Fetal alcohol spectrum disorder (FASD) is caused due to teratogenic insults to the brain resulting from the effects of alcohol exposure, in utero, and is estimated to occur in 1% of births. It is an important public health concern as it is completely preventable, yet at the same time is the leading known cause of neurodevelopmental disability. A more extreme form of this disorder is also known as fetal alcohol syndrome, whose key defining characteristics are facial dysmorphology, pre- and post-natal growth deficiency, and central nervous system (CNS) dysfunction. Presently, almost all neuroscientific studies focusing on this disorder have studied the face, and the brain separately. Furthermore, at the lower end of this spectrum disorder, the CNS deficits may be present without the visually observable facial malformations leading to a potential under- diagnosis. The objective of the proposed research is to overcome these limitations by combining the facial dysmorphic features, and the neurostructural abnormalities in a common shape analysis framework. Specifically, this proposal aims at integrating information from different sources such as structural neuroimaging using MRI and DTI, and 3D photographs of the face. The proposed research will i) conduct a joint morphometric analysis for the brain and face by incorporating facial landmarks, and cortical features, ii) derive combined face-brain imaging biomarkers for the purpose of FASD classification, iii) collect new longitudinal data for charting the neurodevelopmental and facial progression and deficits, and finally iv) investigate the structural connectivity mapping of the brain and face using DTI modalities. This work will lead to a better understanding of the intricate morphological relationships between the brain and the face in FASD, and further promote early detection strategies above and beyond what is achieved by the current diagnostic criteria alone. The candidate's formal training will take advantage of the rich morphometric and imaging experience of his mentors, as well as alcohol related research and neuroimaging resources at UCLA and CHLA, and will include eight formal training courses, two intensive workshops and regular weekly seminars designed to augment the candidate's prior image analysis experience with new knowledge in alcohol research, neurodevelopmental, and craniofacial anatomy, helping him to develop the skills for conducting an independent longitudinal FASD project.
This study aims to find quantitative relationships between the anatomy of the brain from MRI, and that of the face from 3D photographs of children affected by fetal alcohol spectrum disorder (FASD) caused due to prenatal alcohol exposure. A critical outcome of this research is expected to reveal diagnostic effects for children who have neurocognitive deficits but for whom the facial dysmorphology is not directly visible, and will have a significant impact for early detection and possible intervention strategies for FASD in the nation as well as all over the world, wherever alcohol is consumed by mothers during pregnancy. Moreover, this research will integrate methods from engineering and neuroscience, and will develop a common scientific approach for analyzing diverse imaging modalities such as MRI images (brain) and 3D laser scans (face).
| Pal, Susovan; Woods, Roger P; Panjiyar, Suchit et al. (2017) A Riemannian Framework for Linear and Quadratic Discriminant Analysis on the Tangent Space of Shapes. Conf Comput Vis Pattern Recognit Workshops 2017:726-734 |
| Lee, David S; Leaver, Amber; Narr, Katherine L et al. (2017) Measuring Brain Connectivity via Shape Analysis of fMRI Time Courses and Spectra. Connectomics Neuroimaging (2017) 10511:125-133 |
