Radiomics prognostication model in glioblastoma using diffusion- and perfusion-weighted MRI.

Scientific Reports
Ji Eun ParkJeong Hoon Kim

Abstract

We aimed to develop and validate a multiparametric MR radiomics model using conventional, diffusion-, and perfusion-weighted MR imaging for better prognostication in patients with newly diagnosed glioblastoma. A total of 216 patients with newly diagnosed glioblastoma were enrolled from two tertiary medical centers and divided into training (n = 158) and external validation sets (n = 58). Radiomic features were extracted from contrast-enhanced T1-weighted imaging, fluid-attenuated inversion recovery, diffusion-weighted imaging, and dynamic susceptibility contrast imaging. After radiomic feature selection using LASSO regression, an individualized radiomic score was calculated. A multiparametric MR prognostic model was built using the radiomic score and clinical predictors. The results showed that the multiparametric MR prognostic model (radiomics score + clinical predictors) exhibited good discrimination (C-index, 0.74) and performed better than a conventional MR radiomics model (C-index, 0.65, P < 0.0001) or clinical predictors (C-index, 0.66; P < 0.0001). The multiparametric MR prognostic model also showed robustness in external validation (C-index, 0.70). Our results indicate that the incorporation of diffusion- and perfusion-...Continue Reading

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Citations

Feb 19, 2021·Scientific Reports·Joonsang LeeLaurence E Court
Mar 26, 2021·Frontiers in Oncology·Danilo MazieroEric A Mellon
Jun 1, 2021·Frontiers in Neurology·Ching-Chung KoMin-Ying Su
Jul 17, 2021·Korean Journal of Radiology : Official Journal of the Korean Radiological Society·Seo Young ParkSeong Ho Park
Jul 17, 2021·Korean Journal of Radiology : Official Journal of the Korean Radiological Society·Elena PakChul-Ho Sohn
Oct 2, 2021·Neuroradiology·Siddhartha GaddamanuguAparna Singhal

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Methods Mentioned

BETA
feature extraction

Software Mentioned

ANTsR
LASSO
SPM
NordicICE
R Foundation for
Matlab
WhiteStripe
MITK
CompareC
R

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