Radiomics for predicting Grades, IDH mutation and MGMT promoter methylation of Adult Diffuse Gliomas: Combination of structural MRI, ADC and SWI
Motivation: WHO Grade, IDH mutation and MGMT promoter methylation are important for precise diagnosis and treatment plans for diffuse glioma patients. Goal(s): This study aimed to investigate the predictive value of radiomics features extracted from Structural MRI, ADC and SWI. Approach: Radiomic features were extracted from T1WI, T2WI, T1CE, FLAIR, ADC and SWI. Analysis of variance F-test were used for feature selection. 11 classifiers were utilized for model establishment. Results: For WHO Grade task, the highest AUC was 0.990; for IDH mutation task, the highest AUC was 0.947. All the constructed models failed to predict MGMT promoter methylation status efficiently. Impact: This work will help neuro-oncologists better understand the radiological manifestation of gliomas.
Authors
- Huiquan Yang (ORCID: https://orcid.org/0009-0008-6980-8792)
- Xin Zhang (ORCID: https://orcid.org/0000-0002-5096-7194)
- Bing Zhang (ORCID: https://orcid.org/0000-0001-7592-1195)
- Jianan Zhou (ORCID: https://orcid.org/0000-0002-1775-6221)
- Liang Xue (ORCID: https://orcid.org/0009-0004-4744-3199)
- Zhengyang Zhu
Publication Details
- Journal
- Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
- Published
- 2024-11-26
- DOI
- https://doi.org/10.58530/2024/0374
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00