Assessment of MGMT promoter methylation status in glioblastoma using deep learning features from multi-sequence MRI of intratumoral and peritumoral regions
The deep learning model based on MRI data can effectively distinguish between glioblastoma patients with and without MGMT promoter methylation.
Authors
- Nan Meng (ORCID: https://orcid.org/0000-0003-4336-1474)
- Shuting Jin (ORCID: https://orcid.org/0000-0002-8113-9367)
- Yaping Wu (ORCID: https://orcid.org/0000-0002-2979-5332)
- Qingxia Wu (ORCID: https://orcid.org/0000-0003-4888-8830)
- Jing Zhou (ORCID: https://orcid.org/0000-0002-8420-5462)
- Xuan Yu (ORCID: https://orcid.org/0000-0003-3343-7105)
- Panlong Li (ORCID: https://orcid.org/0000-0001-8871-4849)
- Meiyun Wang (ORCID: https://orcid.org/0000-0003-4454-5005)
- Yan Bai (ORCID: https://orcid.org/0000-0001-8779-6184)
- Huanhuan Liu
Institutions
- Zhengzhou University (CN)
- Henan Academy of Sciences (CN)
- Henan Provincial People's Hospital (CN)
- Wuhan University of Science and Technology (CN)
- Ministry of Industry and Information Technology (CN)
Publication Details
- Journal
- Cancer Imaging
- Published
- 2024-12-23
- DOI
- https://doi.org/10.1186/s40644-024-00817-1
- Citations
- 12
- Primary Topic
- Glioma Diagnosis and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 5.26
Funders
- National Natural Science Foundation of China