest that the speed of naturally induced SWs may be related to MS. © 2019 American College of Cardiology Foundation

Abstract
Delineation of the cardiac structures from 2D echocardiographic images is a common clinical task to establish a diagnosis. Over the past decades, the automation of this task has been the subject of intense research. In this paper, we evaluate how far the state-of-the-art encoder-decoder deep convolutional neural network methods can go at assessing 2D echocardiographic images, i.e., segmenting cardiac structures and estimating clinical indices, on a dataset, especially, designed to answer this objective. We, therefore, introduce the cardiac acquisitions for multi-structure ultrasound segmentation dataset, the largest publicly-available and fully-annotated dataset for the purpose of echocardiographic assessment. The dataset contains two and four-chamber acquisitions from 500 patients with reference measurements from one cardiologist on the full dataset and from three cardiologists on a fold of 50 patients. Results show that encoder-decoder-based architectures outperform state-of-the-art non-deep learning methods and faithfully reproduce the expert analysis for the end-diastolic and end-systolic left ventricular volumes, with a mean correlation of 0.95 and an absolute mean error of 9.5 ml. Concerning the ejection fraction of the left ventricle, results are more contrasted with a mean correlation coefficient of 0.80 and an absolute mean error of 5.6%. Although these results are below the inter-observer scores, they remain slightly worse than the intra-observer's ones. Based on this observation, areas for improvement are defined, which open the door for accurate and fully-automatic analysis of 2D echocardiographic images.

Abstract
Background: Patients with single ventricle physiology and Fontan circulation are at increased risk for late complications and reduced survival. The aim of the study was to investigate the correlation between ventricular geometry and systolic regional function in different underlying anatomic conditions in adolescent and adult Fontan-palliated patients. Method: In a retrospective cross-sectional study, we measured 2D strain, ventricular diameters, ventricular volumes, ejection fraction (EF), global and segmental wall stress, and sphericity index. The same analyses were performed in 99 age- and gender-matched healthy individuals. Results: One hundred and one patients were included at a mean age of 21 (range 14–59) years. In comparison with healthy subjects, patients with Fontan circulation displayed larger ventricular volumes (153 ± 78 mL vs 116 ± 38 mL P < 0.05), reduced EF (43% ± 15% vs 55% ± 8% P < 0.05), reduced longitudinal (-13% ± 6% vs -21% ± 4% P < 0.05) and circumferential strain values (-15% ± 7% vs -22% ± 4% P < 0.05). Functionally single ventricles were more spherical (ratio of longitudinal to short-axis diameters 1.3 ± 0.3 vs 1.7 ± 0.2 P < 0.05). Circumferential strain correlated well with global wall stress and the degree of sphericity (R 2  = 0.320), while segmental strain did not correlate with segmental wall stress. The percentage of segments with akinesia was relatively high (16 ± 16% vs 0 ± 0% P < 0.05) indicating reduced segmental contractile function. Conclusion: Functionally single ventricles after Fontan palliation have significantly reduced systolic regional and global function with a high intersegmental inhomogeneity. The underlying pathological mechanisms might be multifactorial, including ventricular geometry, sphericity, and regional contractile properties. Future studies are needed to investigate the role of ventricular geometry for clinical performance and outcome. © 2018 Wiley Periodicals, Inc.

Abstract
Quantitative assessment of mitral valve (MV) morphology is important for diagnosing MV pathology and for planning of reparative procedures. Although this is typically done using 3D transesophageal echocardiography (TEE), recent advances in the spatiotemporal resolution of 3D transthoracic echocardiography (TTE) have enabled the use of this more patient friendly modality. However, manual data analysis is time consuming and operator dependent. In this study, a fully automatic method for MV segmentation and tracking in 3D TTE is proposed and validated. The proposed framework takes advantage of a previously proposed left ventricle (LV) segmentation framework to localize the MV and performs segmentation based on the B-spline Explicit Active Surfaces (BEAS) framework. The orientation of the MV is obtained and the MV surface is cropped to the mitral annulus (MA) and divided into posterior and anterior leaflets. The segmented MV at end diastole (ED) is propagated to end systole (ES) using localized anatomical affine optical flow (lAAOF). Because the orientation and leaflet division is known, relevant clinical parameters can then be extracted from the mesh at any time point. The proposed framework shows excellent segmentation results with a mean absolute distance (MAD) and Hausdorff distance (HD) of 1.19 +/- 0.25 mm and 5.79 +/- 1.25 mm at ED and 1.39 +/- 0.32 mm and 6.70 +/- 1.97 mm at ES against manual analysis. In conclusion, an automatic method for MV segmentation is proposed which could provide valuable clinical information in a more patient-friendly manner.

Abstract
Left ventricular myocardial stiffness could offer superior quantification of cardiac systolic and diastolic function when compared to the current diagnostic tools. Shear wave elastography in combination with acoustic radiation force has been widely proposed to noninvasively assess tissue stiffness. Interestingly, shear waves can also result from intrinsic cardiac mechanical events (e.g., closure of valves) without the need for external excitation. However, it remains unknown whether these natural shear waves always occur, how reproducible they can be detected and what the normal range of shear wave propagation speed is. The present study, therefore, aimed at establishing the feasibility of detecting shear waves created after mitral valve closure (MVC) and aortic valve closure (AVC), the variability of the measurements, and at reporting the normal values of propagation velocity. Hereto, a group of 30 healthy volunteers was scanned with high-frame rate imaging (>1000 Hz) using an experimental ultrasound system transmitting a diverging wave sequence. Tissue Doppler velocity and acceleration were used to create septal color M-modes, on which the shear waves were tracked and their velocities measured. Overall, the methodology was capable of detecting the transient vibrations that spread throughout the intraventricular septum in response to the closure of the cardiac valves in 92% of the recordings. Reference velocities of 3.2±0.6 m/s at MVC and 3.5±0.6 m/s at AVC were obtained. Moreover, in order to show the diagnostic potential of this approach, two patients (one with cardiac amyloidosis and one undergoing a dobutamine stress echocardiography) were scanned with the same protocol and showed markedly higher propagation speeds: the former presented velocities of 6.6 and 5.6 m/s; the latter revealed normal propagation velocities at baseline, and largely increased during the dobutamine infusion (>15 m/s). Both cases showed values consistent with the expected changes in stiffness and cardiac loading conditions. © 1986-2012 IEEE.