基于冠状动脉CT血管成像的影像组学
列线图鉴别诊断易损斑块的价值

doi:10.3877/cma.j.issn.2095-655X.2024.01.001

摘要
图/表
参考文献
相关文章 (15)

全文: PDF (3355 KB) HTML (1 KB)
输出: BibTeX | EndNote (RIS)

摘要目的探讨基于冠状动脉CT血管成像（CCTA）的影像组学列线图鉴别诊断冠状动脉疾病(CAD)患者易损斑块的价值。方法回顾性分析2018年1月至2022年12月在山西医科大学附属心血管病医院接受CCTA检查的93例CAD患者资料，共95个非钙化斑块，其中包括43个易损斑块，52个稳定斑块。以 8∶2 的比例随机将数据划分为训练集（n=76）及测试集（n=19）。应用MannWhitney U检验、相关系数法和最小绝对收缩选择算子（LASSO）回归选择最优的影像组学特征，构建影像组学模型并计算影像组学评分（Radscore）。同时，根据临床资料建立临床模型。结合临床因素和Radscore，构建影像组学列线图。采用受试者工作特征（ROC）曲线、校准曲线及决策曲线分析评估模型的性能。结果最终筛选出13个具有非零系数的最优特征。结合Radscore和临床因素的列线图模型在训练集和测试集中的AUC分别为1.000，0.922，敏感度为1.000，1.000，特异度为1.000，0.800，准确度为1.000，0.895。校准曲线显示列线图预测结果与实际结果之间具有良好的一致性。决策曲线分析表明，列线图比临床模型更具有临床应用价值。结论结合临床因素和影像组学特征的影像组学列线图能够准确、客观地鉴别诊断易损斑块，具有良好的诊断性能，可用于指导临床决策。

	服务

	把本文推荐给朋友
	加入我的书架
	加入引用管理器
	E-mail Alert
	RSS
	作者相关文章

关键词 ：斑块, 动脉粥样硬化, 冠状动脉CT血管成像, 影像组学, 列线图, 诊断,鉴别

Abstract：ObjectiveTo investigate the value of radiomics nomogram based on coronary CT angiography (CCTA) in differential diagnosis of vulnerable plaques in patients with coronary artery disease (CAD). MethodsFrom January 2018 to December 2022, 93 CAD patients who had undergone CCTA scans at the Affiliated Cardiovascular Hospital of Shanxi Medical University with complete data were enrolled. There were 95 non-calcified plaques, including 43 vulnerable plaques and 52 stable plaques. In an 8:2 ratio, the lesions were randomly separated into a training set (n=76) and a testing set (n=19). To choose radiomics features appropriate for a CCTA-image-based radiomics signature, the Mann-Whitney U test, the correlation coefficient approach, and least absolute shrinkage and selection operator (LASSO) were used, and a radiomics score (Radscore) was created. Using clinical data and CCTA findings, a clinical model was constructed. Subsequently, the separate clinical parameters and Radscore were integrated to create a radiomics nomogram. The receiver operating characteristics (ROC) curve, calibration curve, and decision curve analysis were used to evaluate the performance of the radiomics signature, clinical model, and nomogram. ResultsFinally, 13 best features with non-zero coefficients were selected. In the training and test sets, the AUC of the nomogram model combined with Radscore and clinical variables were 1.000 and 0.922, sensitivity were 1.000 and 1.000, specificity were 1.000 and 0.800, and accuracy were 1.000 and 0.895, respectively. The calibration curve demonstrated good agreement between expected and actual results. The decision curve analysis revealed that the nomogram had greater clinical application value compared to the clinical model. ConclusionCombined with clinical factors and imaging features, the radiomics nomogram can accurately and objectively identify vulnerable plaques, and has good diagnostic performance, which can be used to guide clinical decision-making.

Key words： Plaque, atherosclerotic Coronary artery computed tomography angiography Radiomics Nomogram Diagnosis, differential

收稿日期: 2023-07-07

基金资助:山西省医学重点科研项目重大科技攻关专项（2021XM04）

通讯作者: 邓勇志， Email:olympicschina@163.com

引用本文:

王林源熊鑫杨坤邓勇志. 基于冠状动脉CT血管成像的影像组学列线图鉴别诊断易损斑块的价值[J]. 中华诊断学电子杂志, 2024, 12(1): 1-8.
Wang Linyuan, Xiong Xin, Yang Kun, Deng Yongzhi. The value of radiomics nomogram based on coronary CT angiography in differential diagnosis of vulnerable plaques. zhzdx, 2024, 12(1): 1-8.

