In vitro optimization and comparison of CT angiography versus radial cardiovascular magnetic resonance for the quantification of cross-sectional areas and coronary endothelial function.
Computed Tomography Angiography
/ instrumentation
Contrast Media
Coronary Angiography
/ instrumentation
Coronary Circulation
Coronary Vessels
/ diagnostic imaging
Endothelium, Vascular
/ diagnostic imaging
Humans
Limit of Detection
Magnetic Resonance Imaging
/ instrumentation
Meglumine
Multidetector Computed Tomography
/ instrumentation
Organometallic Compounds
Phantoms, Imaging
Predictive Value of Tests
Reproducibility of Results
Vasodilation
Accuracy
CT angiography
Coronary artery
Cross-sectional area
Endothelial function
Limit of detection
Precision
Radial CMR
Vasodilation
Vasomotor response
Journal
Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance
ISSN: 1532-429X
Titre abrégé: J Cardiovasc Magn Reson
Pays: England
ID NLM: 9815616
Informations de publication
Date de publication:
07 02 2019
07 02 2019
Historique:
received:
26
09
2018
accepted:
14
01
2019
entrez:
8
2
2019
pubmed:
8
2
2019
medline:
29
1
2020
Statut:
epublish
Résumé
Our objectives were first to determine the optimal coronary computed tomography angiography (CTA) protocol for the quantification and detection of simulated coronary artery cross-sectional area (CSA) differences in vitro, and secondly to quantitatively compare the performance of the optimized CTA protocol with a previously validated radial coronary cardiovascular magnetic resonance (CMR) technique. 256-multidetector CTA and radial coronary CMR were used to obtain images of a custom in vitro resolution phantom simulating a range of physiological responses of coronary arteries to stress. CSAs were automatically quantified and compared with known nominal values to determine the accuracy, precision, signal-to-noise ratio (SNR), and circularity of CSA measurements, as well as the limit of detection (LOD) of CSA differences. Various iodine concentrations, radiation dose levels, tube potentials, and iterative image reconstruction algorithms (ASiR-V) were investigated to determine the optimal CTA protocol. The performance of the optimized CTA protocol was then compared with a radial coronary CMR method previously developed for endothelial function assessment under both static and moving conditions. The iodine concentration, dose level, tube potential, and reconstruction algorithm all had significant effects (all p < 0.001) on the accuracy, precision, LOD, SNR, and circularity of CSA measurements with CTA. The best precision, LOD, SNR, and circularity with CTA were achieved with 6% iodine, 20 mGy, 100 kVp, and 90% ASiR-V. Compared with the optimized CTA protocol under static conditions, radial coronary CMR was less accurate (- 0.91 ± 0.13 mm Radial coronary CMR was more precise and outperformed CTA for the specific task of detecting small CSA differences in vitro, and was able to reliably identify CSA changes an order of magnitude smaller than those reported for healthy physiological vasomotor responses of proximal coronary arteries. However, CTA yielded more accurate CSA measurements, which may prove useful in other clinical scenarios, such as coronary artery stenosis assessment.
Sections du résumé
BACKGROUND
Our objectives were first to determine the optimal coronary computed tomography angiography (CTA) protocol for the quantification and detection of simulated coronary artery cross-sectional area (CSA) differences in vitro, and secondly to quantitatively compare the performance of the optimized CTA protocol with a previously validated radial coronary cardiovascular magnetic resonance (CMR) technique.
METHODS
256-multidetector CTA and radial coronary CMR were used to obtain images of a custom in vitro resolution phantom simulating a range of physiological responses of coronary arteries to stress. CSAs were automatically quantified and compared with known nominal values to determine the accuracy, precision, signal-to-noise ratio (SNR), and circularity of CSA measurements, as well as the limit of detection (LOD) of CSA differences. Various iodine concentrations, radiation dose levels, tube potentials, and iterative image reconstruction algorithms (ASiR-V) were investigated to determine the optimal CTA protocol. The performance of the optimized CTA protocol was then compared with a radial coronary CMR method previously developed for endothelial function assessment under both static and moving conditions.
