Alexia Rossi1, Andrew Wragg1, Ernst Klotz1, Federica Pirro1, James C Moon1, Koen Nieman1, Francesca Pugliese2. 1. From the Centre for Advanced Cardiovascular Imaging, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, United Kingdom and Barts Heart Centre, St Bartholomew's Hospital, Barts Health NHS Trust, London, United Kingdom (A.R., A.W., F. Pirro, F. Pugliese); Siemens Healthineers, Forchheim, Germany (E.K.); Institute of Cardiovascular Science, University College London, United Kingdom (J.C.M.); and Departments of Cardiology and Radiology, Erasmus MC University Medical Centre Rotterdam, The Netherlands (K.N.). 2. From the Centre for Advanced Cardiovascular Imaging, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, United Kingdom and Barts Heart Centre, St Bartholomew's Hospital, Barts Health NHS Trust, London, United Kingdom (A.R., A.W., F. Pirro, F. Pugliese); Siemens Healthineers, Forchheim, Germany (E.K.); Institute of Cardiovascular Science, University College London, United Kingdom (J.C.M.); and Departments of Cardiology and Radiology, Erasmus MC University Medical Centre Rotterdam, The Netherlands (K.N.). f.pugliese@qmul.ac.uk.
Abstract
BACKGROUND: The clinical analysis of myocardial dynamic computed tomography myocardial perfusion imaging lacks standardization. The objective of this prospective study was to compare different analysis approaches to diagnose ischemia in patients with stable angina referred for invasive coronary angiography. METHODS AND RESULTS: Patients referred for evaluation of stable angina symptoms underwent adenosine-stress dynamic computed tomography myocardial perfusion imaging with a second-generation dual-source scanner. Quantitative perfusion parameters, such as blood flow, were calculated by parametric deconvolution for each myocardial voxel. Initially, perfusion parameters were extracted according to standard 17-segment model of the left ventricle (fully automatic analysis). These were then manually sampled by an operator (semiautomatic analysis). Areas under the receiver-operating characteristic curves of the 2 different approaches were compared. Invasive fractional flow reserve ≤0.80 or diameter stenosis ≥80% on quantitative coronary angiography was used as reference standard to define ischemia. We enrolled 115 patients (88 men; age 57±9 years). There were 72 of 286 (25%) vessels causing ischemia in 52 of 115 (45%) patients. The semiautomatic analysis method was better than the fully automatic method at predicting ischemia (areas under the receiver-operating characteristic curves, 0.87 versus 0.69; P<0.001) with readings obtained in the endocardial myocardium performing better than those in the epicardial myocardium (areas under the receiver-operating characteristic curves, 0.87 versus 0.72; P<0.001). The difference in performance between blood flow, expressed as relative to remote myocardium, and absolute blood flow was not statistically significant (areas under the receiver-operating characteristic curves, 0.90 versus 0.87; P=ns). CONCLUSIONS: Endocardial perfusion parameters obtained by semiautomatic analysis of dynamic computed tomography myocardial perfusion imaging may permit robust discrimination between coronary vessels causing ischemia versus not causing ischemia.
BACKGROUND: The clinical analysis of myocardial dynamic computed tomography myocardial perfusion imaging lacks standardization. The objective of this prospective study was to compare different analysis approaches to diagnose ischemia in patients with stable angina referred for invasive coronary angiography. METHODS AND RESULTS:Patients referred for evaluation of stable angina symptoms underwent adenosine-stress dynamic computed tomography myocardial perfusion imaging with a second-generation dual-source scanner. Quantitative perfusion parameters, such as blood flow, were calculated by parametric deconvolution for each myocardial voxel. Initially, perfusion parameters were extracted according to standard 17-segment model of the left ventricle (fully automatic analysis). These were then manually sampled by an operator (semiautomatic analysis). Areas under the receiver-operating characteristic curves of the 2 different approaches were compared. Invasive fractional flow reserve ≤0.80 or diameter stenosis ≥80% on quantitative coronary angiography was used as reference standard to define ischemia. We enrolled 115 patients (88 men; age 57±9 years). There were 72 of 286 (25%) vessels causing ischemia in 52 of 115 (45%) patients. The semiautomatic analysis method was better than the fully automatic method at predicting ischemia (areas under the receiver-operating characteristic curves, 0.87 versus 0.69; P<0.001) with readings obtained in the endocardial myocardium performing better than those in the epicardial myocardium (areas under the receiver-operating characteristic curves, 0.87 versus 0.72; P<0.001). The difference in performance between blood flow, expressed as relative to remote myocardium, and absolute blood flow was not statistically significant (areas under the receiver-operating characteristic curves, 0.90 versus 0.87; P=ns). CONCLUSIONS: Endocardial perfusion parameters obtained by semiautomatic analysis of dynamic computed tomography myocardial perfusion imaging may permit robust discrimination between coronary vessels causing ischemia versus not causing ischemia.
Authors: Gianluca Pontone; Alexia Rossi; Marco Guglielmo; Marc R Dweck; Oliver Gaemperli; Koen Nieman; Francesca Pugliese; Pal Maurovich-Horvat; Alessia Gimelli; Bernard Cosyns; Stephan Achenbach Journal: Eur Heart J Cardiovasc Imaging Date: 2022-03-22 Impact factor: 9.130
Authors: S Oebel; S Hamada; K Higashigaito; J von Spiczak; E Klotz; F Enseleit; R Hinzpeter; F Ruschitzka; R Manka; H Alkadhi Journal: Eur Radiol Date: 2018-04-30 Impact factor: 5.315
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
Authors: Marc Dewey; Maria Siebes; Marc Kachelrieß; Klaus F Kofoed; Pál Maurovich-Horvat; Konstantin Nikolaou; Wenjia Bai; Andreas Kofler; Robert Manka; Sebastian Kozerke; Amedeo Chiribiri; Tobias Schaeffter; Florian Michallek; Frank Bengel; Stephan Nekolla; Paul Knaapen; Mark Lubberink; Roxy Senior; Meng-Xing Tang; Jan J Piek; Tim van de Hoef; Johannes Martens; Laura Schreiber Journal: Nat Rev Cardiol Date: 2020-02-24 Impact factor: 32.419