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dc.contributor.authorPogosbekian, Eduard
dc.contributor.authorPronin, Igor N
dc.contributor.authorZakharova, Natalia
dc.contributor.authorBatalov, A.I.
dc.contributor.authorTurkin, A.M.
dc.contributor.authorKonakova, T.A.
dc.contributor.authorMaximov, Ivan
dc.date.accessioned2021-01-29T13:01:11Z
dc.date.available2021-01-29T13:01:11Z
dc.date.created2021-01-08T22:50:49Z
dc.date.issued2021
dc.identifier.citationPogosbekian, E. L., Pronin, I. N., Zakharova, N. E., Batalov, A. I., Turkin, A. M., Konakova, T. A., & Maximov, I. I. (2021). Feasibility of generalised diffusion kurtosis imaging approach for brain glioma grading. Neuroradiology.en_US
dc.identifier.issn0028-3940
dc.identifier.urihttps://hdl.handle.net/11250/2725364
dc.description.abstractPurpose 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.en_US
dc.language.isoengen_US
dc.publisherSpringerNatureen_US
dc.rightsNavngivelse 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/deed.no*
dc.subjectglioblastomaen_US
dc.subjectglioma discriminationen_US
dc.subjectdiffusion kurtosis imagingen_US
dc.titleFeasibility of generalised diffusion kurtosis imaging approach for brain glioma gradingen_US
dc.typePeer revieweden_US
dc.typeJournal articleen_US
dc.description.versionpublishedVersionen_US
dc.rights.holder© The Author(s) 2021en_US
dc.source.journalNeuroradiologyen_US
dc.identifier.doi10.1007/s00234-020-02613-7
dc.identifier.cristin1868117
dc.relation.projectNorges forskningsråd: 249795en_US
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode1


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