Mohamed Marwan1, Susanna Koenig2, Kirsten Schreiber3, Fabian Ammon4, Markus Goeller5, Daniel Bittner6, Stephan Achenbach7, Michaela M Hell8. 1. Department of Cardiology, Friedrich-Alexander-Universität Erlangen-Nürnberg, Ulmenweg 18, 91054 Erlangen, Germany. Electronic address: mohamed.marwan@uk-erlangen.de. 2. Department of Cardiology, Friedrich-Alexander-Universität Erlangen-Nürnberg, Ulmenweg 18, 91054 Erlangen, Germany. Electronic address: su_koenig@gmx.de. 3. Department of Cardiology, Friedrich-Alexander-Universität Erlangen-Nürnberg, Ulmenweg 18, 91054 Erlangen, Germany. Electronic address: kirsten_schreiber@web.de. 4. Department of Cardiology, Friedrich-Alexander-Universität Erlangen-Nürnberg, Ulmenweg 18, 91054 Erlangen, Germany. Electronic address: fabian.ammon@uk-erlangen.de. 5. Department of Cardiology, Friedrich-Alexander-Universität Erlangen-Nürnberg, Ulmenweg 18, 91054 Erlangen, Germany. Electronic address: markus.goeller@uk-erlangen.de. 6. Department of Cardiology, Friedrich-Alexander-Universität Erlangen-Nürnberg, Ulmenweg 18, 91054 Erlangen, Germany. Electronic address: daniel.bittner@uk-erlangen.de. 7. Department of Cardiology, Friedrich-Alexander-Universität Erlangen-Nürnberg, Ulmenweg 18, 91054 Erlangen, Germany. Electronic address: stephan.achenbach@uk-erlangen.de. 8. Department of Cardiology, Friedrich-Alexander-Universität Erlangen-Nürnberg, Ulmenweg 18, 91054 Erlangen, Germany. Electronic address: michaela.hell@uk-erlangen.de.
Abstract
PURPOSE: While computed tomography (CT) is frequently used to quantify epicardial adipose tissue (EAT), the effect of different acquisition parameters on EAT volume has not been systematically reported. We assessed the influence of low-voltage acquisition and contrast enhancement on EAT quantification. METHOD: Two independent cohorts (100 and 127 patients) referred for routine coronary CT were included. One cohort received a low-voltage and a standard voltage non-contrast acquisition (120 and 100 kV), the other cohort underwent non-contrast and contrast-enhanced CT. EAT volume was quantified using a semi-automated analysis software. Whereas the lower EAT threshold was consistently set at -190 Hounsfield Units (HU), different upper thresholds for EAT were analyzed. Bland-Altman analysis was used to analyze the agreement of EAT volume between scans with different acquisition parameters. We referred to a non-enhanced 120 kV acquisition with an upper threshold of -30 HU. RESULTS: Mean EAT volume was 159 ± 76 ml as measured in 120 kV non-contrast data sets with an upper threshold of -30 HU. For 100 kV data sets, an upper threshold of -40 HU showed the best correlation (r = 0.961, p < 0.05). Significant overestimation was found for upper thresholds of -20 and -30 HU and significant underestimation for -50 HU. In non-contrast vs. contrast-enhanced acquisitions, there was a significant underestimation of EAT volume for contrast-enhanced scans (mean difference 31 ml, 95% limits of agreement 27 to -89 ml). CONCLUSIONS: CT-based EAT volume quantification in low-voltage and contrast-enhanced images is feasible. However, adjustment of the upper threshold for detection of fat is mandatory.
PURPOSE: While computed tomography (CT) is frequently used to quantify epicardial adipose tissue (EAT), the effect of different acquisition parameters on EAT volume has not been systematically reported. We assessed the influence of low-voltage acquisition and contrast enhancement on EAT quantification. METHOD: Two independent cohorts (100 and 127 patients) referred for routine coronary CT were included. One cohort received a low-voltage and a standard voltage non-contrast acquisition (120 and 100 kV), the other cohort underwent non-contrast and contrast-enhanced CT. EAT volume was quantified using a semi-automated analysis software. Whereas the lower EAT threshold was consistently set at -190 Hounsfield Units (HU), different upper thresholds for EAT were analyzed. Bland-Altman analysis was used to analyze the agreement of EAT volume between scans with different acquisition parameters. We referred to a non-enhanced 120 kV acquisition with an upper threshold of -30 HU. RESULTS: Mean EAT volume was 159 ± 76 ml as measured in 120 kV non-contrast data sets with an upper threshold of -30 HU. For 100 kV data sets, an upper threshold of -40 HU showed the best correlation (r = 0.961, p < 0.05). Significant overestimation was found for upper thresholds of -20 and -30 HU and significant underestimation for -50 HU. In non-contrast vs. contrast-enhanced acquisitions, there was a significant underestimation of EAT volume for contrast-enhanced scans (mean difference 31 ml, 95% limits of agreement 27 to -89 ml). CONCLUSIONS: CT-based EAT volume quantification in low-voltage and contrast-enhanced images is feasible. However, adjustment of the upper threshold for detection of fat is mandatory.
Authors: David Molnar; Olof Enqvist; Johannes Ulén; Måns Larsson; John Brandberg; Åse A Johnsson; Elias Björnson; Göran Bergström; Ola Hjelmgren Journal: Sci Rep Date: 2021-12-13 Impact factor: 4.379
Authors: Alexander Romanov; Stanislav Minin; Nikita Nikitin; Dmitry Ponomarev; Vitaly Shabanov; Denis Losik; Jonathan S Steinberg Journal: Ann Nucl Med Date: 2021-06-14 Impact factor: 2.668