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Multiparametrical diffusion weighted imaging for the detection of anaplastic transformation of low-grade gliomas


The precise detection of anaplastic transformation in low-grade gliomas using magnetic resonance imaging (MRI) is impeded by postoperative changes in brain tissue. We tested the diagnostic value of diffusion tensor-derived axial diffusivity (AD), mean diffusivity (MD) (=apparent diffusion coefficient) and radial diffusivity (RD) maps in comparison to T1w and T2w sequences.


The study was approved by the local ethics committee. Forty-seven patients with histopathologically proven low-grade glioma II° were included, 28 were stable and 19 patients had post-surgical anaplastic transformation. All patients underwent pre-operative MRI, surgery and subsequent post-operative MRI follow-ups at 1.5T including T1w, T2w sequences and a DTI-protocol. The scalar indices AD, MD and RD were calculated voxel-by- voxel for all patients from the tensor eigenvalues and the minimum value within a gross tumour segmentation was extracted using MITK-Diffusion, respectively.


Hypointense clusters were seen in every patient with anaplastic transformation in the DTI maps with best contrast-to-noise in AD. In 65% of patients with anaplastic transformation, these clusters were noticed at the same time when compared to contrast enhancement. In 35% of patients, hypointense changes were visible in AD maps in examinations prior to the initial contrast enhancement. ADmin showed best combined sensitivity/specificity (94.4%/89.7%, AUC 0.96) to indicate transformation.


AD maps provide additional essential information for anaplastic transformation of low-grade gliomas after resection and indicate the progress at the same time or earlier when compared to T1w-CE. We conclude that it is advisable to use a DTI-protocol instead of standard diffusion-weighted imaging for neuro-oncological exams.

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Correspondence to MT Freitag.

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This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver ( applies to the data made available in this article, unless otherwise stated.

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Freitag, M., Weber, C., Maier-Hein, K. et al. Multiparametrical diffusion weighted imaging for the detection of anaplastic transformation of low-grade gliomas. cancer imaging 14 (Suppl 1), S11 (2014).

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