Oops, you're using an old version of your browser so some of the features on this page may not be displaying properly.

MINIMAL Requirements: Google Chrome 24+Mozilla Firefox 20+Internet Explorer 11Opera 15–18Apple Safari 7SeaMonkey 2.15-2.23

Poster display session: Breast cancer - early stage, locally advanced & metastatic, CNS tumours, Developmental therapeutics, Genitourinary tumours - prostate & non-prostate, Palliative care, Psycho-oncology, Public health policy, Sarcoma, Supportive care

2638 - can diffusion tensor mr imaging identify glioma idh mutation status?

Date

22 Oct 2018

Session

Poster display session: Breast cancer - early stage, locally advanced & metastatic, CNS tumours, Developmental therapeutics, Genitourinary tumours - prostate & non-prostate, Palliative care, Psycho-oncology, Public health policy, Sarcoma, Supportive care

Topics

Staging and Imaging

Tumour Site

Central Nervous System Malignancies

Presenters

Sotirios Bisdas

Citation

Annals of Oncology (2018) 29 (suppl_8): viii122-viii132. 10.1093/annonc/mdy273

Authors

S. Bisdas1, J. Yuan2, L. Mancini2, D. Roettger3

Author affiliations

  • 1 Institute Of Neurology, University College London, NW1 2BU - London/GB
  • 2 Department Of Neuroradiology, University College London Hospitals NHS Trust, NW1 2BU - London/GB
  • 3 R&d, Image Analysis Ltd, SW1V 1BA - London/GB
More

Resources

Abstract 2638

Background

The isocitrate dehydrogenase (IDH) mutation status is a recognized molecular biomarker for glioma stratification. In addition, glioma clinical management benefits from advanced MRI sequences including diffusion tensor imaging (DTI). For first time, we investigated the diagnostic power of DTI to characterize gliomas with respect to IDH mutation status.

Methods

This retrospective study examines the accuracy of DTI for staging of IDH mutant (98) and wild-type (67) gliomas in a treatment-naïve setting. The tumour was manually segmented in the MRI and two DTI-derived parameters, namely fractional anisotropy (FA) and mean diffusivity (MD) values were calculated and plotted as histograms. Thresholds for the optimal diagnostic performance in terms of IDH mutation were sought in selected histogram parameters of FA and MD maps using parametric and non-parametric tests as well as receiver operating characteristic curve analysis.

Results

Significantly higher MD median values and significantly lower FA median values were observed in the IDH mutant compared with the wild-type group. As follows, the median MD value was defined as a robust predictor for IDH mutation status [area under the curve (AUC) = 0.82]. The developed logistic regression model included the top 5 correlating histogram parameters and the patient age. The assessment using the parameter combination reached better performance (AUC=0.85) compared with the prediction using parameter of the median MD value alone.

Conclusions

MR imaging DTI-derived metrics (MD and FA values) in combination with demographic information has the potential to non-invasively predict molecular stratification of gliomas.

Clinical trial identification

Legal entity responsible for the study

University College London.

Funding

Has not received any funding.

Editorial Acknowledgement

Disclosure

D. Roettger: Head of Scientific and Medical Affairs: IAG. All other authors have declared no conflicts of interest.

This site uses cookies. Some of these cookies are essential, while others help us improve your experience by providing insights into how the site is being used.

For more detailed information on the cookies we use, please check our Privacy Policy.

Customise settings
  • Necessary cookies enable core functionality. The website cannot function properly without these cookies, and you can only disable them by changing your browser preferences.