Maynard, J;
              
      
            
                Okuchi, S;
              
      
            
                Wastling, S;
              
      
            
                Busaidi, AA;
              
      
            
                Almossawi, O;
              
      
            
                Mbatha, W;
              
      
            
                Brandner, S;
              
      
            
            
          
      
            
            
          
      
            
            
          
      
            
            
          
      
            
            
            ... Thust, S; + view all
            
          
      
        
        
        
    
  
(2020)
  World Health Organization Grade II/III Glioma Molecular Status: Prediction by MRI Morphologic Features and Apparent Diffusion Coefficient.
Radiology
, 296
       (1)
    
     pp. 111-121.
    
         10.1148/radiol.2020191832.
  
  
       
    
  
| Preview | Text Brandner_World Health Organization Grade II:III Glioma Molecular Status_AAM.pdf - Accepted Version Download (554kB) | Preview | 
Abstract
BACKGROUND: A readily implemented MRI biomarker for glioma genotyping is currently lacking. PURPOSE: To evaluate clinically available MRI parameters for predicting isocitrate dehydrogenase (IDH) status in patients with glioma. MATERIALS AND METHODS: In this retrospective study of patients studied from July 2008 to February 2019, untreated World Health Organization (WHO) grade II/III gliomas were analyzed by three neuroradiologists blinded to tissue results. Apparent diffusion coefficient (ADC) minimum (ADC_{mi}) and mean (ADC_{mean}) regions of interest were defined in tumor and normal appearing white matter (ADC_{NAWM}). visual rating of anatomic features (T1 weighted, T1 weighted with contrast enhancement, T2 weighted, and fluid-attenuated inversion recovery) was performed. Interobserver comparison (intraclass correlation coefficient and Cohen κ) was followed by nonparametric (Kruskal-Wallis analysis of variance) testing of associations between ADC metrics and glioma genotypes, including Bonferroni correction for multiple testing. Descriptors with sufficient concordance (intraclass correlation coefficient, >0.8; κ > 0.6) underwent univariable analysis. Predictive variables (P < .05) were entered into a multivariable logistic regression and tested in an additional test sample of patients with glioma. RESULTS: he study included 290 patients (median age, 40 years; interquartile range, 33–52 years; 169 male patients) with 82 IDH wild-type, 107 IDH mutant/1p19q intact, and 101 IDH mutant/1p19q codeleted gliomas. Two predictive models incorporating ADC_{mean}-to-ADC_{NAWM} ratio, age, and morphologic characteristics, with model A mandating calcification result and model B recording cyst formation, classified tumor type with areas under the receiver operating characteristic curve of 0.94 (95% confidence interval [CI]: 0.91, 0.97) and 0.96 (95% CI: 0.93, 0.98), respectively. In the test sample of 49 gliomas (nine IDH wild type, 21 IDH mutant/1p19q intact, and 19 IDH mutant/1p19q codeleted), the classification accuracy was 40 of 49 gliomas (82%; 95% CI: 71%, 92%) for model A and 42 of 49 gliomas (86%; 95% CI: 76%, 96%) for model B. CONCLUSION: Two algorithms that incorporated apparent diffusion coefficient values, age, and tumor morphologic characteristics predicted isocitrate dehydrogenase status in World Health Organization grade II/III gliomas on the basis of standard clinical MRI sequences alone.
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