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. 2024 Dec 5;14(12):9276-9289.
doi: 10.21037/qims-24-1110. Epub 2024 Nov 29.

Radiomics for predicting grades, isocitrate dehydrogenase mutation, and oxygen 6-methylguanine-DNA methyltransferase promoter methylation of adult diffuse gliomas: combination of structural MRI, apparent diffusion coefficient, and susceptibility-weighted imaging

Affiliations

Radiomics for predicting grades, isocitrate dehydrogenase mutation, and oxygen 6-methylguanine-DNA methyltransferase promoter methylation of adult diffuse gliomas: combination of structural MRI, apparent diffusion coefficient, and susceptibility-weighted imaging

Zhengyang Zhu et al. Quant Imaging Med Surg. .

Abstract

Background: There has been no research investigating susceptibility-weighted imaging (SWI) radiomics features in evaluating molecular makers in gliomas. The aim of this study was to assess the predictive value of radiomics features extracted from structural magnetic resonance imaging (MRI), apparent diffusion coefficient (ADC), and SWI in determining World Health Organization (WHO) Grade, isocitrate dehydrogenase (IDH) mutation, and oxygen 6-methylguanine-DNA methyltransferase (MGMT) promoter methylation in patients with diffuse gliomas.

Methods: Retrospective MRI data of 539 patients from University of California San Francisco and Nanjing Drum Tower Hospital between January 2010 and December 2022 were analyzed in this study. The training, internal validation, and external test cohorts included 426 (median age 60 years, 168 female), 67 (median age 56 years, 31 female), and 46 (median age 55 years, 22 female) patients, respectively. A total of 7,896 radiomics features were extracted from structural MRI, ADC, and SWI within two regions of interest (ROIs). Feature selection was conducted using analysis of variance (ANOVA) F-test, and random forest was employed to establish predictive models. Chi-square test and Mann-Whitney U test were used for assessing the statistical differences in patients' clinical characteristics. Delong test was performed to compare the areas under the curve (AUCs) of different radiomics models.

Results: For WHO Grade task, the combined model of structural MRI, ADC, and SWI achieved the highest AUC of 0.951 [95% confidence interval (CI): 0.886-1.000] on the external test cohort. For IDH mutation task, the structural MRI model achieved the highest AUC of 0.917 (95% CI: 0.801-1.000) on the external test cohort. For MGMT task, the combined model of structural MRI and ADC achieved the highest AUC of 0.650 (95% CI: 0.485-0.814) on the internal validation cohort.

Conclusions: The combined structural MRI, ADC, and SWI models achieved promising performance in assessing WHO Grade and IDH mutation status but showed no efficacy in predicting MGMT methylation status. Adding SWI and ADC features cannot provide extra information to structural MRI in predicting WHO grade and IDH mutation.

Keywords: Susceptibility-weighted imaging (SWI); apparent diffusion coefficient (ADC); isocitrate dehydrogenase (IDH); machine learning; radiomics.

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Conflict of interest statement

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://qims.amegroups.com/article/view/10.21037/qims-24-1110/coif). The authors have no conflicts of interest to declare.

Figures

Figure 1
Figure 1
Patients enrollment flowchart. UCSF-PDGM, University of California San Francisco Preoperative Diffuse Glioma; ADC, apparent diffusion coefficient; SWI, susceptibility-weighted imaging.
Figure 2
Figure 2
Example for MRI images of a patient with glioblastoma, IDH wild type, WHO Grade 4, MGMT unmethylated: T1CE (A), T2WI (B), T1WI (C), FLAIR (D), segmentation on T1CE (E), segmentation on T2WI (F), ADC (G), and SWI (H). Yellow area: enhancing tumor area. Red part: non-enhancing tumor area. MRI, magnetic resonance imaging; IDH, isocitrate dehydrogenase; WHO, World Health Organization; MGMT, oxygen 6-methylguanine-DNA methyltransferase; T1CE, contrast-enhanced T1-weighted imaging; T2WI, T2-weighted imaging; T1WI, T1-weighted imaging; FLAIR, fluid-attenuated inversion recovery; ADC, apparent diffusion coefficient; SWI, susceptibility-weighted imaging.
Figure 3
Figure 3
Example for MR images of a patient with astrocytoma IDH mutant, WHO Grade 3, MGMT methylated: T1CE (A), T2WI (B), T1WI (C), FLAIR (D), segmentation on T1CE (E), segmentation on T2WI (F), ADC (G), and SWI (H). Red area: non-enhancing tumor area. MR, magnetic resonance; IDH, isocitrate dehydrogenase; WHO, World Health Organization; MGMT, oxygen 6-methylguanine-DNA methyltransferase; T1CE, contrast-enhanced T1-weighted imaging; T2WI, T2-weighted imaging; T1WI, T1-weighted imaging; FLAIR, fluid-attenuated inversion recovery; ADC, apparent diffusion coefficient; SWI, susceptibility-weighted imaging.
Figure 4
Figure 4
Study design of this research. ANOVA, analysis of variance; AUC, area under the curve; CI, confidence interval.
Figure 5
Figure 5
ROC curves for the internal validation cohort and external test cohort of the multiparametric radiomics models in predicting WHO grade, IDH mutation and MGMT promoter methylation status. ROC, receiver operating characteristic; AUC, area under the curve; CI, confidence interval; IDH, isocitrate dehydrogenase; WHO, World Health Organization; MGMT, oxygen 6-methylguanine-DNA methyltransferase; ADC, apparent diffusion coefficient; SWI, susceptibility-weighted imaging; MRI, magnetic resonance imaging.

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