TY - GEN
T1 - Integrative radiomic analysis for pre-surgical prognostic stratification of glioblastoma patients
T2 - Medical Imaging 2020: Image-Guided Procedures, Robotic Interventions, and Modeling
AU - Bakas, Spyridon
AU - Shukla, Gaurav
AU - Akbari, Hamed
AU - Erus, Guray
AU - Sotiras, Aristeidis
AU - Rathore, Saima
AU - Sako, Chiharu
AU - Ha, Sung Min
AU - Rozycki, Martin
AU - Singh, Ashish
AU - Shinohara, Russell
AU - Bilello, Michel
AU - Davatzikos, Christos
N1 - Funding Information:
FUNDING: This work was supported by the National Institutes of Health grants R01-NS042645 and U24-CA189523.
Publisher Copyright:
© 2020 SPIE.
PY - 2020
Y1 - 2020
N2 - Glioblastoma, the most common and aggressive adult brain tumor, is considered non-curative at diagnosis. Current literature shows promise on imaging-based overall survival prediction for patients with glioblastoma while integrating advanced (structural, perfusion, and diffusion) multiparametric magnetic resonance imaging (AdvmpMRI). However, most patients prior to initiation of therapy typically undergo only basic structural mpMRI (BasmpMRI, i.e., T1,T1-Gd,T2,T2-FLAIR) pre-operatively, rather than Adv-mpMRI. Here we assess a retrospective cohort of 101 glioblastoma patients with available Adv-mpMRI from a previous study, which has shown that an initial feature panel (IFP) extracted from Adv-mpMRI can yield accurate overall survival stratification. We further focus on demonstrating that equally accurate prediction models can be constructed using augmented feature panels (AFP) extracted solely from Bas-mpMRI, obviating the need for using Adv-mpMRI. The classification accuracy of the model utilizing Adv-mpMRI protocols and the IFP was 72.77%, and improved to 74.26% when utilizing the AFP on Bas-mpMRI. Furthermore, Kaplan-Meier analysis demonstrated superior classification of subjects into short-, intermediate-, and long-survivor classes when using AFP on Basic-mpMRI. This quantitative evaluation indicates that accurate survival prediction in glioblastoma patients is feasible by using solely Bas-mpMRI and integrative radiomic analysis can compensate for the lack of Adv-mpMRI. Our finding holds promise for predicting overall survival based on commonly-acquired Bas-mpMRI, and hence for potential generalization across multiple institutions that may not have access to Adv-mpMRI, facilitating better patient selection.
AB - Glioblastoma, the most common and aggressive adult brain tumor, is considered non-curative at diagnosis. Current literature shows promise on imaging-based overall survival prediction for patients with glioblastoma while integrating advanced (structural, perfusion, and diffusion) multiparametric magnetic resonance imaging (AdvmpMRI). However, most patients prior to initiation of therapy typically undergo only basic structural mpMRI (BasmpMRI, i.e., T1,T1-Gd,T2,T2-FLAIR) pre-operatively, rather than Adv-mpMRI. Here we assess a retrospective cohort of 101 glioblastoma patients with available Adv-mpMRI from a previous study, which has shown that an initial feature panel (IFP) extracted from Adv-mpMRI can yield accurate overall survival stratification. We further focus on demonstrating that equally accurate prediction models can be constructed using augmented feature panels (AFP) extracted solely from Bas-mpMRI, obviating the need for using Adv-mpMRI. The classification accuracy of the model utilizing Adv-mpMRI protocols and the IFP was 72.77%, and improved to 74.26% when utilizing the AFP on Bas-mpMRI. Furthermore, Kaplan-Meier analysis demonstrated superior classification of subjects into short-, intermediate-, and long-survivor classes when using AFP on Basic-mpMRI. This quantitative evaluation indicates that accurate survival prediction in glioblastoma patients is feasible by using solely Bas-mpMRI and integrative radiomic analysis can compensate for the lack of Adv-mpMRI. Our finding holds promise for predicting overall survival based on commonly-acquired Bas-mpMRI, and hence for potential generalization across multiple institutions that may not have access to Adv-mpMRI, facilitating better patient selection.
KW - Glioblastoma
KW - Multivariate
KW - Prediction
KW - Prognosis
KW - Radiomics
KW - Survival
UR - http://www.scopus.com/inward/record.url?scp=85085255692&partnerID=8YFLogxK
U2 - 10.1117/12.2566505
DO - 10.1117/12.2566505
M3 - Conference contribution
C2 - 33746333
AN - SCOPUS:85085255692
T3 - Proceedings of SPIE - The International Society for Optical Engineering
BT - Medical Imaging 2020
A2 - Fei, Baowei
A2 - Linte, Cristian A.
PB - SPIE
Y2 - 16 February 2020 through 19 February 2020
ER -