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Abstract #0359

Comparison of MUSE and ssEPI for diffusion-weighted imaging in meningioma: imaging quality and grading accuracy

Danjie Lin1, Yichao Zhang2, Sihui Liu1, Jialu Zhang3, Yunjing Xue1, and Lin Lin1
1Department of Radiology, Fujian Medical University Union Hospital, Fuzhou, Fujian, China, 2School of Medical Imaging, Fujian Medical University, Fuzhou, Fujian, China, 3MR Research, GE Healthcare, Beijing, China

Synopsis

Keywords: Tumors (Pre-Treatment), Neuro

Motivation: DWI is of key importance in evaluating biological behavior of meningioma, but image quality of conventional ssEPI-DWI is unsatisfactory due to susceptibility artifact near the skull.

Goal(s): Our goal was to compare the image quality of ssEPI-DWI and MUSE-DWI in meningiomas, and to compare diagnostic accuracy of them in meningiomas grading.

Approach: We used a 5-point Likert scale to assess image quality of DWI, and calculated SNR and CNR for quantitative evaluation. Combined models were constructed by using ADC histogram parameters extracted from whole tumor.

Results: MUSE-DWI significantly improved imaging quality of DWI, and showed a significantly higher diagnostic accuracy in meningioma grading.

Impact: Meningioma is the most commom intracranial tumours. This study revealed that MUSE-DWI, compared with ssEPI-DWI, can improve the imaging quality and grading accuracy of meningiomas, contributing to better clinical evaluation of meningiomas.

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