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Abstract #2916

Percentile-based Analysis of Non-Gaussian Diffusion Parameters for Improved Glioma Grading

Christopher Y. Zhou1, Jiaxuan Zhang2,3, Wenzhen Zhu3, Zheng Zhong2,4, and Muge Karaman2,4

1Naperville North High School, Naperville, IL, United States, 2Center for Magnetic Resonance Research, University of Illinois at Chicago, Chicago, IL, United States, 3Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China, 4Department of Bioengineering, University of Illinois at Chicago, Chicago, IL, United States

Diffusion MRI has been used for tumor grading due to its sensitivity to alterations at the tissue microstructural level. Recognizing the limitations of analysis methods based on region-of-interest (ROI) in which the parameter values are averaged over the tumor ROIs, histogram-based approaches have been proposed for differentiating tumor grades. One challenge in this approach is to determine an optimal percentile over the ROI to be used in the analysis. In this study, we systematically and statistically determined an optimal percentile cut-off for calculating the mean parameters obtained from a non-Gaussian diffusion model based on continuous-time random-walk (CTRW) theory for differentiation among glioma grades.

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