It has been demonstrated that anthropometric data can accurately distinguish individuals with Fetal alcohol syndrome (FAS) from those who were alcohol exposed but do not manifest the full spectrum of clinical features, and those who were not alcohol exposed [2]. A more efficient means to collect such data may be through three-dimensional (3-D) digitizing instruments, which can capture a facial image that can then be used to collect a wide range of known and novel clinical variables. Through the collection of 3-D images from individuals of variable ethnicity, age and exposure histories, it should be possible to identify a series of variables that effectively discriminate individuals who were prenatally exposed to alcohol and the degree to which they were exposed, from those who were not exposed. The goal of this collaboration is to analyze three-dimensional (3-D) facial images from individuals of variable ethnicity, age and history of alcohol exposure. The analyses of 3-D facial imaging will be developed and utilized for more effective clinical diagnosis of FAS, as well as the more broadly defined FASD. In addition, we believe these studies will generate important insight regarding the changes that occur in the face both prenatally and postnatally that produce the clinical features associated with FAS and thereby provide improved understanding of the pathophysiological effects of ethanol on human development. To accomplish these goals we propose the following specific aims: 1) Train and supervise personnel at each recruitment site to ensure collection of standardized data; 2) Analyze the 3-D facial imaging data to identify the measurements that most efficiently differentiate alcohol exposed from control subjects; 3) Utilize algorithms and methods derived from the emerging field of Automated Facial Recognition (AFR) to extract and identify the most discriminating higher order surface features from 3-D facial images, with the goal of developing an automated method of identifying facial features diagnostic of prenatal alcohol exposure; and 4) Combine the results from the direct and higher order measurements derived from the 3-D facial imaging with variables collected from other study domains to improve the power to accurately discriminate alcohol exposed from control subjects and to better understand the pathophysiological effects of ethanol on human development.
| McCarthy, Neil; Wetherill, Leah; Lovely, C Ben et al. (2013) Pdgfra protects against ethanol-induced craniofacial defects in a zebrafish model of FASD. Development 140:3254-65 |
| Klingenberg, C P; Wetherill, L; Rogers, J et al. (2010) Prenatal alcohol exposure alters the patterns of facial asymmetry. Alcohol 44:649-57 |
| Mattson, Sarah N; Foroud, Tatiana; Sowell, Elizabeth R et al. (2010) Collaborative initiative on fetal alcohol spectrum disorders: methodology of clinical projects. Alcohol 44:635-41 |
| Fang, S; McLaughlin, J; Fang, J et al. (2008) Automated diagnosis of fetal alcohol syndrome using 3D facial image analysis. Orthod Craniofac Res 11:162-71 |
| Moore, Elizabeth S; Ward, Richard E; Wetherill, Leah Flury et al. (2007) Unique facial features distinguish fetal alcohol syndrome patients and controls in diverse ethnic populations. Alcohol Clin Exp Res 31:1707-13 |
