Published August 1, 2019 | Version v1
Journal article

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

  • 1. Centre for Vision, Speech and Signal Processing, University of Surrey, Guildford GU2 7XH (United Kingdom)
  • 2. Department of Medical Physics, Royal Surrey County Hospital NHS Foundation Trust, Guildford GU2 7XX (United Kingdom)
  • 3. Department of Oncology, Royal Surrey County Hospital NHS Foundation Trust, Guildford GU2 7XX (United Kingdom)
  • 4. Alliance Medical Group, London SW1Y 6DN (United Kingdom)

Description

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. (paper)

Availability note (English)

Available from http://dx.doi.org/10.1088/1361-6560/ab23a7

Additional details

Identifiers

Publishing Information

Journal Title
Physics in Medicine and Biology
Journal Volume
64
Journal Issue
16
Journal Page Range
[12 p.]
ISSN
0031-9155
CODEN
PHMBA7

INIS

Country of Publication
United Kingdom
Country of Input or Organization
International Atomic Energy Agency (IAEA)
INIS RN
52003994
Subject category
S62: RADIOLOGY AND NUCLEAR MEDICINE;
Descriptors DEI
BIOLOGICAL MARKERS; DATA ANALYSIS; NEOPLASMS; POSITRON COMPUTED TOMOGRAPHY; QUANTIZATION; RADIOSENSITIVITY; TEXTURE
Descriptors DEC
COMPUTERIZED TOMOGRAPHY; DATA PROCESSING; DIAGNOSTIC TECHNIQUES; DISEASES; EMISSION COMPUTED TOMOGRAPHY; PROCESSING; SENSITIVITY; TOMOGRAPHY