Yinghua Tao1, Guang-Hong Chen2, Timothy A Hacker3, Amish N Raval3, Michael S Van Lysel4, Michael A Speidel4. 1. Department of Medical Physics, University of Wisconsin-Madison, Madison, Wisconsin 53705. 2. Department of Medical Physics and Department of Radiology, University of Wisconsin-Madison, Madison, Wisconsin 53705. 3. Department of Medicine, University of Wisconsin-Madison, Madison, Wisconsin 53792. 4. Department of Medical Physics and Department of Medicine, University of Wisconsin-Madison, Madison, Wisconsin 53705.
Abstract
PURPOSE: Dynamic CT myocardial perfusion imaging has the potential to provide both functional and anatomical information regarding coronary artery stenosis. However, radiation dose can be potentially high due to repeated scanning of the same region. The purpose of this study is to investigate the use of statistical iterative reconstruction to improve parametric maps of myocardial perfusion derived from a low tube current dynamic CT acquisition. METHODS: Four pigs underwent high (500 mA) and low (25 mA) dose dynamic CT myocardial perfusion scans with and without coronary occlusion. To delineate the affected myocardial territory, an N-13 ammonia PET perfusion scan was performed for each animal in each occlusion state. Filtered backprojection (FBP) reconstruction was first applied to all CT data sets. Then, a statistical iterative reconstruction (SIR) method was applied to data sets acquired at low dose. Image voxel noise was matched between the low dose SIR and high dose FBP reconstructions. CT perfusion maps were compared among the low dose FBP, low dose SIR and high dose FBP reconstructions. Numerical simulations of a dynamic CT scan at high and low dose (20:1 ratio) were performed to quantitatively evaluate SIR and FBP performance in terms of flow map accuracy, precision, dose efficiency, and spatial resolution. RESULTS: Forin vivo studies, the 500 mA FBP maps gave -88.4%, -96.0%, -76.7%, and -65.8% flow change in the occluded anterior region compared to the open-coronary scans (four animals). The percent changes in the 25 mA SIR maps were in good agreement, measuring -94.7%, -81.6%, -84.0%, and -72.2%. The 25 mA FBP maps gave unreliable flow measurements due to streaks caused by photon starvation (percent changes of +137.4%, +71.0%, -11.8%, and -3.5%). Agreement between 25 mA SIR and 500 mA FBP global flow was -9.7%, 8.8%, -3.1%, and 26.4%. The average variability of flow measurements in a nonoccluded region was 16.3%, 24.1%, and 937.9% for the 500 mA FBP, 25 mA SIR, and 25 mA FBP, respectively. In numerical simulations, SIR mitigated streak artifacts in the low dose data and yielded flow maps with mean error <7% and standard deviation <9% of mean, for 30 × 30 pixel ROIs (12.9 × 12.9 mm(2)). In comparison, low dose FBP flow errors were -38% to +258%, and standard deviation was 6%-93%. Additionally, low dose SIR achieved 4.6 times improvement in flow map CNR(2) per unit input dose compared to low dose FBP. CONCLUSIONS: SIR reconstruction can reduce image noise and mitigate streaking artifacts caused by photon starvation in dynamic CT myocardial perfusion data sets acquired at low dose (low tube current), and improve perfusion map quality in comparison to FBP reconstruction at the same dose.
