Research Paper Volume 11, Issue 2 pp 673—696
IDH mutation-specific radiomic signature in lower-grade gliomas
- 1 Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
- 2 Neurological Imaging Center, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
- 3 Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- 4 Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing, China
- 5 Department of Nuclear Medicine, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- 6 Center of Brain Tumor, Beijing Institute for Brain Disorders, Beijing, China
- 7 China National Clinical Research Center for Neurological Diseases, Beijing, China
- 8 Chinese Glioma Genome Atlas Network (CGGA) and Asian Glioma Genome Atlas Network (AGGA)
- 9 National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China
received: November 12, 2018 ; accepted: January 6, 2019 ; published: January 29, 2019 ;https://doi.org/10.18632/aging.101769
How to Cite
Copyright: Liu et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Unravelling the heterogeneity is the central challenge for glioma precession oncology. In this study, we extracted quantitative image features from T2-weighted MR images and revealed that the isocitrate dehydrogenase (IDH) wild type and mutant lower grade gliomas (LGGs) differed in their expression of 146 radiomic descriptors. The logistic regression model algorithm further reduced these to 86 features. The classification model could discriminate the two types in both the training and validation sets with area under the curve values of 1.0000 and 0.9932, respectively. The transcriptome-radiomic analysis revealed that these features were associated with the immune response, biological adhesion, and several malignant behaviors, all of which are consistent with biological processes that are differentially expressed in IDH wild type and IDH mutant LGGs. Finally, a prognostic signature showed an ability to stratify IDH mutant LGGs into high and low risk groups with distinctive outcomes. By extracting a large number of radiomic features, we identified an IDH mutation-specific radiomic signature with prognostic implications. This radiomic signature may provide a way to non-invasively discriminate lower-grade gliomas as with or without the IDH mutation.