Data-driven Medicine

For 15 years, IU has worked to improve recognition of prenatal alcohol exposure, one of the leading but preventable causes of birth defects and learning disabilities, by examining facial features. Identifying children with prenatal alcohol exposure can help them get the intervention and support that they need to thrive.

UITS’s Advanced Visualization Lab (AVL) was a key partner with the Collaborative Initiative for Fetal Alcohol Spectrum Disorders (CIFASD). The work was led by IU School of Medicine Distinguished Professor Tatiana Foroud, principal investigator of CIFASD’s 3-D facial imaging core, and IU faculty member Leah Wetherill, who assisted with the analytics and statistics of the study. UITS staff member Jeff Rogers helped with the project by working on 3-D capture support, data processing, distribution, and custom program development.

For the study, Foroud’s team used a 3-D camera to capture images of children with prenatal alcohol exposure, to better recognize facial features that a traditional camera could not capture. By analyzing scans from more than 5,000 people around the world, they have concluded that facial curvature is correlated with brain volume, as well as cognitive defects and learning disabilities.

“I believe that providing the data from the 3-D imaging study to other researchers will help to improve our ability to recognize prenatal alcohol exposure. This will create a lasting impact on individuals and their families world-wide,” Faroud said.

FASD research by the numbers

5,000+3-D facial images captured

11locations where UITS supported onsite 3-D capture or training followed by remote support and documentation

5different 3-D file formats supported by UITS for use by researchers to answer their questions