PURPOSE: Dynamic CT myocardial perfusion imaging has the potential to provide both functional and anatomical information regarding coronary artery stenosis. However, radiation dose can be potentially high due to repeated scanning of the same region. The purpose of this study is to investigate the use of statistical iterative reconstruction to improve parametric maps of myocardial perfusion derived from a low tube current dynamic CT acquisition. METHODS: Four pigs underwent high (500 mA) and low (25 mA) dose dynamic CT myocardial perfusion scans with and without coronary occlusion. To delineate the affected myocardial territory, an N-13 ammonia PET perfusion scan was performed for each animal in each occlusion state. Filtered backprojection (FBP) reconstruction was first applied to all CT data sets. Then, a statistical iterative reconstruction (SIR) method was applied to data sets acquired at low dose. Image voxel noise was matched between the low dose SIR and high dose FBP reconstructions. CT perfusion maps were compared among the low dose FBP, low dose SIR and high dose FBP reconstructions. Numerical simulations of a dynamic CT scan at high and low dose (20:1 ratio) were performed to quantitatively evaluate SIR and FBP performance in terms of flow map accuracy, precision, dose efficiency, and spatial resolution. RESULTS: Forin vivo studies, the 500 mA FBP maps gave -88.4%, -96.0%, -76.7%, and -65.8% flow change in the occluded anterior region compared to the open-coronary scans (four animals). The percent changes in the 25 mA SIR maps were in good agreement, measuring -94.7%, -81.6%, -84.0%, and -72.2%. The 25 mA FBP maps gave unreliable flow measurements due to streaks caused by photon starvation (percent changes of +137.4%, +71.0%, -11.8%, and -3.5%). Agreement between 25 mA SIR and 500 mA FBP global flow was -9.7%, 8.8%, -3.1%, and 26.4%. The average variability of flow measurements in a nonoccluded region was 16.3%, 24.1%, and 937.9% for the 500 mA FBP, 25 mA SIR, and 25 mA FBP, respectively. In numerical simulations, SIR mitigated streak artifacts in the low dose data and yielded flow maps with mean error <7% and standard deviation <9% of mean, for 30 × 30 pixel ROIs (12.9 × 12.9 mm(2)). In comparison, low dose FBP flow errors were -38% to +258%, and standard deviation was 6%-93%. Additionally, low dose SIR achieved 4.6 times improvement in flow map CNR(2) per unit input dose compared to low dose FBP. CONCLUSIONS: SIR reconstruction can reduce image noise and mitigate streaking artifacts caused by photon starvation in dynamic CT myocardial perfusion data sets acquired at low dose (low tube current), and improve perfusion map quality in comparison to FBP reconstruction at the same dose.
Authors: Tiago A Magalhães; Roberto C Cury; Alexandre C Pereira; Valéria de Melo Moreira; Pedro A Lemos; Roberto Kalil-Filho; Carlos E Rochitte Journal: J Cardiovasc Comput Tomogr Date: 2011-11-04
Authors: Andreas H Mahnken; Ernst Klotz; Hubertus Pietsch; Bernhard Schmidt; Thomas Allmendinger; Ulrike Haberland; Willi A Kalender; Thomas Flohr Journal: Invest Radiol Date: 2010-06 Impact factor: 6.016
Authors: Philip Stenner; Bernhard Schmidt; Herbert Bruder; Thomas Allmendinger; Ulrike Haberland; Thomas Flohr; Marc Kachelriess Journal: Med Phys Date: 2009-12 Impact factor: 4.071
Authors: Richard T George; Caterina Silva; Marco A S Cordeiro; Anthony DiPaula; Douglas R Thompson; William F McCarthy; Takashi Ichihara; Joao A C Lima; Albert C Lardo Journal: J Am Coll Cardiol Date: 2006-06-21 Impact factor: 24.094
Authors: Fabian Bamberg; Alexander Becker; Florian Schwarz; Roy P Marcus; Martin Greif; Franz von Ziegler; Ron Blankstein; Udo Hoffmann; Wieland H Sommer; Verena S Hoffmann; Thorsten R C Johnson; Hans-Christoph R Becker; Bernd J Wintersperger; Maximilian F Reiser; Konstantin Nikolaou Journal: Radiology Date: 2011-09 Impact factor: 11.105
Authors: Jose A Rocha-Filho; Ron Blankstein; Leonid D Shturman; Hiram G Bezerra; David R Okada; Ian S Rogers; Brian Ghoshhajra; Udo Hoffmann; Gudrun Feuchtner; Wilfred S Mamuya; Thomas J Brady; Ricardo C Cury Journal: Radiology Date: 2010-02 Impact factor: 11.105
Authors: Richard T George; Armin Arbab-Zadeh; Julie M Miller; Kakuya Kitagawa; Hyuk-Jae Chang; David A Bluemke; Lewis Becker; Omair Yousuf; John Texter; Albert C Lardo; João A C Lima Journal: Circ Cardiovasc Imaging Date: 2009-03-31 Impact factor: 7.792
Authors: Filippo Cademartiri; Sara Seitun; Alberto Clemente; Ludovico La Grutta; Patrizia Toia; Giuseppe Runza; Massimo Midiri; Erica Maffei Journal: Cardiovasc Diagn Ther Date: 2017-04