Abstract #1354

Tumor Classification Using Blood Arrival Histogram Obtained by Resting-state fMRI

Tianyi Qian¹, Yinyan Wang^2,3, Kun Zhou⁴, Yuanyuan Kang⁴, Shaowu Li^2,5, and Tao Jiang^2,5

¹MR Collaborations NE Asia, Siemens Healthcare, Beijing, China, People's Republic of, ²Neurosurgery, Tiantan Hospital, beijing, China, People's Republic of, ³Beijing Neurosurgical Institute, Capital Medical University, Beijing, China, People's Republic of, ⁴Siemens Shenzhen Magnetic Resonance Ltd., APPL, Shenzhen, China, People's Republic of, ⁵Beijing Neurosurgical Institute, Capital Medical University, beijing, China, People's Republic of

In this study, a new post-processing pipeline of resting-statefMRI (rs-fMRI)was proposed for glioma grading, with the feasibility of extracting the timing information of brain perfusion from BOLD signal. The blood arrival time obtained from rs-fMRI shows unevenly distributed perfusion patterns in tumors. A histogram-based analysis method was employed to analyze the non-uniform distribution that could extract the patterns better than the routine method. The proposed pipeline was able to classify between low- and high-grade gliomas.

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