The 2016 WHO classification of glioma emphasized the role of genetic parameters in glioma patients’ prognosis and treatment response[22]. The identification of histology and genetic status of gliomas before surgery can benefit these patients. DWI is performed as a routine preoperative method for evaluating gliomas. In this case, ADC’s discriminative abilities in histologic subtypes, IDH, MGMT, and TERT status were assessed, respectively.
In the current study, ADC values generated from DWI (b=0 and 1000 s/mm2) decreased significantly with the WHO glioma grade, which was in accordance with previous studies[16, 23]. Cell density, mitotic activity, and vascularity play important roles in gliomas’ pathological grading[24]. For example, the increment of cell density can remarkably restrict water molecules’ movement, which can be reflected by ADC[24]. Therefore, HGGs were more prone to exhibit lower ADC values than LGGs. Louis et al. [25]discovered that HGGs also had lesser normal brain cells and more tumor cells than LGGs, which may also partly explain the lower ADC values in HGGs.
Accurate identification of IDH status is crucial because the prognosis varies greatly according to IDH status. IDH-mutated gliomas have a significantly better prognosis than IDH-wt gliomas[1]. In this study, the IDH-mut rate was 75.00% in LGGs and 24.32% in HGGs, respectively. The IDH-mut rate of HGGs was higher than the reported indices (75% for LGGs and 12% for HGGs)[26]. The ADC values for IDH-mutated gliomas were significantly higher than those for IDH-wt gliomas, which was consistent with previous research[16, 27]. This difference was more significant when high b-value (b=3000 s/mm2) rather than standard b-value (1000 s/mm2) was used[28]. IDH may inhibit tumor growth by decreasing the level of nicotinamide adenine dinucleotide phosphate production[26] and hypoxia-inducible factor 1α[29]. This mechanism could decrease cell density and partially explain how IDH-mutated gliomas displayed higher ADC values. Besides, we found that IDH-mut had a direct and greater impact on ADC values than tumor grade, which helped to explain why IDH status could predict prognosis better than the histologic classification[30, 31].Besides IDH, MGMT and TERT are also important genetic hallmarks in guiding clinical treatment and evaluating glioma patients’ prognosis[32, 33]. The ADC values are used as a potential marker for predicting MGMT and TERT status in glioblastomas; however, without expert consensus[2, 12-14, 34]. For WHO II-IV gliomas, we found that ADC values had less accuracy and reliability in discriminating MGMT and TERT status, which limited the use of DWI metrics in predicting these two genotypes. Multiple linear regression analysis also revealed that MGMT and TERT status were not independent parameters for ADC values. We hypothesized that coexisting factors or interactions between variables might induce the increment of ADC in TERT-wt and MGMT-m gliomas. For example, in this study, HGGs were more likely to have MGMT-um and IDH-wt than LGGs (P = 0.002 and P<0.0001, respectively), and consequently, the ADC values in MGMT-unmethylated gliomas might be affected by the tumor grading and concurrent IDH-wt. In accordance with our results, no significant relationship between ADC values in glioblastomas and TERT[2, 15] and MGMT status [34] was reported. However, several studies[12-14] showed that ADC values were significantly higher in glioblastomas with MGMT-m than with MGMT-um. These conflicting results may be partly due to the difference in ROI selection and subject recruitment [14]. Unlike previous studies [2, 12-15] that only included glioblastomas, this study recruited patients with WHO II-IV gliomas. Besides, we placed ROIs on the solid part of the tumor, which is different from the previous study where ROIs were placed on the contrast-enhanced part of the tumor[25]. The predictive value of ADC values still needs to be verified by further large-scale comparative studies.
Advances in radiomics[9, 10] and MRI techniques, including ASL[11, 16, 35, 36], DSC[2, 35, 37], and diffusion tensor imaging[38, 39], have been used in evaluating glioma grade or genotypes. Several studies[14, 16, 36] have shown that, compared with perfusion parameters, ADC values have a better predictive effect on tumor grade and genotypes. In this study, only ADC values were assessed because DWI is a commonly used sequence and can be performed in all hospitals. Besides, the postprocessing method of DWI is simple and time-saving.
This study’s strength was that it evaluated the discriminative ability of ADC values in WHO glioma grade and various genetic status in the same study. Therefore, an overall assessment of the predictive power of DWI metrics was available. Accessing various genetic features in one study also helped us identify the valuable genotypes which directly affected ADC values. Since higher ADC values were associated with a more favorable prognosis[12, 40], it was crucial to find out meaningful genotypes that were tightly associated with patients’ outcomes.
Besides the intrinsic limitations of retrospective researches, the other four limitations of this study should be noted. Firstly, biopsy samples used in this study were not acquired by ADC-guided biopsy. Because the ROI-based method cannot assess the direct correlation between histopathology and ADC values, some bias can be produced, especially in more heterogeneous gliomas like HGGs. Secondly, the ROIs did not include peri-tumor areas that may also be infiltrated by glioma cells and contain information reflecting tumor genotypes. Thirdly, the sample size was small. Thus, a larger cohort of patients is needed to verify our conclusions. Fourthly, the genotypes evaluated in this study were limited.