The Discriminative Power and Stability of Radiomics Features With Computed Tomography Variations: Task-Based Analysis in an Anthropomorphic 3D-Printed CT Phantom. Issue 12 (December 2021)

• Record Type: Journal Article
• Authors: Jimenez-del-Toro, Oscar; Aberle, Christoph; Bach, Michael; Schaer, Roger; Obmann, Markus M.; Flouris, Kyriakos; Konukoglu, Ender; Stieltjes, Bram; Müller, Henning; Depeursinge, Adrien
• Is Part Of: Investigative radiology. Volume 56:Issue 12(2021)
• Publication Date: 2021-12
• Subjects: radiomics -- texture analysis -- anthropomorphic phantom -- computed tomography -- quantitative biomarkers; Diagnosis, Radioscopic -- Periodicals; Radiology, Medical -- Periodicals; 616.0757
• DOI: 10.1097/RLI.0000000000000795
• Languages: English
• ISSNs: 0020-9996

Abstract

Abstract : Objectives: The aims of this study were to determine the stability of radiomics features against computed tomography (CT) parameter variations and to study their discriminative power concerning tissue classification using a 3D-printed CT phantom based on real patient data. Materials and Methods: A radiopaque 3D phantom was developed using real patient data and a potassium iodide solution paper-printing technique. Normal liver tissue and 3 lesion types (benign cyst, hemangioma, and metastasis) were manually annotated in the phantom. The stability and discriminative power of 86 radiomics features were assessed in measurements taken from 240 CT series with 8 parameter variations of reconstruction algorithms, reconstruction kernels, slice thickness, and slice spacing. Pairwise parameter group and pairwise tissue class comparisons were performed using Wilcoxon signed rank tests. Results: In total, 19, 264 feature stability tests and 8256 discriminative power tests were performed. The 8 CT parameter variation pairwise group comparisons had statistically significant differences on average in 78/86 radiomics features. On the other hand, 84% of the univariate radiomics feature tests had a successful and statistically significant differentiation of the 4 classes of liver tissue. The 86 radiomics features were ranked according to the cumulative sum of successful stability and discriminative power tests. Conclusions: The differences in radiomics feature values obtained from different types of liver tissue are generally greater than the intraclass differences resulting from CT parameter variations. Abstract : Supplemental digital content is available in the text.