Radiogenomic classification of the 1p/19q status in presumed low-grade gliomas

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4 Citations (Scopus)

Abstract

1p/19q co-deletion is an important prognostic factor in low grade gliomas. However, determination of the 1p/19q status currently requires a biopsy. To overcome this, we investigate a radiogenomic classification using support vector machines to non-invasively predict the 1p/19q status from multimodal MRI data. Different approaches of predicting this status were compared: a direct approach which predicts the 1p/19q co-deletion status and an indirect approach which predicts the mutation status of 1p and 19q individually and combines these predictions to predict the 1p/19q co-deletion status. Using the indirect approach based on both the T1-weighted and T2-weighted images delivered the best result and resulted in a 95% confidence interval for the sensitivity and specificity of [0.44; 0.89] and [0.70; 1.00] respectively.

Original languageEnglish
Title of host publication2017 IEEE 14th International Symposium on Biomedical Imaging, ISBI 2017
PublisherIEEE Computer Society
Pages638-641
Number of pages4
ISBN (Electronic)9781509011711
DOIs
Publication statusPublished - 15 Jun 2017
Event14th IEEE International Symposium on Biomedical Imaging, ISBI 2017 - Melbourne, Australia
Duration: 18 Apr 201721 Apr 2017

Publication series

SeriesProceedings - International Symposium on Biomedical Imaging
ISSN1945-7928

Conference

Conference14th IEEE International Symposium on Biomedical Imaging, ISBI 2017
Country/TerritoryAustralia
CityMelbourne
Period18/04/1721/04/17

Bibliographical note

Publisher Copyright:
© 2017 IEEE.

Research programs

  • EMC NIHES-03-30-03

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