Comparison Study of Myocardial Radiomics Feature Properties on Energy-Integrating and Photon-Counting Detector CT
Authors:
- Isabelle AyxIAIsabelle Ayx
- Hishan TharmaseelanHTHishan Tharmaseelan
- Alexander HertelAHAlexander Hertel
- Dominik NörenbergDNDominik Nörenberg
- Daniel OverhoffDODaniel Overhoff
- Lukas T. RotkopfLRLukas T. Rotkopf
- Philipp RiffelPRPhilipp Riffel
- Stefan O. SchoenbergSSStefan O. Schoenberg
- Matthias F. FroelichMFMatthias F. Froelich
Open Access
- 23 May 2022
- journal article
- research article
- Published by MDPI AG in Diagnostics
- Vol. 12 (5) , 1294
Abstract
The implementation of radiomics-based, quantitative imaging parameters is hampered by a lack of stability and standardization. Photon-counting computed tomography (PCCT), compared to energy-integrating computed tomography (EICT), does rely on a novel detector technology, promising better spatial resolution and contrast-to-noise ratio. However, its effect on radiomics feature properties is unknown. This work investigates this topic in myocardial imaging. In this retrospective, single-center IRB-approved study, the left ventricular myocardium was segmented on CT, and the radiomics features were extracted using pyradiomics. To compare features between scanners, a t-test for non-paired samples and F-test was performed, with a threshold of 0.05 set as a benchmark for significance. Feature correlations were calculated by the Pearson correlation coefficient, and visualization was performed with heatmaps. A total of 50 patients (56% male, mean age 56) were enrolled in this study, with equal proportions of PCCT and EICT. First-order features were, nearly, comparable between both groups. However, higher-order features showed a partially significant difference between PCCT and EICT. While first-order radiomics features of left ventricular myocardium show comparability between PCCT and EICT, detected differences of higher-order features may indicate a possible impact of improved spatial resolution, better detection of lower-energy photons, and a better signal-to-noise ratio on texture analysis on PCCT.Keywords
Funding Information
- Gesundheitsstandort Baden-Württemberg
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