Armen Kocharian

A novel method for pediatric heart sound segmentation without using the ECG

In this paper, we propose a novel method for pediatric heart sounds segmentation by paying special attention to the physiological effects of respiration on pediatric heart sounds. The segmentation is accomplished in three steps. First, the envelope of a heart sounds signal is obtained with emphasis on the first heart sound (S(1)) and the second heart sound (S(2)) by using short time spectral energy and autoregressive (AR) parameters of the signal. Then, the basic heart sounds are extracted taking into account the repetitive and spectral characteristics of S(1) and S(2) sounds by using a Multi-Layer Perceptron (MLP) neural network classifier. In the final step, by considering the diastolic and systolic intervals variations due to the effect of a childs respiration, a complete and precise heart sounds end-pointing and segmentation is achieved.

Computerized screening of children congenital heart diseases

In this paper, we propose a method for automated screening of congenital heart diseases in children through heart sound analysis techniques. Our method relies on categorizing the pathological murmurs based on the heart sections initiating them. We show that these pathelogical murmur categories can be identified by examining the heart sound energy over specific frequency bands, which we call, Arash-Bands. To specify the Arash-Band for a category, we evaluate the energy of the heart sound over all possible frequency bands. The Arash-Band is the frequency band that provides the lowest error in clustering the instances of that category against the normal ones. The energy content of the Arash-Bands for different categories constitue a feature vector that is suitable for classification using a neural network. In order to train, and to evaluate the performance of the proposed method, we use a training data-bank, as well as a test data-bank, collectively consisting of ninety samples (normal and abnormal). Our results show that in more than 94% of cases, our method correctly identifies children with congenital heart diseases. This percentage improves to 100%, when we use the Jack-Knife validation method over all the 90 samples.

Coenzyme Q10 improves diastolic function in children with idiopathic dilated cardiomyopathy

We aimed to determine the effect of supplementation with coenzyme Q10 on conventional therapy of children with cardiac failure due to idiopathic dilated cardiomyopathy. In a prospective, randomized, double-blinded, placebo-controlled trial, we randomized 38 patients younger than 18 years with idiopathic dilated cardiomyopathy to receive either coenzyme Q10, chosen for 17 patients, or placebo, administered in the remaining 21. Echocardiographic systolic and diastolic function parameters were determined for every patient at baseline, and after 6 months of supplementation. The index score for cardiac failure in children as established in New York was used for assessing the functional class of the patients. After 6 months supplementation, 10 patients randomized to receive coenzyme Q10 showed improvements in the grading of diastolic function, this being significantly more than that achieved by those randomized to the placebo group (p value = 0.011). The mean score for the index of cardiac failure index for those receiving coenzyme Q10 was also lower than the control group (p value = 0.024).Our results, therefore, indicate that administration of coenzyme Q10 is useful in ameliorating cardiac failure in patients with idiopathic dilated cardiomyopathy through its significant effect on improving diastolic function.

Endocardial boundary extraction in left ventricular echocardiographic images using fast and adaptive B-spline snake algorithm

PurposeA fast and robust algorithm was developed for automatic segmentation of the left ventricular endocardial boundary in echocardiographic images. The method was applied to calculate left ventricular volume and ejection fraction estimation.MethodsA fast adaptive B-spline snake algorithm that resolves the computational concerns of conventional active contours and avoids computationally expensive optimizations was developed. A combination of external forces, adaptive node insertion, and multiresolution strategy was incorporated in the proposed algorithm. Boundary extraction with area and volume estimation in left ventricular echocardiographic images was implemented using the B-spline snake algorithm. The method was implemented in MATLAB and 50 medical images were used to evaluate the algorithm performance. Experimental validation was done using a database of echocardiographic images that had been manually evaluated by experts.ResultsComparison of methods demonstrates significant improvement over conventional algorithms using the adaptive B-spline technique. Moreover, our method reached a reasonable agreement with the results obtained manually by experts. The accuracy of boundary detection was calculated with Dice’s coefficient equation (91.13%), and the average computational time was 1.24 s in a PC implementation.ConclusionIn sum, the proposed method achieves satisfactory results with low computational complexity. This algorithm provides a robust and feasible technique for echocardiographic image segmentation. Suggestions for future improvements of the method are provided.

N-terminal pro-B-type natriuretic peptide and ventricular dysfunction in children and adolescents.

Our aim was further to clarify the diagnostic usefulness of N-terminal pro-B-type natriuretic peptide for detecting ventricular dysfunction in children, and its correlation with myocardial performance index and New York University Pediatric Heart Failure Index score. We also hypothesized that the level of this natriuretic peptide in the serum could predict the severity of diastolic abnormalities in children with cardiac failure. We enrolled 99 patients, aged from 3 months to 16 years, who had been referred for echocardiography to evaluate ventricular function. Echocardiographic evidence of left ventricular systolic and diastolic dysfunction was found in 20 and 42 patients, respectively. We classified these patients as having impaired relaxation, seen in 12 patients, pseudonormal patterns seen in 19 patients, and restrictive-like patterns of filling seen in 11 patients. The mean of the log-transformed values for N-terminal pro-B-type natriuretic peptide increased significantly according to the severity of diastolic dysfunction (p = 0.003, p = 0.022, p < 0.0001). A value of 178 pg/ml had a sensitivity of 88% and specificity of 81% for detecting abnormal diastolic function (p < 0.0001). Furthermore, the log-transformed values correlated with myocardial performance index (p < 0.0001) in a positive manner, and the levels increased significantly according to New York University Pediatric Heart Failure Index score, showing a linear correlation with a robust r value for regression (r = 0.89, p < 0.0001). Our findings suggest that higher levels of the peptide, having a good correlation with New York University Pediatric Heart Failure Index score and myocardial performance index, might be a suitable marker to rule out ventricular diastolic dysfunction in children.

