Myocardial radiomics texture features associated with increased coronary calcium score: first results of a photon-counting CT

The coronary artery calcium score is an independent risk factor of the development of adverse cardiac events. The severity of coronary artery calcification may influence the myocardial texture. Due to higher spatial resolution and signal-to-noise ratio, new CT technologies such as PCCT may improve t...

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Main Authors: Ayx, Isabelle (Author) , Tharmaseelan, Hishan (Author) , Hertel, Alexander (Author) , Nörenberg, Dominik (Author) , Overhoff, Daniel (Author) , Rotkopf, Lukas Thomas (Author) , Riffel, Philipp (Author) , Schönberg, Stefan (Author) , Froelich, Matthias F. (Author)
Format: Article (Journal)
Language:English
Published: 8 July 2022
In: Diagnostics
Year: 2022, Volume: 12, Issue: 7, Pages: 1-10
ISSN:2075-4418
DOI:10.3390/diagnostics12071663
Online Access:Verlag, kostenfrei, Volltext: https://doi.org/10.3390/diagnostics12071663
Verlag, kostenfrei, Volltext: https://www.mdpi.com/2075-4418/12/7/1663
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Author Notes:Isabelle Ayx, Hishan Tharmaseelan, Alexander Hertel, Dominik Nörenberg, Daniel Overhoff, Lukas T. Rotkopf, Philipp Riffel, Stefan O. Schoenberg and Matthias F. Froelich
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Summary:The coronary artery calcium score is an independent risk factor of the development of adverse cardiac events. The severity of coronary artery calcification may influence the myocardial texture. Due to higher spatial resolution and signal-to-noise ratio, new CT technologies such as PCCT may improve the detection of texture alterations depending on the severity of coronary artery calcification. In this retrospective, single-center, IRB-approved study, left ventricular myocardium was segmented and radiomics features were extracted using pyradiomics. The mean and standard deviation with the Pearson correlation coefficient for correlations of features were calculated and visualized as boxplots and heatmaps. Random forest feature selection was performed. Thirty patients (26.7% women, median age 58 years) were enrolled in the study. Patients were divided into two subgroups depending on the severity of coronary artery calcification (Agatston score 0 and Agatston score ≥ 100). Through random forest feature selection, a set of four higher-order features could be defined to discriminate myocardial texture between the two groups. When including the additional Agatston 1-99 groups as a validation, a severity-associated change in feature intensity was detected. A subset of radiomics features texture alterations of the left ventricular myocardium was associated with the severity of coronary artery calcification estimated by the Agatston score.
Item Description:Dieser Artikel gehört zum Special issue: Noninvasive diagnosis of cardiac tumors
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Physical Description:Online Resource
ISSN:2075-4418
DOI:10.3390/diagnostics12071663