18 August 2022 Repeatability and reproducibility of magnetic resonance imaging-based radiomic features in rectal cancer
Robba Rai, Michael B. Barton, Phillip Chlap, Gary Liney, Carsten Brink, Shalini Vinod, Monique Heinke, Yuvnik Trada, Lois C. Holloway
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Abstract

Purpose: Radiomics of magnetic resonance images (MRIs) in rectal cancer can non-invasively characterize tumor heterogeneity with potential to discover new imaging biomarkers. However, for radiomics to be reliable, the imaging features measured must be stable and reproducible. The aim of this study is to quantify the repeatability and reproducibility of MRI-based radiomic features in rectal cancer.

Approach: An MRI radiomics phantom was used to measure the longitudinal repeatability of radiomic features and the impact of post-processing changes related to image resolution and noise. Repeatability measurements in rectal cancers were also quantified in a cohort of 10 patients with test–retest imaging among two observers.

Results: We found that many radiomic features, particularly from texture classes, were highly sensitive to changes in image resolution and noise. About 49% of features had coefficient of variations ≤10 % in longitudinal phantom measurements. About 75% of radiomic features in in vivo test–retest measurements had an intraclass correlation coefficient of ≥0.8. We saw excellent interobserver agreement with mean Dice similarity coefficient of 0.95 ± 0.04 for test and retest scans.

Conclusions: The results of this study show that even when using a consistent imaging protocol many radiomic features were unstable. Therefore, caution must be taken when selecting features for potential imaging biomarkers.

© 2022 Society of Photo-Optical Instrumentation Engineers (SPIE)
Robba Rai, Michael B. Barton, Phillip Chlap, Gary Liney, Carsten Brink, Shalini Vinod, Monique Heinke, Yuvnik Trada, and Lois C. Holloway "Repeatability and reproducibility of magnetic resonance imaging-based radiomic features in rectal cancer," Journal of Medical Imaging 9(4), 044005 (18 August 2022). https://doi.org/10.1117/1.JMI.9.4.044005
Received: 4 February 2022; Accepted: 9 August 2022; Published: 18 August 2022
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KEYWORDS
Magnetic resonance imaging

Cancer

Tumors

Magnetism

Signal to noise ratio

Image quality

Image resolution

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