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Feasibility of the resting systolic myocardial perfusion imaging to #br#
assess chronic myocardial ischemia using a porcine animal |
YANG Yi-jing1, HOU Yang1, MA Yue1, ZHANG Xiao-juan2, WANG Yu-ke3, YU Mei4, SUI Shi1 |
1. Department of Radiology, Shengjing Hospital of China Medical University, Laboratory of Medical Image Computing Ministry of Education, Shenyang 110004, China; 2. CT Room, the Third People’s Hospital of Liaoyang, Liaoyang Liaoning 111000, China; 3. Department of Radiology, the People’s Hospital of Liaoning Province, Shenyang 110016, China;
4. Department of Radiology, Tangdu Hospital of the Fourth Military Medical University, Xi’an 710038, China |
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Abstract Objective: To determine the accuracy of the resting systolic myocardial perfusion imaging to assess myocardial ischemia with chronic coronary stenosis and the diagnostic differences capability of the dynamic adenosine-stress CT perfusion using a porcine animal. Methods: The chronic coronary stenosis models was build. 13N-NH3 PET adenosine stress-rest myocardial perfusion imaging(MPI) was obtained in order to have the resting systolic myocardial perfusion imaging(CTP) and the adenosine stress dynamic CT myocardial perfusion imaging(ASDCTP). The myocardial perfusion defect on the resting systolic CTP and ASDCTP were analyzed for the transmural differences in perfusion using the transmural perfusion ratio(TPR) and the myocardial blood flow(MBF) value, respectively. Taking PET-MPI as the reference standard, the sensitivity, specificity, positive predictive value(PPV), negative predictive value(NPV) and accuracy of CTP in the diagnosis of myocardial perfusion defect segments were evaluated. Using receiver operating characteristic curve(ROC) to assess the value analysis of the resting systolic CTP and ASDCTP. The threshold of significance was P<0.05. Results: The accuracy of the resting systolic CTP and ASDCTP to detect perfusion abnormalities using PET-MPI as the gold standard were 75.89% and 83.92%; The sensitivity, specificity, PPV and NPV were 68.75%, 81.25%, 73.33%, 77.61% and 83.33%, 84.37%, 80.0%, 87.1%, respectively. The area under the receiver operating characteristic curve(AUC) of the resting systolic and the adenosine stress dynamic CTP were 0.75 and 0.84, respectively, P=0.07(P>0.05). Conclusion: The resting systolic myocardial perfusion imaging to assess chronic myocardial ischemia using a porcine animal is feasible.
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Received: 01 April 2017
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[1]Cury RC, Kitt TM, Feaheny K, et al. A randomized, multicenter, multivendor study of myocardial perfusion imaging with regadenoson CT perfusion vs single photon emission CT[J]. J Cardiovasc Comput Tomogr, 2015, 9(2): 103-112.
[2]Bamberg F, Hinkel R, Marcus RP, et al. Feasibility of dynamic CT-based adenosine stress myocardial perfusion imaging to detect and differentiate ischemic and infarcted myocardium in an large experimental porcine animal model[J]. Int J Cardiovasc Imaging, 2014, 30(4): 803-812.
[3]Schwarz F, Hinkel R, Baloch E, et al. Myocardial CT perfusion imaging in a garge animal model: comparison of dynamic versus single-phase acquisitions[J]. JACC: Cardiovasc Imaging, 2013, 6(12): 1229-1238.
[4]Branch RK, Busey J, Mitsumori LM, et al. Diagnostic performance of resting CT myocardial perfusion in patients with possible acute coronary syndrome[J]. AJR, 2013, 200(5): 450-457.
[5]Troupis JM, Karge K, Seneviratne S, et al. Myocardial density analysis utilizing automated myocardial defect analysis software on resting 320-detector MDCT[J]. Int J Cardiovas Imaging, 2013, 29(5): 1121-1127.
[6]施冰,郭艳红,邓小莉,等. 中国实验小型猪慢性心肌缺血模型的制备[J]. 中国临床保健杂志,2006,9(2):134-136.
[7]文利,崔建华,黄河,等. 适于影像学研究的猪慢性心肌缺血模型的制备[J]. 第三军医大学学报,2010,32(12):1245-1248.
[8]Cerqueira MD, Weissman NJ, Dilsizian V, et al. Standardized myocardial segmentation and nomenclature for tomographic imaging of the heart[J]. Circulation, 2002, 105(4): 524-539.
[9]George RT, Arbab-Zadeh, Miller JM, et al. Adenosine Stress 64- and 256-Row Detector Computed Tomography Angiography and Perfusion Imaging A Pilot Study Evaluating the Transmural Extent of Perfusion Abnormalities to Predict Atherosclerosis Causing Myocardial Ischemia[J]. Circ Cardiovasc Imaging, 2009, 2(3): 174-182.
[10]Bamberg F, Marcus RP, Becker A, et al. Dynamic myocardial CT perfusion imaging for evaluation of myocardial ischemia as determined by MR Imaging[J]. JACC: Cardiovasc Imaging, 2014, 7(3): 267-277.
[11]Toyota E, Fujimoto K, Ogasawara Y, et al. Dynamic changes in three-dimensional architecture and vascular volume of transmural coronary microvasculature between diastolic- and systolic-arrested rat hearts[J]. Circulation, 2002, 105(5): 621-626.
[12]Pugliese F, Mollet NR, Runza G, et al. Diagnostic accuracy of non-invasive 64-slice CT coronary angiography in patients with stable angina pectoris[J]. Eur Radiol, 2006, 16(3): 575-582.
[13]Iwanaga S, Ewing SG, Husseini WK, et al. Changes in contractility and afterload have only slight effects on subendocardial systolic flow impediment[J]. Am J Physiol, 1995, 269(4 Pt 2): 1202-1212.
[14]Chilian WM. Microvascular pressures and resistances in the left ventricular subepicardium and subendocardium[J]. Circ Res, 1991, 69(3): 561-570.
[15]Iwasaki K, Matsumoto T. Myocardial perfusion defect in patients with coronary artery disease demonstrated by 64-multidetector computed tomography at rest[J]. Clin Cardiol, 2011, 34(7): 454-460.
[16]Busch JL, Alessio AM, Caldwell JH, et al. Myocardial hypo-enhancement on resting computed tomography angiography images accurately identifies myocardial hypoperfusion[J]. J Cardiovasc Comput Tomogr, 2011, 5(6): 412-420.
[17]Henneman MM, Schuijf JD, Dibbetsschneider P, et al. Comparison of multislice computed tomography to gated single-photon emission computed tomography for imaging of healed myocardial infarcts[J]. Am J Cardiol, 2008, 101(2): 144-148.
[18]Bauer RW, Kerl JM, Fischer N, et al. Dual-energy CT for the assessment of chronic myocardial infarction in patients with chronic coronary artery disease: Comparison with 3T-MRI[J]. AJR, 2010, 195(3): 639-646.
[19]de Roos A. Myocardial perfusion imaging with multidetector CT: beyond lumenography[J]. Radiology, 2010, 254(2): 321-323. |
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