Test-Retest Reproducibility and Robustness Analysis of Recurrent Glioblastoma MRI Radiomics Texture Features

Isaac Shiri; Hamid Abdollahi; Sajad Shaysteh; Seied Rabi Mahdavi

doi:10.5812/iranjradiol.48035

Test-Retest Reproducibility and Robustness Analysis of Recurrent Glioblastoma MRI Radiomics Texture Features

Isaac Shiri ^{1
, *} , Hamid Abdollahi ² , Sajad Shaysteh ² and Seied Rabi Mahdavi ¹

Authors Information

¹ Department of Medical Physics, Iran University of Medical science, Tehran, Iran

² Iran University of Medical Science, Tehran, Iran

Article information

Iranian Journal of Radiology: 14 (Special Issue); e48035
Published Online: April 12, 2017
Article Type: Abstract
Received: December 20, 2016
Accepted: February 7, 2017
DOI: 10.5812/iranjradiol.48035

To Cite: Shiri I, Abdollahi H, Shaysteh S, Rabi Mahdavi S. Test-Retest Reproducibility and Robustness Analysis of Recurrent Glioblastoma MRI Radiomics Texture Features, Iran J Radiol. Online ahead of Print ; 14(Special Issue):e48035. doi: 10.5812/iranjradiol.48035.

Abstract

Background: Advanced quantitative information such as radiomics features derived from magnetic resonance (MR) image may be useful for outcome prediction, prognostic models or response biomarkers in Glioblastoma (GBM), knowledge about their Reproducibility and robustness is essential. The purpose of this study was to investigate the reproducible and non-redundant radiomics texture features in oncological GBM MRI based on test-retest setup.

Methods: Thirteen patients with recurrent GBM who underwent repeated MR imaging approximately two day interval were subjected to this study. Lesions were segmented using competitive region-growing based algorithm. Following delineation and segmentation of lesions, 158 quantitative 3D features based on intensity histograms (IH), gray level run-length (GLRLM), gray level co-occurrence (GLCM), gray level size-zone texture matrices (GLSZM), neighborhood-difference matrices (NDM), and geometric features were extracted from the 3D-tumor volumes of each lesion. For every radiomics feature, test-retest was assessed with the intra-class correlation coefficient (ICC) and the concordance correlation coefficient (CCC) and finally the most reproducible and robust radiomics features were selected.

© 2017, Author(s). This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/) which permits copy and redistribute the material just in noncommercial usages, provided the original work is properly cited.

Iranian Journal of Radiology

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Test-Retest Reproducibility and Robustness Analysis of Recurrent Glioblastoma MRI Radiomics Texture Features

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Iranian Journal of Radiology

Published by: Kowsar

Test-Retest Reproducibility and Robustness Analysis of Recurrent Glioblastoma MRI Radiomics Texture Features

Article information

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