Abstract
PurposeAn 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.MethodsDiffusion 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.ResultsWe 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.ConclusionThe 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.
Highlights
Primary brain glioma is a highly widespread type of intraaxial brain tumours seen approximately in one-fourth diagnosed tumour cases [1]
Classification of the brain tumours is performed in accordance with grades introduced by the World Health Organization (WHO) [2] which combine histopathological and molecular features into integrated tumour characterisation
We can see that the visual quality of mean diffusivity (MD) maps between conventional kurtosis (CK) and generalised kurtosis approach (GK) approaches is very similar
Summary
Primary brain glioma is a highly widespread type of intraaxial brain tumours seen approximately in one-fourth diagnosed tumour cases [1]. Glioma grades are ordered from grades I up to IV related to tumour’s aggressiveness and malignancy. Both the tumour’s diagnosis and its grade can be reliably confirmed by a histopathologic analysis of the tumour’s tissue obtained from an invasive procedure such as biopsy or surgery. Neuroradiology (2021) 63:1241–1251 malignancy are necessary for clinical treatment, surgery planning, and survival rate estimations. This applies to low-grade tumour cases where such assessments contribute to treatment efficacy and, as a result, improve quality of life for patients. Conventional MRI techniques such as structural T1/T2-weighted imaging with or without contrast agents or magnetic resonance spectroscopy demonstrate limited sensitivity and specificity for brain glioma differentiation [3, 4]
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
