Radiomics reproducibility in computed tomography through changes of ROI size, resolution, and hounsfield unit: A phantom study

Abstract

IntroductionAlthough radiomics has revealed an intriguing perspective for quantitative radiology, the impact of scanning parameters on its outcomes must be considered. In this study, the effects of changes in the region of interest (ROI) sizes, Hounsfield Unit (HU), and resolution of computed tomography (CT) on feature reproducibility have been investigated. MethodsThe GAMMEX 464 phantom was used to evaluate the reproducibility of radiomics features across different ROI sizes, HU, and resolution. Data were acquired using a consistent system setup, with the phantom repositioned for each scan. The first acquisition series examined the effects of different ROI sizes and resolutions (1, 3, and 5 mm) on feature reproducibility. The second series assessed the impact of different HU and resolution. Segmentation and feature extraction were performed using LIFEx 7.1.0 software, focusing on textural radiomics features. Statistical analysis involved calculating the coefficient of variation (COV) to categorize feature variability. COV <5 % was considered highly stable. ResultsOut of the 32 textural features studied, the analysis of changes in ROI size with a resolution of 1 mm, 3 mm, and 5 mm revealed that 16, 17, and 18 features had high reproducibility, with a COV<5 %. Polyethylene, acrylic, and water also demonstrated stable textural features across changes in scan parameters and image resolutions, with 4 reproducible features in all resolutions. The grey-level run length matrix (GLRLM) and grey-level zone length matrix (GLZLM) radiomics groups were highly stable in the context of variations in scan parameters and different materials. ConclusionThe results of this study highlight the importance of standardizing radiomics studies to reduce the influence of pre-analysis steps on feature values. This standardization is crucial for guaranteeing the consistency of radiomics features under various imaging conditions. Additional research is required to enhance these results. Implications for practiceTo ensure the reproducibility and reliability of radiomics features, it is imperative to standardize scanning parameters and pre-analysis protocols. This standardization will enhance the consistency of radiomics applications in both clinical and research environments.