Multiparametric MRI texture analysis in prediction of glioma biomarker status: added value of MR diffusion.
Publication/Presentation Date
1-1-2021
Abstract
BACKGROUND: Early identification of glioma molecular phenotypes can lead to understanding of patient prognosis and treatment guidance. We aimed to develop a multiparametric MRI texture analysis model using a combination of conventional and diffusion MRI to predict a wide range of biomarkers in patients with glioma.
METHODS: In this retrospective study, patients were included if they (1) had diagnosis of gliomas with known
RESULTS: From a total of 111 patients included, 91 (82%) were categorized to training and 20 (18%) to test datasets. Constructed cross-validated model using a combination of texture features from conventional and diffusion MRI resulted in overall AUC/accuracy of 1/79% for
CONCLUSION: Addition of MR diffusion to conventional MRI features provides added diagnostic value in preoperative determination of IDH1, MGMT, and ATRX in patients with glioma.
Volume
3
Issue
1
First Page
051
Last Page
051
ISSN
2632-2498
Published In/Presented At
Kihira, S., Tsankova, N. M., Bauer, A., Sakai, Y., Mahmoudi, K., Zubizarreta, N., Houldsworth, J., Khan, F., Salamon, N., Hormigo, A., & Nael, K. (2021). Multiparametric MRI texture analysis in prediction of glioma biomarker status: added value of MR diffusion. Neuro-oncology advances, 3(1), vdab051. https://doi.org/10.1093/noajnl/vdab051
Disciplines
Medicine and Health Sciences
PubMedID
34056604
Department(s)
Department of Pathology and Laboratory Medicine
Document Type
Article