链接本文:

http://www.zhzdxzz.com/CN/10.3877/cma.j.issn.2095-655X.2024.01.001 或 http://www.zhzdxzz.com/CN/Y2024/V12/I1/1

［1］Bhatt DL，Lopes RD，Harrington RA.Diagnosis and treatment of acute coronary syndromes：a review［J］.JAMA，2022，327(7)：662-675.DOI：10.1001/jama.2022.0358. ［2］Khan MH，Rochlani Y，Yandrapalli S，et al.Vulnerable plaque：a review of current concepts in pathophysiology and imaging［J］.Cardiol Rev，2020，28(1)：3-9.DOI：10.1097/CRD.0000000000000238. ［3］Grodecki K，Cadet S，Staruch AD，et al.Noncalcified plaque burden quantified from coronary computed tomography angiography improves prediction of side branch occlusion after main vessel stenting in bifurcation lesions：results from the CT-PRECISION registry［J］.Clin Res Cardiol，2021，110(1)：114-123.DOI：10.1007/s00392-020-01658-1. ［4］Greenland P，Blaha MJ，Budoff MJ，et al.Coronary calcium score and cardiovascular risk［J］.J Am Coll Cardiol，2018，72(4)：434-447.DOI：10.1016/j.jacc.2018.05.027. ［5］van Veelen A， van der Sangen N， Delewi R， et al. Detection of vulnerable coronary plaques using invasive and non-invasive imaging modalities［J］.J Clin Med，2022，11(5):1361.DOI：10.3390/jcm11051361. ［6］Masuda T，Nakaura T，Funama Y，et al.Deep learning with convolutional neural network for estimation of the characterisation of coronary plaques：validation using IB-IVUS［J］.Radiography (Lond)，2022，28(3)：661-662.DOI：10.1016/j.radi.2022.05.002. ［7］Lee JM，Choi KH，Koo BK，et al.Prognostic implications of plaque characteristics and stenosis severity in patients with coronary artery disease［J］.J Am Coll Cardiol，2019，73(19)：2413-2424.DOI：10.1016/j.jacc.2019.02.060. ［8］Motoyama S，Ito H，Sarai M，et al.Plaque characterization by coronary computed tomography angiography and the likelihood of acute coronary events in mid-term follow-up［J］.J Am Coll Cardiol，2015，66(4)：337-346.DOI：10.1016/j.jacc.2015.05.069. ［9］Kirili HA，Schaap M，Metz CT，et al.Standardized evaluation framework for evaluating coronary artery stenosis detection，stenosis quantification and lumen segmentation algorithms in computed tomography angiography［J］.Med Image Anal，2013，17(8)：859-876.DOI：10.1016/j.media.2013.05.007. ［10］Cury RC，Abbara S，Achenbach S，et al.CAD-RADS(TM) Coronary Artery Disease-Reporting and Data System.An expert consensus document of the Society of Cardiovascular Computed Tomography (SCCT)，the American College of Radiology (ACR) and the North American Society for Cardiovascular Imaging (NASCI).Endorsed by the American College of Cardiology［J］.J Cardiovasc Comput Tomogr，2016，10(4)：269-281.DOI：10.1016/j.jcct.2016.04.005. ［11］Xu P，Xue Y，Schoepf UJ，et al.Radiomics：the next frontier of cardiac computed tomography［J］.Circ Cardiovasc Imaging，2021，14(3)：e011747.DOI：10.1161/CIRCIMAGING.120.011747. ［12］Chen Q，Pan T，Yin X，et al.CT texture analysis of vulnerable plaques on optical coherence tomography［J］.Eur J Radiol，2021（136）：109551.DOI：10.1016/j.ejrad.2021.109551. ［13］Jiang XY，Shao ZQ，Chai YT，et al.Non-contrast CT-based radiomic signature of pericoronary adipose tissue for screening non-calcified plaque［J］.Phys Med Biol，2022，67(10) DOI：10.1088/1361-6560/ac69a7. ［14］Shaw LJ，Blankstein R，Bax JJ，et al.Society of Cardiovascular Computed Tomography/North American Society of Cardiovascular Imaging-expert consensus document on coronary CT imaging of atherosclerotic plaque［J］.J Cardiovasc Comput Tomogr，2021，15(2)：93-109.DOI：10.1016/j.jcct.2020.11.002. ［15］Roth GA，Mensah GA，Johnson CO，et al.Global burden of cardiovascular diseases and risk factors，1990-2019：update from the GBD 2019 study［J］.J Am Coll Cardiol，2020，76(25)：2982-3021.DOI：10.1016/j.jacc.2020.11.010. ［16］Khan MA，Hashim MJ，Mustafa H，et al.Global epidemiology of ischemic