基于骨重建算法结合ASIR-V在冠状动脉支架成像中的应用研究

doi:10.16150/j.1671-2870.2022.01.013

摘要/Abstract

摘要：

目的： 探讨骨算法结合迭代重建（adaptive statistical iterative reconstruction-V,ASIR-V）技术在冠脉支架成像中的应用价值。目的： 收集本院2020年12月至2021年3月间42例冠状动脉支架植入术后行冠状动脉CT血管成像（coronary computed tomography angiography,CCTA）复查的患者,将扫描的原始数据按照标准算法（Stand）和骨重建算法（Bone）（以下简称骨算法）分别结合ASIR-V权重30%、60%进行重建,得到S30（Stand-30%）、S60（Stand-60%）、B30（Bone-30%）、B60（以下简称骨算法）（Bone-60%）4组图像,分别采用主观（Liket 5级评分法）和客观[图像信噪比（signal-to-noise ratio,SNR）、对比噪声比（contrast-to-noise ratio,CNR）、支架内管腔CT值-降主动脉CT值的差值]方法,对S30与S60、B30与B60、S30与B30、S60与B60间进行图像质量比较评价。结果： 主观评分中,S30、S60、B30、B60的评分分别为（3.54±0.60）分、（3.51±0.60）分、（4.15±0.67）分、（4.49±0.56）分,其中骨算法组的支架显示评分明显高于标准算法组,B60与S60间、B30与S30间差异有统计学意义（P<0.05）,且B60与B30间差异也有统计学意义（P<0.05）,B60评分最高。但在标准算法组内,S60与S30间差异无统计学意义（P>0.05）。客观评价方面,各组图像之间SNR及CNR的差异均具有统计学意义（P<0.05）,S60最高（SNR为18.3±2.56,CNR为26.3±6.35）;支架内管腔CT值-降主动脉CT值的差值比较中,S30与S60间、B30与B60间的差异均无统计学意义（P>0.05）,而S30与B30间、S60与B60间的差异均有统计学意义（P<0.05）,B60的CT值差值最低（36.41±79.37）。结论： 骨算法结合ASIR-V权重60%时,有利于冠脉支架的内腔及支架的显示,可以为临床提供较高质量的诊断图像。

关键词: 冠状动脉, 支架, 迭代重建, 骨算法

Abstract:

Objective: To investigate the efficacy of bore algorithms combined with adaptive statistical iterative reconstruction-V (ASIR-V) in coronary stent imaging. Methods: A total of 42 patients with coronary stent implantation in our hospital were enrolled during December 2020 to March 2021. All 42 patients underwent CCTA (coronary computed tomography angiography) reexaminations using GE Revolution CT machine. The standard algorithm(Stand) and bone algorithm(Bone) were used to reconstruct the original data, combined with the iterative reorganization technology ASIR-V weight (30%, 60%). So there were four groups images, including S30 (Stand-30%)、S60 (Stand-60%)、B30 (Bone-30%) and B60 (Bone-60%). The image quality of four groups (S30/S60, B30/B60, S30/B30 and S60/B60) was evaluated by subjective (liket5 score method) and objective (quantitative measurement of image signal-to-noise ratio, contrast-to-noise ratio, and difference in CT value between stent lumen and descending aorta), respectively. Results: In terms of subjective evaluation, the scores of S30, S60 were 3.54±0.60, 3.51±0.60, which were much lower than those of B30, and B60 (4.15±0.67, 4.49±0.56), respectively. There was significant difference between B60 and B30 in the bone algorithm group(P<0.05), but there was no significant difference between S60 and S30 in standard algorithm group (P>0.05). In terms of objective evaluation, S60 had the highest scores (SNR: 18.3±2.56, CNR: 26.3±6.35). For CT difference values between stent lumen and descending aorta, there was no significant difference between S30 and S60, and between B30 and B60(P>0.05), while there was significant difference between S30 and B30, S60 and B60(P<0.05), and the difference of B60 was the least (36.41±79.37). Conclusions: Bone algorithm combined with the ASIR-V weight of 60% is conducive to display of the coronary stent lumen and stent wall, and may provide higher quality images for the clinical practice.

Key words: Coronary artery, Stents, Adaptive statistical iterative reconstruction, Bone algorithm

中图分类号:

R541.7

黄琼, 吴梦雄, 董海鹏, 严福华, 张雪坤. 基于骨重建算法结合ASIR-V在冠状动脉支架成像中的应用研究[J]. 诊断学理论与实践, 2022, 21(01): 68-73.

HUANG Qiong, WU Mengxiong, DONG Haipeng, YAN Fuhua, ZHANG Xuekun. Study on application of bone algorithm combined with ASIR-V in coronary stent imaging[J]. Journal of Diagnostics Concepts & Practice, 2022, 21(01): 68-73.

