BRIC K01 Awards
Volume-based Analysis of 6-month Infant Brain MRI for Autism Biomarker Identification and Early Diagnosis.
Dr. Li Wang
Autism spectrum disorder (ASD) is a complex developmental disability, characterized by deficits in social interaction, language skills, repetitive stereotyped behaviors, and restricted interests. Based on a recent government survey in 2015, it shows 1 in 45 children (ages 3 to 17) are diagnosed with ASD. Volume-based analysis of neuroimaging data is playing an increasingly critical role in adult autism studies, and has revealed widespread structural and functional abnormalities. However, existing volume-based analysis tools developed for adult brains are ill-suited for infant studies, due to great challenges in brain tissue segmentation and ROI labeling, caused by the extremely low tissue contrast. To become an independent investigator on infant neuroimaging research, the candidate proposes in this K01 application to receive training in clinical phenomenology and child developmental cognitive neuroscience of children with ASD, developmental neurobiology and neurodevelopmental disorders, and biostatistics. These training activities will greatly augment the candidate’s background in ASD, infant neuroimaging mapping and establish a solid foundation for his long-term goal of being a leading researcher on developing imaging-based early biological markers for autism. In the research plan, the candidate will create a unique suite of infant-specific, volume-based neuroimaging analysis tools that enable accurate characterization of early brain development in autistic infants, as well as improved capabilities in early identification of biomarkers and early diagnosis of at-risk infants.
Longitudinal Analysis for Early Diagnosis of Alzheimer’s Disease
Dr. Guorong Wu
This proposal aims for the development of novel neuroimaging analysis methods for early diagnosis of Alzheimer’s disease using longitudinal image data. In particular, a set of automated algorithms will be created to aid the difficult task of analyzing subtle and complex morphological change patterns of Alzheimer’s disease during the disease progression. The successful completion of this project will represent an import milestone in neuroimaging research by bringing forth the fruition of a powerful and practical system for early diagnosis of Alzheimer’s disease at individual level, for potential effective treatment.