alexa The assessment of fetal behavior of growth restricted fetuses by 4D sonography.
Bioinformatics & Systems Biology

Bioinformatics & Systems Biology

Journal of Health & Medical Informatics

Author(s): Andonotopo W, Kurjak A

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Abstract AIM: To find out whether the quantity of fetal facial expression and quality of body movements can be used as an additional diagnostic criterion for prenatal brain impairment in fetuses with growth restriction. SUBJECT AND METHODS: A prospective study was conducted in 50 uncomplicated healthy women as control group with reliably dated pregnancies and 50 pregnant women with a growth restricted fetus as study group in the third trimester of pregnancy. 4D ultrasound observation is specially designed to assess whether functional brain impairment and fetal growth restriction had prenatally occurred by the utilization of several behavioral patterns. RESULTS: The median value of all movement patterns in the normal fetuses differed from fetuses with intrauterine growth restriction (IUGR). Statistical evaluation revealed significant differences in the distribution of the movements between these groups (P<0.05). We noted a tendency that IUGR fetuses have less behavioral activity than normal fetuses in all observed movement patterns. Correlation reached statistical significance between normal and IUGR fetuses in the third trimester in hand to head, hand to face and head retroflexion. Statistically significant differences could be shown in the distribution of the median values of observation over the five qualitative categories of head and hand movements (P<0.05). CONCLUSIONS: Recent data on IUGR fetuses obtained by 4D sonography are stimulating and might result in a more effective strategy to assess development before birth. The results of this study may encourage future use of 4D ultrasound for quantitative and qualitative assessment of fetal behavior as possible indicators of the neurological condition in IUGR fetuses. This article was published in J Perinat Med and referenced in Journal of Health & Medical Informatics

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