The preoperative grading of gliomas, which is critical for determination of the most appropriate treatment, remains unsatisfactory^[1]. As an improved MRI technique, diffusion-weighted imaging (DWI) is considered the most sensitive for early pathological changes and therefore can potentially be useful in evaluating the glioma grades^[2-4]. Recently, apparent diffusion coefficient (ADC) values derived from the high (3000 sec/mm²) b values DWI were reported to improve the diagnostic performance of DWI in differentiating high- from low-grade gliomas^[5]. But a mono-exponential model and relatively lower high-b values were used in this study^[5].

We used a tri-component model to calculate ultra-high ADC (ADC_uh) in our research, aiming to retrospectively compare the efficacy of ultra-high and conventional mono-b value DWI in the glioma grading.

This retrospective study was approved by the Ethics Committee and informed consents were obtained from all participants. Between July 2014 and September 2015, seventy-four consecutive glioma patients (mean age, 47 years; range, 2-87 years) confirmed by postoperative histopathology and immunohistochemistry were enrolled in the study. Each subject underwent routine MRI, eighteen b-value DWI (b-value:0,50,100,150,200,300,500,800,1000,1300,1500,1700,2000,2500,3000,3500,4000,4500 sec/mm²), as well as contrast-enhanced MRI sequence of the brain on a 3.0-T MRI system (MR750, GE Healthcare, Milwaukee, USA) before any treatments. All data were analyzed and processed on a GE ADW4.6 workstation. The multi-b-value data were analyzed using a AQP program. A freehand ROI was placed on the solid tumor parts with the highest signal intensity on DW image (b=1000-4000 sec/mm²) and the corresponding region of relatively low ADC values on the ADC map to avoid hemorrhagic, calcified, cystic and necrotic areas (as shown in Figure 1A or D). Tri-exponential curve (Figure 1B or E), ADCuh maps (Figure 1C or F) were generated. The ADC values at standard (1000 sec/mm²) and ultrahigh (0-4500 sec/mm²) b values were calculated according to the mono-exponential (ADC_st) and tri-component model (ADC_uh), respectively^[6]. Parameters ADC_uh, ADC_st, ADC_{uh_edema} (edema area) and ADC_{uh_wm} (contralateral healthy white matter area) were compared for the differences between the low-grade (WHO I and II) and high-grade gliomas (WHO III and IV) by using independent sample t test. Receiver operating characteristic (ROC) analyses were performed to determine optimal thresholds for differentiating the low-grade from the high-grade gliomas by ADCuh and ADCst value respectively. Also the sensitivity, specificity, and area under curve (AUC) for differentiating the low-grade gliomas were calculated.Among the 74 studied patients, 18 were low-grade and 56 were high-grade gliomas. ADC_uh and ADC_st tended to be higher in the low-grade glioma (P=0.000, Table 1 and Fig 2), while no significant differences were found in tumor edema area (ADC_{uh_edema}) and contralateral healthy white matter area (ADC_{uh_wm}). According to the ROC analyses, with AUC of 0.922, ADC_uh parameter had 94.4 % sensitivity and 78.6 % specificity for differentiating the low-grade gliomas at the cutoff value of 0.362×10⁻³ mm²/sec. With regards to ADC_st, AUC of 0.886, and 83.3% sensitivity and 82.1% specificity at the cutoff value of 1.105×10⁻³ mm²/sec were achieved(Table 2).This study suggested that the ADC_uh based on tri-exponential model DWI could be used to grade gliomas preoperatively. We detected significant differences in parameters ADC_uh and ADC_st between low- and high-grade gliomas. We also determined the most appropriate cutoff values for both parameter, which could potentially be used in clinical practice regarding preoperatively grading gliomas.Both tri- and mono-exponential models provide accurate preoperative glioma gradings. The ADC_uh parameter demonstrate higher efficacy over the conventional ADC value. Glioma; Grading; Diffusion-weighted imaging; MRI; Apparent diffusion coefficient