Left atrial ejection force in healthy newborn infants.

BACKGROUND Atrial ejection force (AEF) expresses the force exerted by the left atrium to the mass of blood passing through the mitral valve during atrial systole. It provides a diagnostic and predictive parameter for evaluating left ventricular diastolic abnormalities and a physiologic assessment of atrial systolic function. METHODS We obtained normal values of AEF in a group of 47 newborn infants with normal heart function and structure, using Doppler echocardiographic parameters of transmitral filling flow. AEF is defined as the product of the density of blood, the mitral valve area, and the square of peak A velocity [AEF = 0.5 x rho x mitral valve area x (peak A velocity)(2)]. RESULTS Mean and SD of AEF was 1.12 +/- 0.42 kilodynes. Atrial filling fraction (r = 0.74, P value = .000), A acceleration rate (r = 0.67, P value = .000), A deceleration rate (r = 0.64, P value = .000), and heart rate (r = 0.70, P value = .000) showed a positive correlation with AEF. Rapid filling fraction (r = -0.71, P value = .000) and E/A ratio (r = -0.6, P value = .000) had a negative correlation with AEF. CONCLUSION AEF index in neonatal period is augmented and comparable with the values in adult population that could be explained by the specific pattern of slow ventricular relaxation in newborn infants. Complex aspects of diastolic function in newborn infants could be assessed beyond a simple E to A ratio by providing an estimate of normal values for AEF in this age group.

An Intelligent Method for Discrimination between Aortic and Pulmonary Stenosis using Phonocardiogram

This study presents an artificial intelligent-based method for processing phonocardiographic (PCG) signal of the patients with ejection murmur to assess the underlying pathology initiating the murmur. The method is based on our unique method for finding disease-related frequency bands in conjunc-tion with a sophisticated statistical classifier. Children with aortic stenosis (AS), and pulmonary stenosis (PS) were the two patient groups subjected to the study, taking the healthy ones (no mur-mur) as the control group. PCG signals were acquired from 45 referrals to the children University hospital, comprised of 15 individuals of each group; all were diagnosed by the expert pedi-atric cardiologists according to the echocardiographic measure-ments together with the complementary tests. The accuracy of the method is evaluated to be 90% and 93.3% using the 5-fold and leave-one-out validation method, respectively. The accuracy is slightly degraded to 86.7% and 93.3% when a Gaussian noise with signal to noise ratio of 20 dB is added to the PCG signals, exhibiting an acceptable immunity against the noise. The method offered promising results to be used as a decision support system in the primary healthcare centers or clinics.

A Novel Method for Screening Children with Isolated Bicuspid Aortic Valve

This paper presents a novel processing method for heart sound signal: the statistical time growing neural network (STGNN). The STGNN performs a robust classification by merging supervised and unsupervised statistical methods to overcome non-stationary behavior of the signal. By combining available preprocessing and segmentation techniques and the STGNN classifier, we build an automatic tool for screening children with isolated BAV, the congenital heart malformation which can lead to serious cardiovascular lesions. Children with BAV (22 individuals) and healthy condition (28 individuals) are subjected to the study. The performance of the STGNN is compared to that of a time growing neural network (CTGNN) and a conventional support vector (CSVM) machine, using balanced repeated random sub sampling. The average of the accuracy/sensitivity is estimated to be 87.4/86.5 for the STGNN, 81.8/83.4 for the CTGNN, and 72.9/66.8 for the CSVM. Results show that the STGNN offers better performance and provides more immunity to the background noise as compared to the CTGNN and CSVM. The method is implementable in a computer system to be employed in primary healthcare centers to improve the screening accuracy.

Fast and automatic LV mass calculation from echocardiographic images via B-spline snake model and markov random fields

Left ventricular (LV) mass has several important diagnostic and indicative implications. In this paper, a fast and accurate technique for detection of inner and outer boundaries of LV and, consequently, calculation of LV mass from apical 4-chamber echocardiographic images is presented. For detection of the inner boundary, a modified B-spline snake is proposed, which relies merely on image intensity and obviates the need for computationally-demanding image forces. The outer boundary is then obtained using a Markov random fields model in the neighborhood of the estimated inner border. Experimental validation of the proposed technique demonstrates remarkable improvement over conventional algorithms.

The Impact of Preload Alteration on the Myocardial Performance Index through Implementing Positive End Expiratory Pressure

Load independent methods should be used for the assessment of ventricular function. Debate still exists regarding whether tissue Doppler imaging (TDI) indices are influenced by preload. Here, we evaluated the effect of positive end expiratory pressure (PEEP) related preload reduction on both conventional pulsed Doppler (PD) and TDI myocardial performance index (MPI). Thirty‐eight mechanically ventilated patients of 3 months to 12 years old (mean ± SD age of 30 ± 11months) without overt heart disease were enrolled. Doppler mitral inflow velocities, isovolumetric contraction and relaxation times and aortic ejection time in addition to TDI peak systolic, early and late diastolic velocities from the basal segment of left ventricular lateral wall were determined for each patient before and after applying high PEEP (10 cmH2O).PD‐MPI was load dependent (0.61 ± 0.22 vs. 0.78 ± 0.25, P = 0.002). However, TDI‐MPI did not significantly change after the use of high PEEP declining the left ventricular volume loading (0.78 ± 0.21 vs. 0.84 ± 0.22, P = 0.23). Hence, regarding various interfering pathophysiologic factors particularly preload reduction, it seems that TDI‐MPI would be a more reliable index for the assessment of ventricular function.