Meeting Banner
Abstract #0871

Using Multi-sequence MRI-based Convolutional Neural Network to Predict the Methylation Status of MGMT Promoter in Glioma

Xiaohua Chen1,2, Zhiqiang Chen3, Ruodi Zhang1, Yunshu Zhou1, Shili Liu1, and Yuhui Xiong4
1Clinical medicine school of Ningxia Medical University, Yinchuan, China, 2Medical Imaging Center of Ningxia Hui Autonomous Region People's Hospital, Yinchuan, China, 3Department of Radiology ,the First Hospital Affiliated to Hainan Medical College, Haikou, China, 4GE Healthcare MR Research, Beijing, China

Synopsis

Keywords: Diagnosis/Prediction, Radiomics, Gliomas

Motivation: The MGMT promoter is closely associated with the survival period of glioma patients and their response to chemotherapy drug temozolomide. Predicting the promoter status of MGMT accurately pre-operator is crucial for making personalized treatment decisions for glioma patients.

Goal(s): To propose models based on CNNs to predict the MGMT methylation status of gliomas using conventional pre-operative MR images.

Approach: Building three CNNs models based on T2WI, T2-FLAIR, CE-T1WI images, respectively. Fusing features to build the fourth model to predict the MGMT methylation status.

Results: All models can predict the MGMT status effectively and accurately, the fused-feature model has the best diagnostic performance.

Impact: Models based on conventional MRI sequences and VASARI features provide the clinical value for evaluation of molecular typing in gliomas. It is expected to become a practical tool for the non-invasive characterization of gliomas to help the individualized treatment planning.

How to access this content:

For one year after publication, abstracts and videos are only open to registrants of this annual meeting. Registrants should use their existing login information. Non-registrant access can be purchased via the ISMRM E-Library.

After one year, current ISMRM & ISMRT members get free access to both the abstracts and videos. Non-members and non-registrants must purchase access via the ISMRM E-Library.

After two years, the meeting proceedings (abstracts) are opened to the public and require no login information. Videos remain behind password for access by members, registrants and E-Library customers.

Click here for more information on becoming a member.

Keywords