图/表 5

表1

表2

图1

图2

表3

参考文献 18

[1]	王艳, 姚新宇, 苏壮志, 等. 高级的基于模型的迭代重建对冠脉支架显示的影响[J]. 中国医疗设备, 2016, 31(12):49-52,59.
	Wang Y, Yao XY, Su ZZ, et al. Effect of advanced model-based iterative reconstruction on coronary stent display[J]. China Med Equip, 2016, 31(12):49-52,59.
[2]	Katz G, Harchandani B, Shah B. Drug-eluting stents: the past, present, and future[J]. Curr Atheroscler Rep, 2015, 17(3):485.
[3]	Pendyala L, Jabara R, Shinke T, et al. Drug-eluting stents: present and future[J]. Cardiovasc Hematol Agents Med Chem, 2008, 6(2):105-115. doi: 10.2174/187152508783955051 URL
[4]	André F, Fortner P, Vembar M, et al. Improved image quality with simultaneously reduced radiation exposure: Knowledge-based iterative model reconstruction algorithms for coronary CT angiography in a clinical setting[J]. J Cardiovasc Comput Tomogr, 2017, 11(3):213-220. doi: 10.1016/j.jcct.2017.02.007 URL
[5]	Lehmkuhl L, Gosch D, Nagel HD, et al. Quantification of radiation dose savings in cardiac computed tomography using prospectively triggered mode and ECG pulsing: a phantom study[J]. Eur Radiol, 2010, 20(9):2116-2125. doi: 10.1007/s00330-010-1767-x
[6]	Hoe J, Toh KH. First experience with 320-row multidetector CT coronary angiography scanning with prospective electrocardiogram gating to reduce radiation dose[J]. J Cardiovasc Comput Tomogr, 2009, 3(4):257-261. doi: 10.1016/j.jcct.2009.05.013 URL
[7]	Hirai N, Horiguchi J, Fujioka C, et al. Prospective versus retrospective ECG-gated 64-detector coronary CT angiography: assessment of image quality, stenosis, and radiation dose[J]. Radiology, 2008, 248(2):424-430. doi: 10.1148/radiol.2482071804 URL
[8]	Scheffel H, Alkadhi H, Leschka S, et al. Low-dose CT coronary angiography in the step-and-shoot mode: diagnostic performance[J]. Heart, 2008, 94(9):1132-1137. doi: 10.1136/hrt.2008.149971 pmid: 18519548
[9]	Güler E, Vural V, ünal E, et al. Effect of iterative reconstruction on image quality in evaluating patients with coronary calcifications or stents during coronary computed tomography angiography: a pilot study[J]. Anatol J Cardiol, 2016, 16(2):119-124. doi: 10.5152/akd.2015.5920 pmid: 26467371
[10]	Pontone G, Muscogiuri G, Andreini D, et al. Impact of a New Adaptive Statistical Iterative Reconstruction (ASIR)-V Algorithm on Image Quality in Coronary Computed Tomography Angiography[J]. Acad Radiol. 2018 Oct; 25(10):1305-1313. doi: 10.1016/j.acra.2018.02.009 URL
[11]	Stehli J, Fuchs TA, Singer A, et al. First experience with single-source, dual-energy CCTA for monochromatic stent imaging[J]. Eur Heart J Cardiovasc Imaging, 2015, 16(5):507-512. doi: 10.1093/ehjci/jeu282 pmid: 25525062
[12]	Leipsic J, Labounty TM, Heilbron B, et al. Adaptive statistical iterative reconstruction: assessment of image noise and image quality in coronary CT angiography[J]. AJRl, 2010, 195(3):649-654.
[13]	杨帆, 王彦懿, 金士琪, 等. CCTA双低扫描对冠脉支架显示影响的实验研究[J]. 放射学实践, 2017, 32(1):28-32.
	Qin Le, Gu Shengjia, Chen Chihua, et al. Study on optimal single level image of coronary stent based on dual detector spectral CT[J]. Chin J Radiol, 2020, 54(6):508-513.
[14]	Gaspar T, Halon DA, Lewis BS, et al. Diagnosis of coronary in-stent restenosis with multidetector row spiral computed tomography[J]. J Am Coll Cardiol, 2005, 46(8):1573-1579. pmid: 16226187
[15]	Amanuma M, Kondo T, Sano T, et al. Assessment of coronary in-stent restenosis: value of subtraction coronary computed tomography angiography[J]. Int J Cardiovasc Imaging, 2016, 32(4):661-670. doi: 10.1007/s10554-015-0826-4 pmid: 26662268
[16]	Mahnken AH. CT Imaging of Coronary Stents: Past, Present, and Future[J]. ISRN Cardiol, 2012, 2012:139823.
[17]	Zhou Q, Jiang B, Dong F, et al. Computed tomography coronary stent imaging with iterative reconstruction: a trade-off study between medium kernel and sharp kernel[J]. J Comput Assist Tomogr, 2014, 38(4):604-612. doi: 10.1097/RCT.0000000000000080 URL
[18]	Hou Y, Ma Y, Fan W, et al. Diagnostic accuracy of low-dose 256-slice multi-detector coronary CT angiography using iterative reconstruction in patients with suspected coronary artery disease[J]. Eur Radiol, 2014, 24(1):3-11. doi: 10.1007/s00330-013-2969-9 URL

位置	1级	2级	3级	4级
左主干（2枚）	2	0	0	0
左前降支（29枚）	19	6	3	1
左回旋支（8枚）	5	1	2	0
钝缘支（1枚）	1	0	0	0
右冠状动脉（14枚）	10	1	2	1

分组	客观评价			主观评价
分组	SNR（分）	CNR（分）	支架内管腔-降主动脉 CT值差值（HU）	支架显示评分（分）
Stand-30%	16.19±2.91	22.12±5.60	57.37±85.35	3.54±0.60
Stand-60%	18.34±2.56	26.30±6.35	57.10±82.11	3.51±0.60
Bone-30%	6.81±1.95	8.63±1.91	37.03±66.03	4.15±0.67
Bone-60%	9.75±1.55	13.32±2.85	36.41±79.37	4.49±0.56
P值	<0.05	<0.05	<0.05	<0.05

支架直径（mm）	数量（个）	S30	S60	B30	B60
<3.0	7	2.87±0.34	2.91±0.38	3.27±0.24	3.38±0.25
3.0~4.0	39	3.18±0.47	3.29±0.41	4.12±0.36	4.27±0.39
≥4.0	6	3.65±0.40	3.67±0.38	4.25±0.41	4.53±0.42