Background

Early detection of fetal alcohol spectrum disorders (FASDs) is desirable to allow earlier and more comprehensive interventions to be initiated for the mother and infant. We examined prenatal ultrasound as an early method of detecting markers of the physical features and neurobehavioral deficits characteristic of FASD.

Methods

A longitudinal cohort of pregnant women in Ukraine was recruited as part of the Collaborative Initiative on Fetal Alcohol Spectrum Disorders. Women were enrolled into a moderately to heavy-alcohol-exposed group or a low- or no-alcohol exposure group and were followed to pregnancy outcome. In the second trimester, a fetal ultrasound was performed to measure transverse cerebellar diameter, occipital frontal diameter (OFD), caval-calvarial distance, frontothalamic distance (FTD), interorbital distance (IOD), outer orbital diameter, and orbital diameter (OD). Live born infants received a dysmorphological examination and a neurobehavioral evaluation using the Bayley Scales of Infant Development. These data were used to classify infants with respect to FASD. Comparisons were made on the ultrasound measures between those with and without features of FASD, adjusting for gestational age at ultrasound and maternal smoking.

Results

A total of 233 mother/child dyads were included. Children classified as FASD had significantly longer IOD and lower FTD/IOD, OFD/IOD, and FTD/OD ratios (p < 0.05). Children with a Bayley score <85 had significantly shorter FTD, longer IOD, lower OFD/IOD, and FTD/IOD ratios (p < 0.05). In general, mean differences were small. Ultrasound variables alone predicted <10% of the variance in the FASD outcome.

Conclusions

Some ultrasound measurements were associated with FASD, selected facial features of the disorder, and lower neurobehavioral scores. However, mean differences were relatively small, making it difficult to predict affected children based solely on these measures. It may be advantageous to combine these easily obtained ultrasound measures with other data to aid in identifying high risk for an FASD outcome.