Effect of vessel size on the flow efficiency of the total cavopulmonary connection: in vitro studies.

The total cavopulmonary connection (TCPC) creates a passive system of blood flow into the pulmonary circulation. We hypothesize that the efficiency differences found in models with superior vena cava-inferior vena cava (SVC-IVC) offsets is dependent on vessel size, with flow efficiency improving with larger size vessels. Two sets of in vitro TCPC models (TCPC-3 and TCPC-15) were constructed corresponding to average vessel diameters of 3- and 15-year-old patients. The model with full SVC-IVC offset was the most efficient in TCPC-3 models. There was no significant difference between geometric arrangements in TCPC-15 models; however, the average efficiencies were significantly higher. Among the models representing vessel sizes of the younger age group, the model with the full-diameter SVC-IVC offset was the most efficient. The models representing vessel sizes of the older age group showed marked improvement in efficiencies throughout without obvious differences between various geometric arrangements. This suggests that geometric considerations in TCPC surgical techniques may be of lower than expected significance over the life span of a patient. More important, after balancing the effects of improved flow efficiency with larger vessels against the effects of chronic volume overload, the trend of performing the Fontan surgery on increasingly younger patients may need to be reconsidered after further studies.

Artificial neural network-based method of screening heart murmurs in children.

BACKGROUND: Early recognition of heart disease is an important goal in pediatrics. Efforts in developing an inexpensive screening device that can assist in the differentiation between innocent and pathological heart murmurs have met with limited success. Artificial neural networks (ANNs) are valuable tools used in complex pattern recognition and classification tasks. The aim of the present study was to train an ANN to distinguish between innocent and pathological murmurs effectively. METHODS AND RESULTS: Using an electronic stethoscope, heart sounds were recorded from 69 patients (37 pathological and 32 innocent murmurs). Sound samples were processed using digital signal analysis and fed into a custom ANN. With optimal settings, sensitivities and specificities of 100% were obtained on the data collected with the ANN classification system developed. For future unknowns, our results suggest the generalization would improve with better representation of all classes in the training data. CONCLUSION: We demonstrated that ANNs show significant potential in their use as an accurate diagnostic tool for the classification of heart sound data into innocent and pathological classes. This technology offers great promise for the development of a device for high-volume screening of children for heart disease.