CONFERENCE PROCEEDINGS
Advanced Search
Home > Proceedings > Volume 12930 > Article
Paper
2 April 2024 Predicting glioma IDH mutation using multiparametric MRI and fractal analysis
Brandon Qi, Jinyi Qi
Author Affiliations +
Proceedings Volume 12930, Medical Imaging 2024: Clinical and Biomedical Imaging; 129301C (2024) https://doi.org/10.1117/12.3006661
Event: SPIE Medical Imaging, 2024, San Diego, California, United States
Abstract
This study aims to investigate the effectiveness of applying fractal analysis to pre-operative MRI images for prediction of glioma IDH mutation status. IDH mutation has been shown to provide more prognostic and therapeutic benefits to patients, so predicting it before surgery can provide useful information for planning the proper treatments. This study utilized the UCSF-PDGM dataset from the Cancer Image Archive. We used the modified box counting method to compute the fractal dimension of segmented tumor regions in pre- and post-contrast T1-weighted MRI. The results showed that the FD provided clear differentiation between tumor grades, with higher FD correlated to higher tumor grade. Additionally, FD demonstrated clear separation between IDH wildtype and IDH mutated tumors. Enhanced differentiation based on FD was observed with post-contrast T1-weighted images. Significant p-values from the Wilcoxon rank sum test validated the potential of using fractal analysis. The AUC of ROC for IDH mutation prediction reached 0.88 for both pre- and post-contrast T1-weighted images. In conclusion, this study shows fractal analysis is a promising technique for glioma IDH mutation prediction. Future work will include studies using more advanced MRI imaging contrasts as well as combination of multi-parametric images.
© (2024) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Citation Download Citation
Brandon Qi and Jinyi Qi "Predicting glioma IDH mutation using multiparametric MRI and fractal analysis", Proc. SPIE 12930, Medical Imaging 2024: Clinical and Biomedical Imaging, 129301C (2 April 2024); https://doi.org/10.1117/12.3006661
ACCESS THE FULL ARTICLE
ORGANIZATIONAL
Sign in with credentials provided by your organization.
INSTITUTIONAL
Select your institution to access the SPIE Digital Library.
SELECT YOUR INSTITUTION
PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.
PERSONAL SIGN IN
No SPIE Account? Create one
PURCHASE THIS CONTENT
SUBSCRIBE TO DIGITAL LIBRARY
50 downloads per 1-year subscription
Members: $195
Non-members: $335 ADD TO CART
25 downloads per 1 - year subscription
Members: $145
Non-members: $250 ADD TO CART
PURCHASE SINGLE ARTICLE
Includes PDF, HTML & Video, when available
Members: $17.00
Non-members: $21.00 ADD TO CART
PROCEEDINGS
 4 PAGES
DOWNLOAD PAPER SAVE TO MY LIBRARY
GET CITATION
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Tumors
Magnetic resonance imaging
Fractal analysis
Brain
Cancer
Genetics
Radiomics
RELATED CONTENT
Subscribe to Digital Library
Receive Erratum Email Alert
Back to Top