Document Type
Article
Publication Date
2023
DOI
10.3390/cancers15184636
Publication Title
Cancers
Volume
15
Issue
18
Pages
4636 (1-25)
Abstract
Rapid early progression (REP) has been defined as increased nodular enhancement at the border of the resection cavity, the appearance of new lesions outside the resection cavity, or increased enhancement of the residual disease after surgery and before radiation. Patients with REP have worse survival compared to patients without REP (non-REP). Therefore, a reliable method for differentiating REP from non-REP is hypothesized to assist in personlized treatment planning. A potential approach is to use the radiomics and fractal texture features extracted from brain tumors to characterize morphological and physiological properties. We propose a random sampling-based ensemble classification model. The proposed iterative random sampling of patient data followed by feature selection and classification with radiomics, multi-resolution fractal, and proteomics features predicts REP from non-REP using radiation-planning magnetic resonance imaging (MRI). Our results further show the efficacy of pre-radiation image features in the analysis of survival probability and prognostic grouping of patients.
Rights
© 2023 by the authors.
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution 4.0 International (CC BY 4.0) license.
Data Availability
Article states: "Data may be available subject to appropriate IRB approval."
Original Publication Citation
Farzana, W., Basree, M. M., Diawara, N., Shboul, Z. A., Dubey, S., Lockhart, M. M., Hamza, M., Palmer, J. D., & Iftekharuddin, K. M. (2023). Prediction of rapid early progression and survival risk with pre-radiation MRI in WHO grade 4 glioma patients. Cancers, 15(18), 1-25, Article 4636. https://doi.org/10.3390/cancers15184636
Repository Citation
Farzana, Walia; Basree, Mustafa M.; Diawara, Norou; Shboul, Zeina; Dubey, Sagel; Lockheart, Marie M.; Hamza, Mohamed; Palmer, Joshua D.; and Iftekharuddin, Khan, "Prediction of Rapid Early Progression and Survival Risk with Pre-Radiation MRI in WHO Grade 4 Glioma Patients" (2023). Electrical & Computer Engineering Faculty Publications. 422.
https://digitalcommons.odu.edu/ece_fac_pubs/422
ORCID
0000-0003-1995-2426 (Farzana), 0000-0002-8403-6793 (Diawara), 0000-0002-1277-4041 (Shboul), 0000-0001-8316-4163 (Iftekharuddin)
Included in
Analytical, Diagnostic and Therapeutic Techniques and Equipment Commons, Clinical Trials Commons, Neurology Commons, Radiology Commons