Investigating the value of radiomics stemming from DSC quantitative biomarkers in IDH mutation prediction in gliomas

Journal article


Ioannidis, G, Pigott, L.E., Iv, M, Surlan-Popovic, K, Wintermark, M, Bisdas, S and Marias, K (2023). Investigating the value of radiomics stemming from DSC quantitative biomarkers in IDH mutation prediction in gliomas. Frontiers in Neurology. https://doi.org/10.3389/fneur.2023.1249452
AuthorsIoannidis, G, Pigott, L.E., Iv, M, Surlan-Popovic, K, Wintermark, M, Bisdas, S and Marias, K
Abstract

Objective: This study aims to assess the value of biomarker based radiomics to predict IDH mutation in gliomas. The patient cohort consists of 160 patients histopathologicaly proven of primary glioma (WHO grades 2–4) from 3 different centers.

Methods: To quantify the DSC perfusion signal two different mathematical modeling methods were used (Gamma fitting, leakage correction algorithms) considering the assumptions about the compartments contributing in the blood flow between the extra- and intra vascular space.

Results: The Mean slope of increase (MSI) and the K1 parameter of the bidirectional exchange model exhibited the highest performance with (ACC 74.3% AUROC 74.2%) and (ACC 75% AUROC 70.5%) respectively.

Conclusion: The proposed framework on DSC-MRI radiogenomics in gliomas has the potential of becoming a reliable diagnostic support tool exploiting the mathematical modeling of the DSC signal to characterize IDH mutation status through a more reproducible and standardized signal analysis scheme for facilitating clinical translation.

KeywordsIDH, Glioma, Machine Learning, Artificial Intelligence, Cancer, Imaging Biomarkers
Year2023
JournalFrontiers in Neurology
PublisherFrontiers Media
ISSN1664-2295
Digital Object Identifier (DOI)https://doi.org/10.3389/fneur.2023.1249452
Web address (URL)https://www.frontiersin.org/articles/10.3389/fneur.2023.1249452/full
Publication dates
Print16 Nov 2023
Publication process dates
Accepted23 Oct 2023
Deposited21 Nov 2023
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Open
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