Prediction of IDH1 gene mutation by a nomogram based on multiparametric and multiregional MR images

Highlights

• Combination of clinical factors and radiomic features to construct models for predicting IDH1 gene mutations in glioma.

• Multiparametric and multiregional MR images were used to achieve more accurate prediction performance.

• The model performance with different regions of interest for different sequences was compared.

Abstract

Objective

To investigate the value of a nomogram based on multiparametric and multiregional MR images to predict Isocitrate Dehydrogenase-1 (IDH1) gene mutations in glioma.

Data and methods

The authors performed a retrospective analysis of 110 MR images of surgically confirmed pathological gliomas; 33 patients with IDH1 gene Mutation (IDH1-M) and 77 patients with Wild-type IDH1 (IDH1-W) were divided into training and validation sets in a 7:3 ratio. The clinical features were statistically analyzed using SPSS and R software. Three glioma regions (rCET, rE, rNEC) were outlined using ITK-SNAP software and projected to four conventional sequences (T1, T2, Flair, T1C) for feature extraction using AI-Kit software. The extracted features were screened using R software. A logistic regression model was established, and a nomogram was generated using the selected clinical features. Eight models were developed based on different sequences and ROIs, and Receiver Operating Characteristic (ROC) curves were used to evaluate the predictive efficacy. Decision curve analysis was performed to assess the clinical usefulness.

Results

Age was selected with Radscore to construct the nomogram. The Model 1 AUC values based on four sequences and three ROIs were the highest in these models, at 0.93 and 0.89, respectively. Decision curve analysis indicated that the net benefit of model 1 was higher than that of the other models for most Pt-values.

Conclusion

A nomogram based on multiparametric and multiregional MR images can predict the mutation status of the IDH1 gene accurately.

Keywords
Glioma of the brain; Magnetic resonance imaging; Isocitrate dehydrogenase; Radiomics; Genotype