Cardiff University | Prifysgol Caerdydd ORCA
Online Research @ Cardiff 
WelshClear Cookie - decide language by browser settings

Assessing radiomic feature robustness to interpolation in 18F-FDG PET imaging

Whybra, Philip, Parkinson, Craig ORCID:, Foley, Kieran, Staffurth, John ORCID: and Spezi, Emiliano ORCID: 2019. Assessing radiomic feature robustness to interpolation in 18F-FDG PET imaging. Scientific Reports 9 (1) , 9649. 10.1038/s41598-019-46030-0

[thumbnail of s41598-019-46030-0.pdf] PDF - Published Version
Available under License Creative Commons Attribution.

Download (2MB)


Radiomic studies link quantitative imaging features to patient outcomes in an effort to personalise treatment in oncology. To be clinically useful, a radiomic feature must be robust to image processing steps, which has made robustness testing a necessity for many technical aspects of feature extraction. We assessed the stability of radiomic features to interpolation processing and categorised features based on stable, systematic, or unstable responses. Here, 18F-fluorodeoxyglucose (18F-FDG) PET images for 441 oesophageal cancer patients (split: testing = 353, validation = 88) were resampled to 6 isotropic voxel sizes (1.5 mm, 1.8 mm, 2.0 mm, 2.2 mm, 2.5 mm, 2.7 mm) and 141 features were extracted from each volume of interest (VOI). Features were categorised into four groups with two statistical tests. Feature reliability was analysed using an intraclass correlation coefficient (ICC) and patient ranking consistency was assessed using a Spearman’s rank correlation coefficient (ρ). We categorised 93 features robust and 6 limited robustness (stable responses), 34 potentially correctable (systematic responses), and 8 not robust (unstable responses). We developed a correction technique for features with potential systematic variation that used surface fits to link voxel size and percentage change in feature value. Twenty-nine potentially correctable features were re-categorised to robust for the validation dataset, after applying corrections defined by surface fits generated on the testing dataset. Furthermore, we found the choice of interpolation algorithm alone (spline vs trilinear) resulted in large variation in values for a number of features but the response categorisations remained constant. This study attempted to quantify the diverse response of radiomics features commonly found in 18F-FDG PET clinical modelling to isotropic voxel size interpolation.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Medicine
Additional Information: This work is licensed under a Creative Commons Attribution 4.0 International License.
Publisher: Nature Publishing Group
ISSN: 2045-2322
Funders: EPSRC
Date of First Compliant Deposit: 25 July 2019
Date of Acceptance: 17 June 2019
Last Modified: 24 Mar 2024 15:02

Citation Data

Cited 48 times in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item Edit Item


Downloads per month over past year

View more statistics