gms | German Medical Science

68th Annual Meeting of the German Society of Neurosurgery (DGNC)
7th Joint Meeting with the British Neurosurgical Society (SBNS)

German Society of Neurosurgery (DGNC)

14 - 17 May 2017, Magdeburg

Diffusion-Weighted Imaging Based Probabilistic Quantification of Residual Tumor on Early Postoperative MRI in Low-Grade Glioma

Meeting Abstract

  • Moritz Scherer - Heidelberg University Hospital, Heidelberg, Deutschland
  • Michael Götz - Heidelberg, Deutschland
  • Christine Jungk - Division of Experimental Neurosurgery, Department of Neurosurgery, University Hospital Heidelberg, Heidelberg, Deutschland
  • Klaus Maier-Hein - Heidelberg, Deutschland
  • Andreas Unterberg - Universitätsklinikum Heidelberg, Klinik für Neurochirurgie, Neurochirurgie, Heidelberg, Deutschland

Deutsche Gesellschaft für Neurochirurgie. Society of British Neurological Surgeons. 68. Jahrestagung der Deutschen Gesellschaft für Neurochirurgie (DGNC), 7. Joint Meeting mit der Society of British Neurological Surgeons (SBNS). Magdeburg, 14.-17.05.2017. Düsseldorf: German Medical Science GMS Publishing House; 2017. DocMi.14.04

doi: 10.3205/17dgnc457, urn:nbn:de:0183-17dgnc4570

Published: June 9, 2017

© 2017 Scherer et al.
This is an Open Access article distributed under the terms of the Creative Commons Attribution 4.0 License. See license information at



Objective: In low-grade gliomas (LGG), early postoperative MRI (epMRI) has been shown to frequently over-estimate the amount of residual tumor on fluid-attenuated inversion recovery (FLAIR) sequences. Therefore, residual tumor is usually defined according to follow-up MRI 3 months after surgery (fuMRI). This study sought to evaluate if integration of apparent diffusion coefficient (ADC)-maps permits an accurate estimation of residual tumor also on epMRI.

Methods: Since 2004, 28 consecutive cases with primary surgery for WHO°II astrocytomas and complete epMRI and fuMRI including ADC-maps were retrospectively identified. To account for imaging confounders, histology was adjusted and cases with previous radiation therapy were excluded. Residual FLAIR hyperintense tumor was manually segmented on epMRI. After co-registration with corresponding ADC-maps, residual tumor segments were probabilistically clustered into areas of either low-ADC (edema, ischemia), high-ADC (residual tumor) or partial volume. Clustering was based on an expectation maximization (EM) algorithm fitting a mixture model of three respective Gaussians to the normalized ADC histogram. EpMRI residual tumor and results from ADC-clustering were compared with respective residual tumor on fuMRI.

Results: Median residual FLAIR tumor was significantly greater on epMRI compared to intMRI (17.0ccm, range 1.6-122.7ccm vs. 1.8ccm, range 0-168.0ccm, p<0.001). ADC-clustering of epMRI subclassified FLAIR-hyperintense segments into proportions of: 27±23% residual tumor (median volume 1.7ccm, range 0.2-79.2ccm), 45±20% ischemia (6.2ccm, range 0.4-47.2ccm) and 28±20% partial volume (2.9ccm, range 0.2-64.9ccm). After ADC-clustering, the amount of residual tumor on epMRI was comparable to fuMRI (p=0.45) and showed significant correlation (Spearman r=0.65, p<0.0001). The amount of low-ADC clusters on epMRI suggestive for surgical trauma strongly correlated with the difference in FLAIR-hyperintensity between epMRI and fuMRI (Spearman r=0.86, p<0.0001).

Conclusion: With additional information conveyed in ADC-maps, an accurate quantification of residual tumor could already be achieved on epMRI in this series of low-grade astrocytomas. Probabilistic segmentation of ADC-maps helped to reassess the amount of residual tumor under suppression of signal alterations caused by surgical trauma which was the driving force for bias on epMRI. Reliability of ADC-clustering results based on the proportional partial volume has to be evaluated in the future. Larger case-series are needed to evaluate the prognostic impact of ADC-clustering in LGG.