Abstract #0703

An Improved Probabilistic Atlas of the Dentate Nucleus Derived with QSM

Naying He^1,2, Jason Langley³, Daniel E Huddleston⁴, Huawei Ling⁵, Hongmin Xu⁵, Chunlei Liu⁶, Yong Zhang⁷, Fuhua Yan⁸, and Xiaoping Hu^9,10

¹Radiology, Ruijin Hospital,Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China, ²Center for Advanced Neuroimaging, University of California, Riverside, Riverside, CA, United States, ³Center for Advanced NeuroImaging, University of California Riverside, Riverside, CA, United States, ⁴the department of Neurology, Emory School of Medicine, Atlanta, GA, United States, ⁵Radiology, Ruijin Hospital,Shanghai Jiao Tong University School of Medicine, ⁶Electrical Engineering and Computer Sciences, University of California, Berkeley, CA, United States, ⁷MR Research, GE Healthcare, Shanghai, People's Republic of China, ⁸Radiology, Ruijin Hospital,Shanghai Jiao Tong University School of Medicine, shanghai, People's Republic of China, ⁹Center for Advanced Neuroimaging, University of California, Riverside, CA, United States, ¹⁰Bioengineering, University of California, Riverside, Riverside, CA, United States

Prior dentate nucleus (DN) atlases were derived using T_1-, T₂*- or susceptibility-weighted imaging. Accurate delineation of the DN boundary is difficult in these images. We present an atlas derived from quantitative susceptibility maps, which exhibit better contrast between DN and surrounding cerebellum tissue. An improved delineation of DN boundaries was achieved, resulting in increased maximum overlap in our DN atlas as compared to previously published results. We anticipate the atlas to be used in a variety of imaging applications ranging from functional imaging of DN to measuring DN iron deposition arising from disease.

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