Can 3D photography at birth help to detect features of FASD?
Research type
Research Study
Full title
Comparing 2D and 3D photography with computerised analysis for earlier detection of craniofacial changes of fetal alcohol spectrum disorder in newborn infants with and without prenatal alcohol exposure
IRAS ID
241498
Contact name
Neil Aiton
Contact email
Sponsor organisation
Brighton & Sussex University Hospitals NHS Trust
Duration of Study in the UK
1 years, 2 months, 9 days
Research summary
Alcohol consumption in pregnancy can cause fetal alcohol syndrome. In this condition there are 3 principle diagnostic criteria: 1)subtle changes to the face (size of the eyes, smooth philtrum and thin top lip), 2)impaired growth, and 3) a neurological problem, which can be either a structural brain malformation or a subsequent problem with development and behaviour. Fetal alcohol syndrome lies at the severest end of a whole spectrum of disorders caused by prenatal alcohol consumption. Studies have suggested that between 2-5% of children in the UK might be affected. Although there is no cure, children do much better when earlier appropriate help and support are provided. Early diagnosis is therefore important.
In a previous feasibility study (2011-2013) we recruited 92 babies on the postnatal ward. Mothers completed an anonymous alcohol questionnaire to record their alcohol consumption before and during their pregnancy. We performed computerised 2D facial analysis, and showed that this could be achieved in newborn babies.
In this study we are using the same method to recruit babies from the postnatal ward over a 2 year period, and again asking mothers to complete an anonymous alcohol questionnaire. We will record size and birthweight, take 2D and 3D facial photographs. These observations will be stored anonymously and linked to the questionnaire by a unique reference number.
We will also recruit babies who have been exposed to significant levels of alcohol consumption from the specialist One Stop Clinic.
These images will be analysed at the Big Data institute at Oxford and contribute to the 3D modelling of facial features extending from fetal life into childhood, with the aim of developing automated screening and mobile device use.REC name
South Central - Berkshire Research Ethics Committee
REC reference
18/SC/0211
Date of REC Opinion
1 May 2018
REC opinion
Favourable Opinion