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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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Autores principales: Ayx, Isabelle, Tharmaseelan, Hishan, Hertel, Alexander, Nörenberg, Dominik, Overhoff, Daniel, Rotkopf, Lukas T., Riffel, Philipp, Schoenberg, Stefan O., Froelich, Matthias F.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9320412/
https://www.ncbi.nlm.nih.gov/pubmed/35885567
http://dx.doi.org/10.3390/diagnostics12071663
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author Ayx, Isabelle
Tharmaseelan, Hishan
Hertel, Alexander
Nörenberg, Dominik
Overhoff, Daniel
Rotkopf, Lukas T.
Riffel, Philipp
Schoenberg, Stefan O.
Froelich, Matthias F.
author_facet Ayx, Isabelle
Tharmaseelan, Hishan
Hertel, Alexander
Nörenberg, Dominik
Overhoff, Daniel
Rotkopf, Lukas T.
Riffel, Philipp
Schoenberg, Stefan O.
Froelich, Matthias F.
author_sort Ayx, Isabelle
collection PubMed
description 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.
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spelling pubmed-93204122022-07-27 Myocardial Radiomics Texture Features Associated with Increased Coronary Calcium Score—First Results of a Photon-Counting CT Ayx, Isabelle Tharmaseelan, Hishan Hertel, Alexander Nörenberg, Dominik Overhoff, Daniel Rotkopf, Lukas T. Riffel, Philipp Schoenberg, Stefan O. Froelich, Matthias F. Diagnostics (Basel) Article 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. MDPI 2022-07-08 /pmc/articles/PMC9320412/ /pubmed/35885567 http://dx.doi.org/10.3390/diagnostics12071663 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Ayx, Isabelle
Tharmaseelan, Hishan
Hertel, Alexander
Nörenberg, Dominik
Overhoff, Daniel
Rotkopf, Lukas T.
Riffel, Philipp
Schoenberg, Stefan O.
Froelich, Matthias F.
Myocardial Radiomics Texture Features Associated with Increased Coronary Calcium Score—First Results of a Photon-Counting CT
title Myocardial Radiomics Texture Features Associated with Increased Coronary Calcium Score—First Results of a Photon-Counting CT
title_full Myocardial Radiomics Texture Features Associated with Increased Coronary Calcium Score—First Results of a Photon-Counting CT
title_fullStr Myocardial Radiomics Texture Features Associated with Increased Coronary Calcium Score—First Results of a Photon-Counting CT
title_full_unstemmed Myocardial Radiomics Texture Features Associated with Increased Coronary Calcium Score—First Results of a Photon-Counting CT
title_short Myocardial Radiomics Texture Features Associated with Increased Coronary Calcium Score—First Results of a Photon-Counting CT
title_sort myocardial radiomics texture features associated with increased coronary calcium score—first results of a photon-counting ct
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9320412/
https://www.ncbi.nlm.nih.gov/pubmed/35885567
http://dx.doi.org/10.3390/diagnostics12071663
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