Haibo Dong

This study aimed to construct an imaging genomics nomogram based on intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) to predict the status of the alpha thalassemia/mental retardation syndrome X-linked (ATRX) gene in patients with brain gliomas. We retrospectively analyzed routine MR and IVIM-DWI data from 85 patients with pathologically confirmed brain gliomas from January 2017 to May 2023. The data were divided into a training set (N=61) and a test set (N=24) in a 7:3 ratio. Regions of interest (ROIs) of brain gliomas, including the solid tumor region (rCET), edema region (rE), and necrotic region (rNec), were delineated using 3D-Slicer software and projected onto the D, D*, and f sequences. A total of 1037 features were extracted from each ROI, resulting in 3111 features per patient. Age was incorporated in the calculation of the Radscore, and a clinical-imaging genomics combined model was constructed, from which a nomogram graph was generated. Separate models were built for the D, D*, and f parameters. The AUC value of the D parameter model was 0.97 (95% CI: 0.93–1.00) in the training set and 0.91 (95% CI: 0.79–1.00) in the validation set, which was significantly higher than that of the D* parameter model (0.90, 0.82) and the f parameter model (0.89, 0.91). The imaging genomics nomogram based on IVIM-DWI can effectively predict the ATRX gene status of patients with brain gliomas, with the D parameter showing the highest efficacy.

Intravoxel incoherent motion (IVIM) magnetic resonance imaging (MRI) has been applied to gliomas; however, the relationships between its parameters and isocitrate dehydrogenase 1 (IDH1) mutations in gliomas remain to be investigated. To investigate the value of IVIM in predicting IDH1 mutations in high-grade gliomas before surgery. A total of 72 patients with pathologically confirmed high-grade gliomas underwent conventional brain MRI and IVIM from September 2016 to May 2020. Among them, 22 cases were IDH1 mutant and 50 cases were IDH1 wild type. The independent samples t test (normal distribution and homogeneity of variance) or Mann–Whitney rank-sum test (non-normal distribution or heterogeneity of variance) was conducted, and receiver operating characteristic curves were generated to determine parameters for distinguishing IDH1-mutated from IDH1 wild-type high-grade gliomas. These parameters included apparent diffusion coefficient (ADC), true diffusivity (D), pseudo-diffusivity (D*), and perfusion fraction (f). ADC, D, and f were significantly higher in IDH1-mutated gliomas than in IDH1 wild-type gliomas (P < 0.05 for all). There was no significant difference in the D* value between the two groups (P = 0.053). The areas under the curve of ADC, D, and f in predicting IDH1 mutations in gliomas were 0.798, 0.810, and 0.823, respectively. The specificity of ADC was highest (80.0%), and the sensitivity of the f value was the highest (100.0%). IVIM can be used for the quantitative prediction of IDH1 mutations in high-grade gliomas before surgery, and the f value is the most effective.

Intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) and three-dimensional arterial spin labeling (3D-ASL) have been applied to brain tumors; however, the relationship between their parameters and the Ki-67 labeling index (Ki-67 LI) for the grading of gliomas have yet to be investigated. The aim of this study is to compare multiple parameters obtained from IVIM-DWI and 3D-ASL with the Ki-67 LI when grading gliomas. Fifty-two patients with pathologically confirmed gliomas had undergone magnetic resonance imaging (MRI), including IVIM-DWI and 3D-ASL imaging. Mann–Whitney U tests were conducted and receiver operating characteristic (ROC) curves were generated to determine parameters for distinguishing high-grade gliomas (HGGs) from low-grade gliomas (LGGs). These parameters included the apparent diffusion coefficient (ADC), true diffusivity (D), pseudo diffusivity (D*), perfusion fraction (f), cerebral blood flow (CBF), and their relative values (rADC, rD, rD*, rf, and rCBF). Spearman correlation analysis was used to assess the correlations of the parameters of MRI with the Ki-67 LI. The rADC, rD, and rf were significantly lower in HGGs than in LGGs (P < 0.005 for all). The rD had a significantly greater area under the ROC curve than that of the other parameters in the differentiation of HGGs from LGGs (P < 0.05). Both the rD and rf were moderately negatively correlated with the Ki-67 LI. Both the rD and rf can be used for the quantitative prediction of the Ki-67 LI. Among the extracted parameters, the rD had the significantly greatest diagnostic efficacy.