Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition
9 May 2026 – 14 May 2026 · Cape Town, South Africa
565-02-011 ISMRM Abstract

Can Contrast-Enhanced Synthetic MRI Improve the Efficiency of Predicting Meningioma Consistency?

Primary: Neuro - Tumors
Secondary: Acquisition & Reconstruction - Quantitative Imaging: relaxometry, multi-parametric, MR Fingerprinting, and synthetic MRI
565-02-011 · Neuro-Oncology and Ear, Nose, and Throat Cancer · Wednesday, 13 May, 9:15 AM–10:10 AM · Digital Posters Row F
Keywords: Meningiomas Synthetic MRI Histogram Analysis Tumor consistency
Accepted
Ye Li1,2, Mingwei Sun 2, Junzhe Zhao1,2, Jialu Zhang3,4, Yunjing Xue1,2, Lin Lin1,2
1School of Medical Imaging, Fujian Medical University, Fuzhou, China
2Department of Radiology, Fujian Medical University Union Hospital, Fuzhou, China
3MR Research, Beijing, China
4GE Healthcare, Beijing, China
Presenting Author: Mingwei Sun

Synopsis

Motivation:
Goals:
Approach:
Results:
Full abstract & presentation

The full text, figures, and any recorded presentation for this abstract are not shown here. Log in if you are a member or registered attendee with access.

Full abstracts, figures, and presentations for Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition are available to registered attendees. This content becomes freely available to the public roughly two years after the meeting.

To request or purchase access, contact the ISMRM Central Office at info@ismrm.org.

Log in

References

1. Ostrom QT, Price M, Neff C, et al. CBTRUS Statistical Report: Primary Brain and Other Central Nervous System Tumors Diagnosed in the United States in 2015-2019. Neuro Oncol. 2022;24(Suppl 5):v1-v95. doi:10.1093/neuonc/noac202 [doi]
2. Maggio I, Franceschi E, Tosoni A, et al. Meningioma: not always a benign tumor. A review of advances in the treatment of meningiomas. CNS Oncol. 2021;10(2):CNS72. doi:10.2217/cns-2021-0003 [doi]
3. Koechli C, Zwahlen DR, Schucht P, Windisch P. Radiomics and machine learning for predicting the consistency of benign tumors of the central nervous system: A systematic review. Eur J Radiol. 2023;164:110866. doi:10.1016/j.ejrad.2023.110866 [doi]
4. Shah I, Chung RS, Liu K, et al. Association between meningioma consistency and surgical outcomes. J Neurosurg. 2025;142(5):1331-1337. Published 2025 Jan 10. doi:10.3171/2024.8.JNS241066 [doi]
5. Zheng Z, Liu Y, Yin H, et al. Evaluating T1, T2 Relaxation, and Proton Density in Normal Brain Using Synthetic MRI with Fast Imaging Protocol. Magn Reson Med Sci. 2024;23(4):514-524. doi:10.2463/mrms.tn.2022-0161 [doi]
6. Zheng L, Jiang P, Lin D, et al. Histogram analysis of mono-exponential, bi-exponential and stretched-exponential diffusion-weighted MR imaging in predicting consistency of meningiomas. Cancer Imaging. 2023;23(1):117. Published 2023 Dec 5. doi:10.1186/s40644-023-00633-z [doi]
7. Gracien RM, Reitz SC, Hof SM, et al. Changes and variability of proton density and T1 relaxation times in early multiple sclerosis: MRI markers of neuronal damage in the cerebral cortex. Eur Radiol. 2016;26(8):2578-2586. doi:10.1007/s00330-015-4072-x [doi]
8. Zeng F, Yang Z, Tang X, et al. Whole-tumor histogram models based on quantitative maps from synthetic MRI for predicting axillary lymph node status in invasive ductal breast cancer. Eur J Radiol. 2024;172:111325. doi:10.1016/j.ejrad.2024.111325 [doi]
9. Xu X, Zhu H, Li R, et al. Whole-liver histogram and texture analysis on T1 maps improves the risk stratification of advanced fibrosis in NAFLD. Eur Radiol. 2021;31(3):1748-1759. doi:10.1007/s00330-020-07235-4 [doi]

Cite this abstract

http://echo.ismrm.org/p/ISMRM2026/565-02-011