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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