DKI was collected from September 2016 to September 2017. Before scanning, consent was obtained from the patients or their guardians. A total of 150 patients aged 14–70-years-old with single space-occupying lesions were recruited. Seventy-three patients had a surgical pathological diagnosis of glioma, including WHO II (n=21), WHO III (n= 13), and WHO IV (n=39), among whom 38 had IDH mutation status (IDH wildtype, n=21; IDH mutation, n=17).
A Siemens Prisma 3.0 T (Prisma Siemens Healthcare, Erlangen, Germany) MRI scanner with a 64-channel head/neck coil was used. Conventional scans, enhanced scans, and DKI sequences that lasted a total of 30 minutes were performed on patients. The various sequence parameters are as follows: Axial and sagittal T1-weighted imaging: TR = 250 ms, TE = 2.46 ms; Axial T2-weighted imaging: TR = 4000 ms, TE = 95 ms; both sequences had similar FOV = 230 mm × 230 mm, number of slices = 20, slice thickness = 5.0 mm, matrix = 256 × 256. A spin-echo echoplanar imaging sequence was used for the acquisition of DKI (TR = 3500 ms, TE = 78 ms; b = 0, 500, 1000, 1500, 2000, 2500; diffusion direction = 30, slice thickness = 5.0 mm, number of slices = 20, FOV = 220 mm × 220 mm, matrix = 384 × 384, scan time = 9 minutes and 1 second). Contrast-enhanced scan: a high-pressure injector was used for elbow vein injection of gadopentetate dimeglumine (Magnevist, Bayer Schering Pharma AG, Berlin, Germany) at a dose of 0.1 mmol/kg bodyweight and an injection speed of 2.0 ml/s. The T1 volume interpolated breath-hold sequence (TR = 630 ms, TE = 9.3 ms) was used for dynamic enhanced acquisition in the axial plane for six cycles. The sagittal plane 3D-T1MPRAGE (magnetization-prepared rapid gradient echo) sequence was used for the delayed enhanced scan, with TR＝2300 ms, TE = 2.32 ms, slice thickness = 0.9 mm, number of slices = 179, FOV = 240 mm × 240 mm, matrix = 256 × 256, and a scan time of 5 minutes and 21 seconds, and axial and coronal post-contrast T1MPRAGE images were reconstructed to include the whole brain with section thickness = 5 mm and intersection gap = 1 mm.
The raw DKI images were imported into the DKE  software for preprocessing to obtain MK, RK, AK, mean diffusivity (MD), and fractional anisotropy (FA) graphs. Under the guidance of two experienced magnetic resonance physicians and by using the T2WI and T1contrast-enhanced scan images as reference, we manually selected ROIs in continuous solid tumor regions in the MRIcron software by avoiding cystic changes, bleeding, necrosis, calcifications, and regions close to the blood vessels and cerebrospinal fluid. The entire solid tumor component of the glioma was selected as ROI (Figure 1) and the mean values of the corresponding parameters were calculated. At the same time, contralateral normal-appearing white matter (NAWM) from the same slice as the tumor ROI was selected and the parameters were compared to obtain corrected MK, RK, AK, FA, and MD values. Two radiologists with 15 years of experience in head and neck MRI (JB and GA), who were blinded to clinical information and histopathological results, delineated the ROIs of all study subjects.
DWI obtained from the DKI scans were imported into the preset MATLAB platform for histogram analysis. The ROIs selected by histogram analysis were consistent with those drawn in the MRIcron software (Figure 1) to obtain the minimum, maximum, mean, skewness coefficient, kurtosis coefficient, and 25th, 50th, 75th, and 95th percentiles for the Kapp and Dapp .
Statistical Package for the Social Sciences, Version 21.0 (SPSS, IBM, Chicago, USA) was used for statistical analysis in this study, and α=0.05 was used as the test criterion. The MK, AK, RK, FA, and MD values for WHO Grade II, III, and IV gliomas, and the minimum, maximum, mean, skewness coefficient, kurtosis coefficient, and the 25th, 50th, 75th, and 95th percentiles of the Kapp and Dapp values obtained from the MATLAB histogram analysis are expressed as mean ± standard deviation (`x ± s) for inter-group comparison of differences. When required, normalizing transformation (Bloom normalizing transformation) was carried out so that the data conformed to the requirements of the parametric tests. One-way ANOVA and the Least-Square Differential test were used for pairwise inter-group comparison. ROC curves were plotted, the AUC-ROC was calculated, and the threshold values for valid parameters were predicted.