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Assessment of epicardial adipose tissue on virtual non-contrast images derived from photon-counting detector coronary CTA datasets

OBJECTIVES: To assess epicardial adipose tissue (EAT) volume and attenuation of different virtual non-contrast (VNC) reconstructions derived from coronary CTA (CCTA) datasets of a photon-counting detector (PCD) CT-system to replace true non-contrast (TNC) series. METHODS: Consecutive patients (n = 4...

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Autores principales: Risch, Franka, Schwarz, Florian, Braun, Franziska, Bette, Stefanie, Becker, Judith, Scheurig-Muenkler, Christian, Kroencke, Thomas J., Decker, Josua A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10017616/
https://www.ncbi.nlm.nih.gov/pubmed/36462042
http://dx.doi.org/10.1007/s00330-022-09257-6
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author Risch, Franka
Schwarz, Florian
Braun, Franziska
Bette, Stefanie
Becker, Judith
Scheurig-Muenkler, Christian
Kroencke, Thomas J.
Decker, Josua A.
author_facet Risch, Franka
Schwarz, Florian
Braun, Franziska
Bette, Stefanie
Becker, Judith
Scheurig-Muenkler, Christian
Kroencke, Thomas J.
Decker, Josua A.
author_sort Risch, Franka
collection PubMed
description OBJECTIVES: To assess epicardial adipose tissue (EAT) volume and attenuation of different virtual non-contrast (VNC) reconstructions derived from coronary CTA (CCTA) datasets of a photon-counting detector (PCD) CT-system to replace true non-contrast (TNC) series. METHODS: Consecutive patients (n = 42) with clinically indicated CCTA and coronary TNC were included. Two VNC series were reconstructed, using a conventional (VNC(Conv)) and a novel calcium-preserving (VNC(PC)) algorithm. EAT was segmented on TNC, VNC(Conv), VNC(PC), and CCTA (CTA(-30)) series using thresholds of −190 to −30 HU and an additional segmentation on the CCTA series with an upper threshold of 0 HU (CTA(0)). EAT volumes and their histograms were assessed for each series. Linear regression was used to correlate EAT volumes and the Euclidian distance for histograms. The paired t-test and the Wilcoxon signed-rank test were used to assess differences for parametric and non-parametric data. RESULTS: EAT volumes from VNC and CCTA series showed significant differences compared to TNC (all p < .05), but excellent correlation (all R(2) > 0.9). Measurements on the novel VNC(PC) series showed the best correlation (R(2) = 0.99) and only minor absolute differences compared to TNC values. Mean volume differences were −12%, −3%, −13%, and +10% for VNC(Conv), VNC(PC), CTA(-30), and CTA(0) compared to TNC. Distribution of CT values on VNC(PC) showed less difference to TNC than on VNC(Conv) (mean attenuation difference +7% vs. +2%; Euclidean distance of histograms 0.029 vs. 0.016). CONCLUSIONS: VNC(PC)-reconstructions of PCD-CCTA datasets can be used to reliably assess EAT volume with a high accuracy and only minor differences in CT values compared to TNC. Substitution of TNC would significantly decrease patient’s radiation dose. KEY POINTS: • Measurement of epicardial adipose tissue (EAT) volume and attenuation are feasible on virtual non-contrast (VNC) series with excellent correlation to true non-contrast series (all R (2) >0.9). • Differences in VNC algorithms have a significant impact on EAT volume and CT attenuation values. • A novel VNC algorithm (VNC (PC) ) enables reliable assessment of EAT volume and attenuation with superior accuracy compared to measurements on conventional VNC- and CCTA-series.
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spelling pubmed-100176162023-03-17 Assessment of epicardial adipose tissue on virtual non-contrast images derived from photon-counting detector coronary CTA datasets Risch, Franka Schwarz, Florian Braun, Franziska Bette, Stefanie Becker, Judith Scheurig-Muenkler, Christian Kroencke, Thomas J. Decker, Josua A. Eur Radiol Computed Tomography OBJECTIVES: To assess epicardial adipose tissue (EAT) volume and attenuation of different virtual non-contrast (VNC) reconstructions derived from coronary CTA (CCTA) datasets of a photon-counting detector (PCD) CT-system to replace true non-contrast (TNC) series. METHODS: Consecutive patients (n = 42) with clinically indicated CCTA and coronary TNC were included. Two VNC series were reconstructed, using a conventional (VNC(Conv)) and a novel calcium-preserving (VNC(PC)) algorithm. EAT was segmented on TNC, VNC(Conv), VNC(PC), and CCTA (CTA(-30)) series using thresholds of −190 to −30 HU and an additional segmentation on the CCTA series with an upper threshold of 0 HU (CTA(0)). EAT volumes and their histograms were assessed for each series. Linear regression was used to correlate EAT volumes and the Euclidian distance for histograms. The paired t-test and the Wilcoxon signed-rank test were used to assess differences for parametric and non-parametric data. RESULTS: EAT volumes from VNC and CCTA series showed significant differences compared to TNC (all p < .05), but excellent correlation (all R(2) > 0.9). Measurements on the novel VNC(PC) series showed the best correlation (R(2) = 0.99) and only minor absolute differences compared to TNC values. Mean volume differences were −12%, −3%, −13%, and +10% for VNC(Conv), VNC(PC), CTA(-30), and CTA(0) compared to TNC. Distribution of CT values on VNC(PC) showed less difference to TNC than on VNC(Conv) (mean attenuation difference +7% vs. +2%; Euclidean distance of histograms 0.029 vs. 0.016). CONCLUSIONS: VNC(PC)-reconstructions of PCD-CCTA datasets can be used to reliably assess EAT volume with a high accuracy and only minor differences in CT values compared to TNC. Substitution of TNC would significantly decrease patient’s radiation dose. KEY POINTS: • Measurement of epicardial adipose tissue (EAT) volume and attenuation are feasible on virtual non-contrast (VNC) series with excellent correlation to true non-contrast series (all R (2) >0.9). • Differences in VNC algorithms have a significant impact on EAT volume and CT attenuation values. • A novel VNC algorithm (VNC (PC) ) enables reliable assessment of EAT volume and attenuation with superior accuracy compared to measurements on conventional VNC- and CCTA-series. Springer Berlin Heidelberg 2022-12-03 2023 /pmc/articles/PMC10017616/ /pubmed/36462042 http://dx.doi.org/10.1007/s00330-022-09257-6 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Computed Tomography
Risch, Franka
Schwarz, Florian
Braun, Franziska
Bette, Stefanie
Becker, Judith
Scheurig-Muenkler, Christian
Kroencke, Thomas J.
Decker, Josua A.
Assessment of epicardial adipose tissue on virtual non-contrast images derived from photon-counting detector coronary CTA datasets
title Assessment of epicardial adipose tissue on virtual non-contrast images derived from photon-counting detector coronary CTA datasets
title_full Assessment of epicardial adipose tissue on virtual non-contrast images derived from photon-counting detector coronary CTA datasets
title_fullStr Assessment of epicardial adipose tissue on virtual non-contrast images derived from photon-counting detector coronary CTA datasets
title_full_unstemmed Assessment of epicardial adipose tissue on virtual non-contrast images derived from photon-counting detector coronary CTA datasets
title_short Assessment of epicardial adipose tissue on virtual non-contrast images derived from photon-counting detector coronary CTA datasets
title_sort assessment of epicardial adipose tissue on virtual non-contrast images derived from photon-counting detector coronary cta datasets
topic Computed Tomography
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10017616/
https://www.ncbi.nlm.nih.gov/pubmed/36462042
http://dx.doi.org/10.1007/s00330-022-09257-6
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