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Tomography
Volume 2
Issue 4
10.18383/j.tom.2016.00208
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Article

Test–Retest Data for Radiomics Feature Stability Analysis: Generalizable or Study-Specific?

by
Janna E. van Timmeren
1,*,
Ralph T.H. Leijenaar
1,
Wouter van Elmpt
1,
Jiazhou Wang
2,3,
Zhen Zhang
2,3,
André Dekker
1 and
Philippe Lambin
1
1
Department of Radiation Oncology (MAASTRO), GROW-School for Oncology and Developmental Biology, Maastricht University Medical Centre (MUMC), Maastricht, The Netherlands
2
Department of Radiation Oncology, Fudan University Shanghai Cancer Center, China
3
Department of Oncology, Shanghai Medical College, Fudan University, China
*
Author to whom correspondence should be addressed.
Tomography 2016, 2(4), 361-365; https://doi.org/10.18383/j.tom.2016.00208
Submission received: 3 September 2016 / Revised: 4 October 2016 / Accepted: 3 November 2016 / Published: 1 December 2016
Versions Notes

Abstract

Radiomics is an objective method for extracting quantitative information from medical images. However, in radiomics, standardization, overfitting, and generalization are major challenges to be overcome. Test–retest experiments can be used to select robust radiomic features that have minimal variation. Currently, it is unknown whether they should be identified for each disease (disease specific) or are only imaging device-specific (computed tomography [CT]-specific). Here, we performed a test–retest analysis on CT scans of 40 patients with rectal cancer in a clinical setting. Correlation between radiomic features was assessed using the concordance correlation coefficient (CCC). In total, only 9/542 features have a CCC > 0.85. Furthermore, results were compared with the test–retest results on CT scans of 27 patients with lung cancer with a 15-minute interval. Results show that 446/542 features have a higher CCC for the test–retest analysis of the data set of patients with lung cancer than for patients with rectal cancer. The importance of controlling factors such as scanners, imaging protocol, reconstruction methods, and time points in a radiomics analysis is shown. Moreover, the results imply that test–retest analyses should be performed before each radiomics study. More research is required to independently evaluate the effect of each factor.
Keywords: radiomics; test–retest; computed tomography radiomics; test–retest; computed tomography

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MDPI and ACS Style

van Timmeren, J.E.; Leijenaar, R.T.H.; van Elmpt, W.; Wang, J.; Zhang, Z.; Dekker, A.; Lambin, P. Test–Retest Data for Radiomics Feature Stability Analysis: Generalizable or Study-Specific? Tomography 2016, 2, 361-365. https://doi.org/10.18383/j.tom.2016.00208

AMA Style

van Timmeren JE, Leijenaar RTH, van Elmpt W, Wang J, Zhang Z, Dekker A, Lambin P. Test–Retest Data for Radiomics Feature Stability Analysis: Generalizable or Study-Specific? Tomography. 2016; 2(4):361-365. https://doi.org/10.18383/j.tom.2016.00208

Chicago/Turabian Style

van Timmeren, Janna E., Ralph T.H. Leijenaar, Wouter van Elmpt, Jiazhou Wang, Zhen Zhang, André Dekker, and Philippe Lambin. 2016. "Test–Retest Data for Radiomics Feature Stability Analysis: Generalizable or Study-Specific?" Tomography 2, no. 4: 361-365. https://doi.org/10.18383/j.tom.2016.00208

APA Style

van Timmeren, J. E., Leijenaar, R. T. H., van Elmpt, W., Wang, J., Zhang, Z., Dekker, A., & Lambin, P. (2016). Test–Retest Data for Radiomics Feature Stability Analysis: Generalizable or Study-Specific? Tomography, 2(4), 361-365. https://doi.org/10.18383/j.tom.2016.00208

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