This presentation will cover three separate diffusion-weighted MRI projects that each aim to advance methods for mapping neuronal fibers. First, I will present a practical, model-free, Fourier reconstruction framework for obtaining Diffusion Spectrum Imaging-style probability density and orientation distribution functions from multi-b-shell/non-Cartesian q-space samples. This technique employs q-space sampling density non-uniformity correction and analytic solver. It is demonstrated on data from the Human Connectome Project and shown to be effective and broadly applicable to multi-b-shell data. Using this method, the contribution and combination of information from individual q-space points is elucidated. Second, I will discuss methods for comparing diffusion-weighted MRI measurements with CLARITY 3D histology. Structure tensor texture analysis is adapted from 2D to 3D to recover local primary axon orientations from 3D CLARITY images. The CLARITY axon orientation estimates are compared against diffusion tensor imaging in the same human specimen, and used to perform CLARITY-based tractography in a mouse brain. Finally, I will present a retrospective study that assesses the efficacy of diffusion tractography-based targeting for transcranial MRI-guided focused ultrasound treatment of essential tremor. For 8 patients, the degree of overlap between the tractography-identified target and the focused ultrasound-induced lesion location is found to correlate with clinical outcome.
About the Speaker
Qiyuan Tian is a Ph.D. candidate of the Department of Electrical Engineering and a graduate student research assistant in the research group of Professor Jennifer McNab in the Radiological Sciences Laboratory of the Department of Radiology at Stanford University. He obtained his M.S. in Electrical Engineering from Stanford University in 2013 and the B.Eng. in Communication Science and Engineering from Fudan University in Shanghai, China in 2011. He also studied as an undergraduate exchange student in the Department of Electronic and Computer Engineering at The Hong Kong University of Science and Technology in 2009. Qiyuan’s research lies at developing novel diffusion MRI and neuroimaging acquisition and analysis methods to study the human brain.