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. 2021 Apr 9;63(11):1831–1851. doi: 10.1007/s00234-021-02703-0

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© The Author(s) 2021

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

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Fig. 7 — Qualitative T1-T2-analysis based on manual ROI annotations together with additional explorative parameter-driven tumor subclassification for two representative patient cases. Classification of necrotic/non-enhancing tissue voxels based on quantitative T1 and T2 values can give more insights into the heterogenous structure, which we attribute to fluidic (necrotic/non-enhancing tumor core II, magenta) and solid (necrotic/non-enhancing tumor core I, red) components, within the gross tumor regions (right). Expected spatial correlations of the two subcomponents are maintained as the back-projection of the T1-T2-based classification of necrotic and solid tissue results in connected annotations (left)