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Clinical Article
The value of predicting the subtype of IDH mutation combining with MGMT promoter methylation in lower grade gliomas by radiomics based on preoperative MRI
SHA Yongjian  WANG Xiaochun  TAN Yan  ZHANG Hui  YANG Guoqiang 

Cite this article as: Sha YJ, Wang XC, Tan Y, et al. The value of predicting the subtype of IDH mutation combining with MGMT promoter methylation in lower grade gliomas by radiomics based on preoperative MRI[J]. Chin J Magn Reson Imaging, 2022, 13(7): 6-11. DOI:10.12015/issn.1674-8034.2022.07.002.


[Abstract] Objective To develope a radiomics model to predict the subtype of isocitrate dehydrogenase mutation (IDH-mut) combining with O6-methylguanine DNA methyltransferase promoter methylation (MGMT meth) in LGGs (lower grade gliomas).Materials and Methods Preoperative MRI images, clinical and genetic information of 158 patients from the First Hospital of Shanxi Medical University, Shanxi People's Hospital and the TCGA/TCIA (The Cancer Genome Atlas and The Cancer Imaging Archive) common dataset were retrospectively collected. The above three data sets were integrated, their images were resampling and normalized, and then randomly divided into the training set and the test set in a ratio of 7∶3. A total of 1702 radiomics features of the post-contrast enhanced T1-weighted sequence (CE-T1) and the T2-weighted fluid attenuation inversion recovery sequence (T2-FLAIR) were extracted from preoperative MRI images. Feature selection was performed by single-factor logistic regression (LR), and then performed by least absolute shrinkage and selection operator (LASSO). In order to solve the shortage of minority samples and improve the universality of the model, the synthetic minority oversampling technique (SMOTE) was used to balance the training set, and then multi-factor LR was used for modeling. Finally, the performance and goodness of fit of the model was verified using receiver operating characteristic curve (ROC) and calibration curve, and a nomogram was established for visual risk prediction.Results There were no statistically significant differences in the clinical characteristics of the two subtypes in the training set and test set (P<0.05). The area under the curve (AUC) of the radiomics model in the training set and the test set were 0.842 and 0.935, respectively, and the F-Measure were 0.965 and 0.942, respectively. The P value of the Hosmer-Lemeshow test of the calibration curve of the training set was 0.1393.Conclusions The preoperative MRI radiomics model can predict the subtype of IDH mutation combined with MGMT promoter methylation in LGGs, thus providing auxiliary guidance value for LGGs in molecular subtype diagnosis, temozolomide (TMZ) treatment decision-making and survival prediction.
[Keywords] lower grade glioma;radiomics;magnetic resonance imaging;isocitrate dehydrogenase;O6-methylguanine-DNA methyltransferase;molecular subtype

SHA Yongjian1   WANG Xiaochun2   TAN Yan2   ZHANG Hui2   YANG Guoqiang2*  

1 School of Medical Imaging, Shanxi Medical University, Taiyuan 030001, China

2 Department of Radiology, First Hospital of Shanxi Medical University, Taiyuan 030001, China

Yang GQ, E-mail: doctor_ygq@163.com

Conflicts of interest   None.

Received  2022-02-13
Accepted  2022-07-01
DOI: 10.12015/issn.1674-8034.2022.07.002
Cite this article as: Sha YJ, Wang XC, Tan Y, et al. The value of predicting the subtype of IDH mutation combining with MGMT promoter methylation in lower grade gliomas by radiomics based on preoperative MRI[J]. Chin J Magn Reson Imaging, 2022, 13(7): 6-11.DOI:10.12015/issn.1674-8034.2022.07.002

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