Abstract #3992

Comparison of Different CEST Metrics for Brain Tumor Grading with Semi-Automatic ROIs

Ruibin Liu¹, Xianlong Wang², Zhibo Wen², Tingting Liu¹, Jinyuan Zhou³, Dan Wu^1,3, and Yi Zhang^1,3

¹Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China, ²Department of Radiology, Zhujiang Hospital, Southern Medical University, Guangzhou, China, ³Department of Radiology, Johns Hopkins University, Baltimore, MD, United States

The performance of three CEST metrics including CESTR, CESTR^nr, MTR_Rex at various frequency offsets was evaluated for human brain tumor grading. Regions of interest were created semi-automatically based on an initial radiologist-drawn contour and automatic histogram analysis in order to minimize subjective bias. Thirty-nine patients with 23 confirmed high-grade and 16 confirmed low-grade gliomas were included. CESTR^nr metric at 3 ppm were superior to other frequency offsets for grading human brain gliomas, with the maximum area under the curve value of 0.88.

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