McHugh, DJ;
Porta, N;
Little, RA;
Cheung, S;
Watson, Y;
Parker, GJM;
Jayson, GC;
(2021)
Article image contrast, image pre-processing, and T₁ mapping affect MRI radiomic feature repeatability in patients with colorectal cancer liver metastases.
Cancers
, 13
(2)
, Article 240. 10.3390/cancers13020240.
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Mchugh et al. - 2021 - Image Contrast , Image Pre-Processing , and T 1 Mapping Affect Cancer Liver Metastases.pdf - Published Version Download (42MB) | Preview |
Abstract
Imaging biomarkers require technical, biological, and clinical validation to be translated into robust tools in research or clinical settings. This study contributes to the technical validation of radiomic features from magnetic resonance imaging (MRI) by evaluating the repeatability of features from four MR sequences: pre-contrast T_{1}- and T_{2}-weighted images, pre-contrast quantitative T_{1} maps (qT_{1}), and contrast-enhanced T_{1} weighted images. Fifty-one patients with colorectal cancer liver metastases were scanned twice, up to 7 days apart. Repeatability was quantified using the intraclass correlation coefficient (ICC) and repeatability coefficient (RC), and the impact of non-Gaussian feature distributions and image normalisation was evaluated. Most radiomic features had non-Gaussian distributions, but Box–Cox transformations enabled ICCs and RCs to be calculated appropriately for an average of 97% of features across sequences. ICCs ranged from 0.30 to 0.99, with volume and other shape features tending to be most repeatable; volume ICC > 0.98 for all sequences. 19% of features from non-normalised images exhibited significantly different ICCs in pair-wise sequence comparisons. Normalisation tended to increase ICCs for pre-contrast T_{1}- and T_{2}-weighted images, and decrease ICCs for qT_{1} maps. RCs tended to vary more between sequences than ICCs, showing that evaluations of feature performance depend on the chosen metric. This work suggests that feature-specific repeatability, from specific combinations of MR sequence and pre-processing steps, should be evaluated to select robust radiomic features as biomarkers in specific studies. In addition, as different repeatability metrics can provide different insights into a specific feature, consideration of the appropriate metric should be taken in a study-specific context.
| Type: | Article |
|---|---|
| Title: | Article image contrast, image pre-processing, and T₁ mapping affect MRI radiomic feature repeatability in patients with colorectal cancer liver metastases |
| Location: | Switzerland |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.3390/cancers13020240 |
| Publisher version: | https://doi.org/10.3390/cancers13020240 |
| Language: | English |
| Additional information: | © 2021 by the Authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
| Keywords: | MRI, intraclass correlation coefficient, liver metastases, radiomics, repeatability, repeatability coefficient |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Med Phys and Biomedical Eng |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10119331 |
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