Purpose An accurate differentiation of brain glioma grade constitutes an important clinical issue. Powerful non-invasive approach based on diffusion MRI has already demonstrated its feasibility in glioma grade stratification. However, the conventional diffusion tensor (DTI) and kurtosis imaging (DKI) demonstrated moderate sensitivity and performance in glioma grading. In the present work, we apply generalised DKI (gDKI) approach in order to assess its diagnostic accuracy and potential application in glioma grading. Methods Diffusion scalar metrics were obtained from 50 patients with different glioma grades confirmed by histological tests following biopsy or surgery. All patients were divided into two groups with low- and high-grade gliomas as grade II versus grades III and IV, respectively. For a comparison, trained radiologists segmented the brain tissue into three regions with solid tumour, oedema, and normal appearing white matter. For each region, we estimated the conventional and gDKI metrics including DTI maps. Results We found high correlations between DKI and gDKI metrics in high-grade glioma. Further, gDKI metrics enabled introduction of a complementary measure for glioma differentiation based on correlations between the conventional and generalised approaches. Both conventional and generalised DKI metrics showed quantitative maps of tumour heterogeneity and oedema behaviour. gDKI approach demonstrated largely similar sensitivity and specificity in low-high glioma differentiation as in the case of conventional DKI method. Conclusion The generalised diffusion kurtosis imaging enables differentiation of low- and high-grade gliomas at the same level as the conventional DKI. Additionally, gDKI exhibited higher sensitivity to tumour heterogeneity and tissue contrast between tumour and healthy tissue and, thus, may contribute as a complementary source of information on tumour differentiation.

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We found a correlation between the CT-based ONSD and the median ICP (R=0.32, p<0.05). An ONSD value of 6.35 mm and more is one of the signs of previous or existing ICP.

Aim: to explore the opportunities of application of diffusionkurtosis imaging (DKI) for assessment and estimation of diffusion scalar metrics in different locations of peritumoral edema for extra- and intracerebral tumors and in contralateral normal tissue.Materials and methods. 38 patients with supratentorial brain tumors were investigated: 24 (63%) patients with primarily revealed glioblastomas (GB) and 14 (37%) patients with solitary cancer brain metastasis (MTS). MRI was performed on 3.0 T MR-scanner (Signa HDxt, General Electric, USA) with the standard protocols for brain tumor and additional protocol for DKI. The standard protocol for brain tumor included: T1-, T2-weighted images, T2-FLAIR, DWI,  T1 with contrast enhancement. Diffusion kurtosis MRI based on SE  EPI with TR = 10000 ms, TE = 102 ms, FOV = 240 mm, isotropic voxel size 3 × 3 × 3 mm3, 60 noncoplanar diffusion directions. We  used three b-values: 0, 1000 and 2500 s/mm2. Аcquisition time was 22 min. Total acquisition time was near 40 min. This study was approved by Ethical committee of Burdenko National Scientific  and Practical Center for Neurosurgery. Parametric maps were  constructed for the following diffusion coefficients: mean (MK),  transverse / radial (RK), longitudinal / axial (AK) kurtozis; medium  (MD), transverse / radial (RD) and longitudinal / axial (AD) diffusion; fractional anisotropy (FA) and a bi-exponential diffusion model  coefficients: axonal water fractions (AWF), axial (AxEAD) and radial  (RadEAD) extra-axonal water diffusion and the water molecules  trajectory tortuosity index (TORT). Normative quantitative indicators  were obtained for the six regions of the peritumoral zone as they  moved away from the tumor (region 2) to the edema periphery  (regions 4–5), as well as in the normal brain on the contralateral  hemisphere (C/L) (zone 7). A comparative analysis of these  indicators was conducted for cases with GB and MTS. DKI scalar metrics were estimated using Explore DTI (http://www.exploredti.com/).Results. Anatomic MRI (T1 without/with contrast enhancement) for  all cases with GB and MTS visualized a contrast enhancement tumor.  The peritumoral edema, spreading mainly over the brain white  matter, was well visualized on T2-FLAIR. Diffusion kurtosis  coefficients decreased in the near peritumoral edema (regions 2–3)  and a gradually increased to the edema periphery (regions 5–6). In Region 2, MK in both GB and MTS groups were MKGB(2) = 0.637 ±  0.140 and MKMTS(2) = 0.550 ± 0.046; RK in this region were  RKGB(2) = 0.690 ± 0.154 and RKMTS (2) = 0.584 ± 0.051.  Differences both MK and RK coefficients in patients with GB and MTS of region 2 were significant (p < 0.001). There were no differences in AK values for GB and MTS in region 2 (p > 0.05), but in regions 3  and 4 differences were observed (p < 0.01). The minimum value of  AK in the central edema (regions 3–4) was AKMTS(3–4) = 0.433 ± 0.063 in patients with MTS. The values of MK and RK on the  contralateral side in patients with MTS were significantly higher than  in the GB group (p < 0.02); MKC/LMTC = 0.954 ± 0.140, RKC/LMTC  = 1.257 ± 0.308 and MKC/LGB = 0.829 ± 0.146, RKc/LGB = 0.989  ± 0.282. There was no significant difference for contralateral AK between the groups.Conclusions. We found that DKI scalar metrics are the sensitive  tumor biomarkers. It allows us to perform a robust differentiation  between the infiltrating GB tumor and purely vasogenic edema of  МТS. The obtained results will allow further differential diagnosis of  extra- and intracerebral tumors and can be used to plan surgical /  radiosurgical treatment for brain tumors.

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