RESULTS
The iodine concentration, dose level, tube potential, and reconstruction algorithm all had significant effects (all p < 0.001) on the accuracy, precision, LOD, SNR, and circularity of CSA measurements with CTA. The best precision, LOD, SNR, and circularity with CTA were achieved with 6% iodine, 20 mGy, 100 kVp, and 90% ASiR-V. Compared with the optimized CTA protocol under static conditions, radial coronary CMR was less accurate (- 0.91 ± 0.13 mm
CONCLUSIONS
Radial coronary CMR was more precise and outperformed CTA for the specific task of detecting small CSA differences in vitro, and was able to reliably identify CSA changes an order of magnitude smaller than those reported for healthy physiological vasomotor responses of proximal coronary arteries. However, CTA yielded more accurate CSA measurements, which may prove useful in other clinical scenarios, such as coronary artery stenosis assessment.
Identifiants
pubmed: 30728035
doi: 10.1186/s12968-019-0521-z
pii: 10.1186/s12968-019-0521-z
pmc: PMC6366062
doi:
Substances chimiques
Contrast Media
0
Organometallic Compounds
0
Meglumine
6HG8UB2MUY
gadoterate meglumine
L0ND3981AG
Types de publication
Comparative Study
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
11Références
Radiology. 2015 Aug;276(2):339-57
pubmed: 26203706
Radiat Prot Dosimetry. 2018 Jan 1;178(1):63-72
pubmed: 28591861
J Cardiovasc Magn Reson. 2000;2(3):181-7
pubmed: 11545115
AJR Am J Roentgenol. 2017 Nov;209(5):1088-1092
pubmed: 28834448
PLoS One. 2013;8(3):e58047
pubmed: 23536782
Acta Radiol. 2008 Jul;49(6):658-67
pubmed: 18568558
Eur Heart J. 2012 Feb;33(4):495-504
pubmed: 21951627
Circ Cardiovasc Imaging. 2010 Mar;3(2):179-86
pubmed: 20044512
Int J Cardiovasc Imaging. 2008 Jun;24(5):535-46
pubmed: 18368512
Magn Reson Med. 2019 Jan;81(1):291-302
pubmed: 30024061
Phys Med. 2018 Apr;48:111-118
pubmed: 29728223
Radiat Prot Dosimetry. 2015 Apr;164(1-2):116-9
pubmed: 25342609
Invest Radiol. 2018 Aug;53(8):486-494
pubmed: 29794949
J Cardiovasc Comput Tomogr. 2015 May-Jun;9(3):215-24
pubmed: 25843243
Magn Reson Med. 2016 Nov;76(5):1443-1454
pubmed: 26597978
J Am Coll Cardiol. 2010 Nov 9;56(20):1657-65
pubmed: 21050976
AJNR Am J Neuroradiol. 2001 Mar;22(3):481-92
pubmed: 11237970
Magn Reson Med. 2018 Jan;79(1):108-120
pubmed: 28261859
Int J Cardiovasc Imaging. 2018 Aug;34(8):1265-1275
pubmed: 29516228
Med Phys. 2007 Nov;34(11):4526-44
pubmed: 18072519
Am J Physiol Heart Circ Physiol. 2015 Jun 1;308(11):H1343-50
pubmed: 25820391
Circulation. 2007 Mar 13;115(10):1285-95
pubmed: 17353456
Radiographics. 2017 Nov-Dec;37(7):1955-1974
pubmed: 29131773
Nature. 1980 Nov 27;288(5789):373-6
pubmed: 6253831
Am Heart J. 2006 Feb;151(2):404-11
pubmed: 16442907
J Magn Reson Imaging. 2015 May;41(5):1251-8
pubmed: 24989833
Am J Cardiol. 2011 Aug 15;108(4):491-7
pubmed: 21624552
J Magn Reson Imaging. 1998 Nov-Dec;8(6):1228-35
pubmed: 9848733
J Comput Assist Tomogr. 2018 Mar/Apr;42(2):184-190
pubmed: 28806318
JACC Cardiovasc Imaging. 2011 Jan;4(1):50-61
pubmed: 21232704
Invest Radiol. 2018 Mar;53(3):143-149
pubmed: 28945655
J Cardiovasc Comput Tomogr. 2017 Jan - Feb;11(1):33-39
pubmed: 28096049
Med Phys. 2017 Sep;44(9):e153-e163
pubmed: 28901621
Circ Cardiovasc Imaging. 2012 May 1;5(3):341-8
pubmed: 22492483
Eur Radiol. 2014 Feb;24(2):469-83
pubmed: 24121713
Circulation. 2004 Jun 15;109(23 Suppl 1):III27-32
pubmed: 15198963
Circ J. 2012;76(1):160-7
pubmed: 22033346
N Engl J Med. 1986 Oct 23;315(17):1046-51
pubmed: 3093861