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

• Published in: European radiology Vol. 33; no. 4; pp. 2450 - 2460
• Main Authors: Risch, Franka, Schwarz, Florian, Braun, Franziska, Bette, Stefanie, Becker, Judith, Scheurig-Muenkler, Christian, Kroencke, Thomas J., Decker, Josua A.
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.04.2023; Springer Nature B.V
• Subjects: Adipose tissue; Adipose Tissue - diagnostic imaging; Algorithms; Angiography; Attenuation; Body fat; Computed Tomography; Datasets; Diagnostic Radiology; Euclidean geometry; Histograms; Humans; Image contrast; Image segmentation; Imaging; Internal Medicine; Interventional Radiology; Medicine; Medicine & Public Health; Neuroradiology; Photons; Radiation; Radiation dosage; Radiation measurement; Radiology; Rank tests; Reproducibility of Results; Retrospective Studies; Tomography, X-Ray Computed - methods; Ultrasound; Heart; Computed tomography angiography; Medical image processing; Adipose tissue; Radiation dosage
• ISSN: 1432-1084; 0938-7994; 1432-1084
• DOI: 10.1007/s00330-022-09257-6

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.