Abstract #5113

Exploring Brain Microstructure with Ultra-high b-values Diffusion MRI: A NODDI Model Comparison

Paween Wongkornchaovalit^1,2, Junye Yao^1,2, Bo Dong^1,2, Jianhui Zhong³, Hui Zhang⁴, and Hongjian He^1,5,6

¹Center for Brain Imaging Science and Technology, Zhejiang University, Hangzhou, China, ²College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China, ³Department of Imaging Sciences, University of Rochester, Rochester, NY, United States, ⁴Department of Computer Science & Centre for Medical Image Computing, University College London, London, United Kingdom, ⁵School of Physics, Zhejiang University, Hangzhou, China, ⁶State Key Laboratory of Brain-Machine Intelligence, Zhejiang University, Hangzhou, China

Synopsis

Keywords: Microstructure, Data Analysis, Ultra-high b-values, NODDI

Motivation: The benefits of using ultra-high b-values diffusion MRI (b>6000s/mm²) on characterizing and resolving brain microstructure are still unclear.

Goal(s): To determine if the NODDI metrics computed from ultra-high b-values can help characterizing and providing more biological information related to brain microstructure.

Approach: NODDI metrics are compared between different b-schemes, and between the corpus callosum and hippocampal subfields.

Results: NODDI metrics computed with ultra-high b-value data can help characterize different subfields. Higher NDI and ODI differences in the corpus callosum and hippocampal subfields are observed with larger b-values.

Impact: We show that NODDI models can work with ultra-high b-values and help characterizing and providing more biological information related to brain microstructure.

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