Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition
9 May 2026 – 14 May 2026 · Cape Town, South Africa
364-02-006 ISMRM Abstract

Assessment of CT-Based Synthetic T1CE MRI Using a Deep Learning Model for Meningioma Screening: A Multicenter Study

Primary: Acquisition & Reconstruction - AI methods
Secondary: Neuro - Tumors
364-02-006 · Innovations in Brain Tumor Imaging: Quantitative MRI, Radiogenomics, and Deep-Learning Approaches · Monday, 11 May, 9:15 AM–10:10 AM · Digital Posters Row E
Keywords: Deep learning Meningiomas Generation Qualitative evaluation Quantitative evaluation
Accepted
Jin Cui1, Pu-Yeh Wu 2, Nan Mei1, Ji Xiong1, Dongdong Wang1, Yue Hu1, Kaiyi Liang3, Qiufeng Zhao4, Lei Fang5, Yao Chen6, Zhisong Zheng7, Wenxue Feng1, Kaiyue Zhang1, Mengping Hong1, Jie Chen1, Yiping Lu1, Bo Yin1
1Huashan Hospital, Fudan University, China
2GE Healthcare, Beijing, China
3Department of Radiology, Jiading District Central Hospital Affiliated Shanghai University of Medicine & Health Sciences, Shanghai, China
4Department of Radiology, Longhua Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China
5Department of Radiology, Shanghai Pudong Hospital, Fudan University Pudong Medical Center, Shanghai, China
6Wuxi Huishan District People's Hospital, Wuxi, China
7Binzhou Medical University Hospital, Binzhou, China
Presenting Author: Pu-Yeh Wu

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References

1. 1. Nayeri A, Prablek MA, Brinson PR, Weaver KD, Thompson RC, Chambless LB: Short-term postoperative surveillance imaging may be unnecessary in elderly patients with resected WHO Grade I meningiomas. Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia 2016, 26:101-104.doi:10.1016/j.jocn.2015.11.002. [doi]
2. 2. Li Z, Cao G, Zhang L, Yuan J, Li S, Zhang Z, Wu F, Gao S, Xia J: Feasibility study on the clinical application of CT-based synthetic brain T1-weighted MRI: comparison with conventional T1-weighted MRI. European radiology 2024, 34(9):5783-5799.doi:10.1007/s00330-023-10534-1. [doi]
3. 3. Jiang M, Wang S, Song Z, Song L, Wang Y, Zhu C, Zheng Q: Cross(2)SynNet: cross-device-cross-modal synthesis of routine brain MRI sequences from CT with brain lesion. Magma (New York, NY) 2024, 37(2):241-256.doi:10.1007/s10334-023-01145-4. [doi]
4. 4. Wamelink I, Azizova A, Booth TC, Mutsaerts H, Ogunleye A, Mankad K, Petr J, Barkhof F, Keil VC: Brain Tumor Imaging without Gadolinium-based Contrast Agents: Feasible or Fantasy? Radiology 2024, 310(2):e230793.doi:10.1148/radiol.230793. [doi]
5. 5. Murugesan G, Yu FF, Achilleos M, DeBevits J, Nalawade S, Ganesh C, Wagner B, Madhuranthakam AJ, Maldjian JA: Synthesizing Contrast-Enhanced MR Images from Noncontrast MR Images Using Deep Learning. AJNR American journal of neuroradiology 2024, 45(3):312-319.doi:10.3174/ajnr.A8107. [doi]
6. 6. Hu N, Zhang T, Wu Y, Tang B, Li M, Song B, Gong Q, Wu M, Gu S, Lui S: Detecting brain lesions in suspected acute ischemic stroke with CT-based synthetic MRI using generative adversarial networks. Annals of translational medicine 2022, 10(2):35.doi:10.21037/atm-21-4056. [doi]

Cite this abstract

http://echo.ismrm.org/p/ISMRM2026/364-02-006