3-D Image Analysis Promises to Improve Detection of Children Affected by Prenatal Alcohol
Computerized image analysis can be a useful tool for detecting the sometimes subtle changes in facial features that occur when children are exposed to alcohol before birth, according to a recent study conducted through the NIAAA-funded Collaborative Initiative on Fetal Alcohol Spectrum Disorders (CIFASD). As reported in the journal Pediatrics, the study suggests that three-dimensional (3-D) imaging could soon help clinicians identify children at high risk for cognitive impairments due to prenatal alcohol exposure.
“This important work could help pediatricians and clinicians make earlier identification of children at high risk for cognitive deficits due to prenatal alcohol exposure, especially those heavily exposed individuals who lack the classic facial characteristics of fetal alcohol syndrome (FAS),” said NIAAA acting director Kenneth R. Warren, Ph.D.
Prenatal alcohol exposure causes a continuum of effects. FAS is the most serious consequence of heavy drinking during pregnancy and involves a specific pattern of facial abnormalities, including small eye width, smoothing of the ridges between the base of the nose and the upper lip, and a thin upper lip border, as well as growth deficits, and neurocognitive problems.
Collaborating with other CIFASD investigators and additional researchers in South Africa, lead investigator Peter Hammond, Ph.D., of the University College London identified novel strategies for detecting facial effects of prenatal alcohol exposure among a sample of children from a community clinic in Cape Town, South Africa, where the incidence of heavy alcohol use during pregnancy and FAS are among the highest in the world.
Using three-dimensional photography and computerized image analysis techniques, the researchers examined facial characteristics of children either not exposed or heavily exposed to alcohol and compared their observations with clinically-determined FASD categorizations. They found that 3-D facial image analyses substantially enhanced the ability to detect a broad range of alcohol-induced facial changes in children. Importantly, their computer-based approach should help identify affected children who have cognitive impairments but lack facial features necessary for a FAS diagnosis. They note that more substantial testing of these techniques is planned in South Africa, the United States, and the Ukraine. For more information on the CIFASD consortium, visit http://www.cifasd.org.