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Abstract #1354

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

Tianyi Qian1, Yinyan Wang2,3, Kun Zhou4, Yuanyuan Kang4, Shaowu Li2,5, and Tao Jiang2,5

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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