Marly van Assen1, Gert Jan Pelgrim2, Carlo N De Cecco3, J Marco A Stijnen4, Beatrice M Zaki5, Matthijs Oudkerk6, Rozemarijn Vliegenthart7, U Joseph Schoepf8. 1. Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, 25 Courtenay Drive, Charleston, SC, USA; Center for Medical Imaging, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands. Electronic address: vanasse@musc.edu. 2. Center for Medical Imaging, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands. Electronic address: g.j.pelgrim@umcg.nl. 3. Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, 25 Courtenay Drive, Charleston, SC, USA; Division of Cardiothoracic Imaging, Nuclear Medicine and Molecular Imaging, Department of Radiology and Imaging Sciences, Emory University Hospital, Atlanta, GA, USA. Electronic address: carlo.dececco@emory.edu. 4. LifeTec Group, Eindhoven, the Netherlands. Electronic address: m.stijnen@lifetecgroup.com. 5. Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, 25 Courtenay Drive, Charleston, SC, USA. Electronic address: zaki@musc.edu. 6. Center for Medical Imaging, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands. Electronic address: m.oudker@rug.nl. 7. Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, 25 Courtenay Drive, Charleston, SC, USA; Center for Medical Imaging, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands. Electronic address: r.vliegenthart@umcg.nl. 8. Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, 25 Courtenay Drive, Charleston, SC, USA. Electronic address: schoepf@musc.edu.
Abstract
PURPOSE: To assess the intermodel agreement of different tracer kinetic models to determine myocardial blood flow (MBF) and their diagnostic accuracy in coronary artery disease (CAD) at dynamic CT myocardial perfusion imaging (CTMPI). METHODS: Three porcine hearts perfused in Langendorff mode and 15 patients with suspected CAD and perfusion single photon emission CT (SPECT) were included. Dynamic CTMPI was performed in shuttle-mode (70 kVp, 350mAs/rot) on 3rd generation dual-source CT. In porcine hearts and patients, myocardial segments (AHA-16-segment model) were drawn. Tissue attenuation curves were constructed per segment and arterial input functions were derived from the aorta. True MBF was calculated with input flow and weight of the porcine hearts. In patients, ischemic segments were based on SPECT results. MBF quantification was performed using the VPCT-software, Upslope, Extended Toft (ET), Two-compartment (TC) and Fermi models. RESULTS: In porcine hearts, true MBF was 1.88 (interquartile range [IQR]:1.80-2.80)mL/g/min. Diagnostic accuracy was similar for all models: 0.96, 0.99, 0.92, 0.93 and 0.96 for VPCT software, Upslope method, Fermi, ET and TC model. The VPCT software and Upslope method resulted in lower MBF (median 1.44 [1.29-1.58] and 1.39 [1.25-1.59]mL/g/min) compared to the Fermi, ET, and TC model (median values of 1.76 mL/g/min [1.36-2.44], 2.55 mL/g/min [2.20-2.92], and 1.98 mL/g/min [1.60-2.60], respectively [p < 0.001]). In patients, all models showed a significant difference in MBF between the 34 ischemic and 206 non-ischemic segments (p-value<0.001). CONCLUSION: Absolute MBF values are significantly different between the models and a uniform threshold could not be determined; however, diagnostic accuracy for detecting ischemia is similar. Published by Elsevier B.V.
PURPOSE: To assess the intermodel agreement of different tracer kinetic models to determine myocardial blood flow (MBF) and their diagnostic accuracy in coronary artery disease (CAD) at dynamic CT myocardial perfusion imaging (CTMPI). METHODS: Three porcine hearts perfused in Langendorff mode and 15 patients with suspected CAD and perfusion single photon emission CT (SPECT) were included. Dynamic CTMPI was performed in shuttle-mode (70 kVp, 350mAs/rot) on 3rd generation dual-source CT. In porcine hearts and patients, myocardial segments (AHA-16-segment model) were drawn. Tissue attenuation curves were constructed per segment and arterial input functions were derived from the aorta. True MBF was calculated with input flow and weight of the porcine hearts. In patients, ischemic segments were based on SPECT results. MBF quantification was performed using the VPCT-software, Upslope, Extended Toft (ET), Two-compartment (TC) and Fermi models. RESULTS: In porcine hearts, true MBF was 1.88 (interquartile range [IQR]:1.80-2.80)mL/g/min. Diagnostic accuracy was similar for all models: 0.96, 0.99, 0.92, 0.93 and 0.96 for VPCT software, Upslope method, Fermi, ET and TC model. The VPCT software and Upslope method resulted in lower MBF (median 1.44 [1.29-1.58] and 1.39 [1.25-1.59]mL/g/min) compared to the Fermi, ET, and TC model (median values of 1.76 mL/g/min [1.36-2.44], 2.55 mL/g/min [2.20-2.92], and 1.98 mL/g/min [1.60-2.60], respectively [p < 0.001]). In patients, all models showed a significant difference in MBF between the 34 ischemic and 206 non-ischemic segments (p-value<0.001). CONCLUSION: Absolute MBF values are significantly different between the models and a uniform threshold could not be determined; however, diagnostic accuracy for detecting ischemia is similar. Published by Elsevier B.V.
Authors: Fay M A Nous; Tobias Geisler; Mariusz B P Kruk; Hatem Alkadhi; Kakuya Kitagawa; Rozemarijn Vliegenthart; Michaela M Hell; Jörg Hausleiter; Patricia K Nguyen; Ricardo P J Budde; Konstantin Nikolaou; Cezary Kepka; Robert Manka; Hajime Sakuma; Sachin B Malik; Adriaan Coenen; Felix Zijlstra; Ernst Klotz; Pim van der Harst; Christoph Artzner; Admir Dedic; Francesca Pugliese; Fabian Bamberg; Koen Nieman Journal: JACC Cardiovasc Imaging Date: 2021-09-15