Article

Congenital heart disease and brain development

Department of Pediatrics, University of California, San Francisco, California, USA.
Annals of the New York Academy of Sciences (Impact Factor: 4.31). 01/2010; 1184:68-86. DOI: 10.1111/j.1749-6632.2009.05116.x
Source: PubMed

ABSTRACT Brain and heart development occur simultaneously in the human fetus. Given the depth and complexity of these shared morphogenetic programs, it is perhaps not surprising that disruption of organogenesis in one organ will impact the development of the other. Newborns with congenital heart disease show a high frequency of acquired focal brain injury on sensitive magnetic resonance imaging studies in the perioperative period. The surprisingly high incidence of white matter injury in these term newborns suggests a unique vulnerability and may be related to a delay in brain development. These abnormalities in brain development identified with MRI in newborns with congenital heart disease might reflect abnormalities in cerebral blood flow while in utero. A complete understanding of the mechanisms of white matter injury in the term newborn with congenital heart disease will require further investigation of the timing, extent, and causes of delayed fetal brain development in the presence of congenital heart disease.

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    • "The condition involves the death of small areas of the brain tissue around fluidfilled areas called ventricles. Research has shown a high incidence of PVL both before and after cardiac surgery in neonates [5], [6]. Recently, there has been a growing interest in clinical research to aim to understand the progression and pathology of PVL, to develop protocols for the prevention of PVL development and to examine the trends in outcomes of individuals with PVL [7]. "
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    ABSTRACT: This paper is concerned with predicting the occurrence of Periventricular Leukomalacia (PVL) using vital data which are collected over a period of twelve hours after neonatal cardiac surgery. The vital data contain heart rate (HR), mean arterial pressure (MAP), right atrium pressure (RAP), and oxygen saturation (SpO2). Various features are extracted from the data and are then ranked so that an optimal subset of features that have the highest discriminative capabilities can be selected. A decision tree (DT) is then developed for the vital data in order to identify the most important vital measurements. The DT result shows that high amplitude 20 minutes variations and low sample entropy in the data is an important factor for prediction of PVL. Low sample entropy represents lack of variability in hemodynamic measurement, and constant blood pressure with small fluctuations is an important indicator of PVL occurrence. Finally, using the different time frames of the collected data, we show that the first six hours of data contain sufficient information for PVL occurrence prediction.
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    • "Generally motor control problems or other neuro-developmental problems including cerebral palsy or epilepsy are common in PVL patients [2], [3]. Recent research has shown that PVL is very common in neonates before and after cardiac surgery [4]–[6], and hence there is a growing interest among clinical researchers to attempt to understand the physiology and pathology of PVL, develop clinical protocols for the prediction and prevention of PVL and also to predict the outcomes of individual patients suffering from PVL [7], [8]. "
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    ABSTRACT: This paper is concerned with the prediction of the occurrence of periventricular leukomalacia (PVL) that occurs in neonates after heart surgery. The data which is collected over a period of 12 hours after cardiac surgery contains vital measurements as well as blood gas measurements with different resolutions. Vital data measured using near-inferred spectroscopy (NIRS) at the sampling rate of 0.25 Hz and blood gas measurement up to 12 times with irregular time intervals for 35 patients collected at Children's Hospital of Philadelphia (CHOP) are used for this study. Features derived from the data include statistical moments (mean, variance, skewness and kurtosis), trend and minimum and maximum values of the vital data and rate of change, time weighted mean and a custom defined out of range index (ORI) for the blood gas data. A decision tree is developed for the vital data in order to identify the most important vital measurements. In addition, a decision tree is developed for blood gas data to find important factors for the prediction of PVL occurrence. Results show that in the blood gas data, maximum rate of change of concentration of bicarbonate ions in blood (HCO(3)) and minimum rate of change of partial pressure of dissolved CO(2) in the blood (PaCO(2)) are the two most important factors for prediction of the PVL. Also important are the kurtosis of heart rate and hemoglobin values.
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    ABSTRACT: Acute brain injury is rarely seen, but salient features include acute hemorrhage, thrombosis, and localized or general edema. Findings are rarely specific with regard to etiology. In addition to maternal disease, risk factors for acquired brain lesions include disorders of the placenta and/or umbilical cord, exposure to toxic agents, metabolic disease, iatrogenic hazards, fetal cardiovascular disease, and space-occupying lesions. Most often, defective stages are found, characterized by local or diffuse tissue loss, and/or hemorrhagic residuals, and/or calcification. In order to describe an acquired lesion most accurately, in addition to T2-weighted sequences, T1-weighted, diffusion-weighted, and echoplanar (or T2*) information is necessary. In case of suspected infection, the whole fetus and the extrafetal structures must be screened for pathological changes.
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