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The stability of imaging biomarkers in radiomics: a framework for evaluation

Wang, Helen Yu Chi, Donovan, Ellen M, Nisbet, Andrew, South, Christopher P, Alobaidli, Sheaka, Ezhil, Veni, Phillips, Iain, Prakash, Vineet, Ferreira, Mark, Webster, Philip and Evans, Philip M (2019) The stability of imaging biomarkers in radiomics: a framework for evaluation Physics in Medicine and Biology, 64 (16), 165012. pp. 1-12.

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Abstract

This paper studies the sensitivity of a range of image texture parameters used in radiomics to: i) the number of intensity levels, ii) the method of quantisation to select the intensity levels and iii) the use of an intensity threshold. 43 commonly used texture features were studied for the gross target volume outlined on the CT component of PET/CT scans of 50 patients with non-small cell lung carcinoma (NSCLC). All cases were quantised for all values between 4 and 128 intensity levels using four commonly used quantisation methods. All results were analysed with and without a threshold range of -200 HU to 300 HU. Cases were ranked for each texture feature and for all quantisation methods with the Spearman's rank correlation coefficient determined to evaluate stability. Results showed large fluctuations in ranking, particularly for low numbers of levels, differences between quantisation methods and with the use of a threshold, with values Spearman's Rank Correlation for many parameters below 0.2. Our results demonstrated the sensitivity of radiomics features to the parameters used during analysis and highlight the risk of low reproducibility comparing studies with slightly different parameters. In terms of the lung cancer CT datasets, this study supports the use of 128 intensity levels, the same uniform quantiser applied to all scans and thresholding of the data. It also supports several of the features recommended in the literature for such studies such as skewness and kurtosis. A recommended framework is presented for curation of the data analysis process to ensure stability of results.

Item Type: Article
Divisions : Faculty of Engineering and Physical Sciences > Electronic Engineering
Authors :
NameEmailORCID
Wang, Helen Yu Chih.y.wang@surrey.ac.uk
Donovan, Ellen Me.donovan@surrey.ac.uk
Nisbet, AndrewA.Nisbet@surrey.ac.uk
South, Christopher P
Alobaidli, Sheaka
Ezhil, Veni
Phillips, Iaini.phillips@surrey.ac.uk
Prakash, Vineet
Ferreira, Mark
Webster, Philip
Evans, Philip Mp.evans@surrey.ac.uk
Date : 21 August 2019
DOI : 10.1088/1361-6560/ab23a7
Copyright Disclaimer : © 2018 Institute of Physics and Engineering in Medicine. As the Version of Record of this article is going to be/has been published on a subscription basis, this Accepted Manuscript will be available for reuse under a CC BY-NC-ND 3.0 licence after a 12 month embargo period. Although reasonable endeavours have been taken to obtain all necessary permissions from third parties to include their copyrighted content within this article, their full citation and copyright line may not be present in this Accepted Manuscript version. Before using any content from this article, please refer to the Version of Record on IOPscience once published for full citation and copyright details, as permission may be required. All third party content is fully copyright protected, unless specifically stated otherwise in the figure caption of the Version of Record.
Uncontrolled Keywords : Radiomics; Texture analysis; Lung cancer; CT imaging
Related URLs :
Depositing User : Clive Harris
Date Deposited : 17 Jun 2019 10:52
Last Modified : 29 Aug 2019 07:58
URI: http://epubs.surrey.ac.uk/id/eprint/852007

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