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

Details

Serval ID
serval:BIB_E1579BACE27A
Type
Article: article from journal or magazin.
Collection
Publications
Title
The Discriminative Power and Stability of Radiomics Features With Computed Tomography Variations: Task-Based Analysis in an Anthropomorphic 3D-Printed CT Phantom.
Journal
Investigative radiology
Author(s)
Jimenez-Del-Toro O., Aberle C., Bach M., Schaer R., Obmann M.M., Flouris K., Konukoglu E., Stieltjes B., Müller H., Depeursinge A.
ISSN
1536-0210 (Electronic)
ISSN-L
0020-9996
Publication state
Published
Issued date
01/12/2021
Peer-reviewed
Oui
Volume
56
Number
12
Pages
820-825
Language
english
Notes
Publication types: Journal Article ; Research Support, Non-U.S. Gov't
Publication Status: ppublish
Abstract
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.
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.
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.
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.
Keywords
Algorithms, Humans, Phantoms, Imaging, Printing, Three-Dimensional, Tomography, X-Ray Computed/methods
Pubmed
Web of science
Create date
31/05/2021 8:29
Last modification date
09/10/2023 16:39
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