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Abstract #5351

Features extracted from diffusion-driven tensor based morphometry can serve as a specific imaging marker for Moebius Syndrome

Neda Sadeghi1, Irini Manoli2, Timothy Wood3, Francis S. Collins2, Ethylin Wang Jabs4, Elizabeth C. Engle5, Moebius Syndrome Research Consortium6, and Carlo Pierpaoli1

1Quantitative Medical Imaging Section, National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health, Bethesda, MD, United States, 2Medical Genomics and Metabolic Genetics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, United States, 3Department of Computer Science, University of Maryland: College Park, College Park, MD, United States, 4Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, United States, 5Departments of Neurology and Ophthalmology, Boston Children's Hospital and Harvard Medical School, Boston, MA, United States, 6National Institutes of Health, Bethesda, MD, United States

Quantitative diffusion derived metrics such as fractional anisotropy (FA), and Trace of diffusion tensor (TR) have been used in many studies to assess differences between a subject group and a control group. In this study, in addition to FA and TR, we also look at morphological differences measured by diffusion-driven tensor based morphometry (DTBM). We use DTBM to extract features for use in classification of Moebius syndrome subjects, a rare birth defect characterized by paralysis or weakness of facial muscles and impairment of ocular abduction.

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