heart disease：results from the global burden of disease study［J］.Cureus，2020，12(7)：e9349.DOI：10.7759/cureus.9349. ［17］Rothwell PM，Eliasziw M，Gutnikov SA，et al.Analysis of pooled data from the randomised controlled trials of endarterectomy for symptomatic carotid stenosis［J］.Lancet，2003，361(9352)：107-116.DOI：10.1016/s0140-6736(03)12228-3. ［18］Hoffmann U，Ferencik M，Udelson JE，et al.Prognostic value of noninvasive cardiovascular testing in patients with stable chest pain：insights from the PROMISE trial (prospective multicenter imaging study for evaluation of chest pain)［J］.Circulation，2017，135(24)：2320-2332.DOI：10.1161/CIRCULATIONAHA.116.024360. ［19］Bittencourt MS，Hulten E，Ghoshhajra B，et al.Prognostic value of nonobstructive and obstructive coronary artery disease detected by coronary computed tomography angiography to identify cardiovascular events［J］.Circ Cardiovasc Imaging，2014，7(2)：282-291.DOI：10.1161/CIRCIMAGING.113.001047. ［20］Achenbach S，Ropers D，Hoffmann U，et al.Assessment of coronary remodeling in stenotic and nonstenotic coronary atherosclerotic lesions by multidetector spiral computed tomography［J］.J Am Coll Cardiol，2004，43(5)：842-847.DOI：10.1016/j.jacc.2003.09.053. ［21］Bittner DO，Mayrhofer T，Puchner SB，et al.Coronary computed tomography angiography-specific definitions of high-risk plaque features improve detection of acute coronary syndrome［J］.Circ Cardiovasc Imaging，2018，11(8)：e007657.DOI：10.1161/CIRCIMAGING.118.007657. ［22］Theofilis P，Sagris M，Antonopoulos AS，et al.Non-invasive modalities in the assessment of vulnerable coronary atherosclerotic plaques［J］.Tomography，2022，8(4)：1742-1758.DOI：10.3390/tomography8040147. ［23］Knuuti J，Wijns W，Saraste A，et al.2019 ESC guidelines for the diagnosis and management of chronic coronary syndromes［J］.Eur Heart J，2020，41(3)：407-477.DOI：10.1093/eurheartj/ehz425. ［24］Maroules CD，Hamilton-Craig C，Branch K，et al.Coronary Artery Disease Reporting and Data System (CAD-RADS(TM))：inter-observer agreement for assessment categories and modifiers［J］.J Cardiovasc Comput Tomogr，2018，12(2)：125-130.DOI：10.1016/j.jcct.2017.11.014. ［25］Kolossváry M，Kellermayer M，Merkely B，et al.Cardiac computed tomography radiomics：a comprehensive review on radiomic techniques［J］.J Thorac Imaging，2018，33(1)：26-34.DOI：10.1097/RTI.0000000000000268. ［26］Kolossváry M，Park J，Bang JI，et al.Identification of invasive and radionuclide imaging markers of coronary plaque vulnerability using radiomic analysis of coronary computed tomography angiography［J］.Eur Heart J Cardiovasc Imaging，2019，20(11)：1250-1258.DOI：10.1093/ehjci/jez033. ［27］Kolossváry M，Karády J，Szilveszter B，et al.Radiomic features are superior to conventional quantitative computed tomographic metrics to identify coronary plaques with napkin-ring sign［J］.Circ Cardiovasc Imaging，2017，10(12)：e006843.DOI：10.1161/CIRCIMAGING.117.006843. ［28］Lin A，Kolossváry M，Cadet S，et al.Radiomics-based precision phenotyping identifies unstable coronary plaques from computed tomography angiography［J］.JACC Cardiovasc Imaging，2022，15(5)：859-871.DOI：10.1016/j.jcmg.2021.11.016. ［29］Chen Q，Pan T，Wang YN，et al.A coronary CT angiography radiomics model to identify vulnerable plaque and predict cardiovascular events［J］.Radiology，2023，307(2)：e221693.DOI：10.1148/radiol.221693. ［30］Ebersberger U，Bauer MJ，Straube F，et al.Gender differences in epicardial adipose tissue and plaque composition by coronary CT angiography：association with cardiovascular outcome［J］.Diagnostics(Basel)，2023，13(4):624.DOI：10.3390/diagnostics13040624. ［31］Andreini D，Magnoni M，Conte E，et al.Coronary plaque features on CTA can identify patients at increased risk of cardiovascular events［J］.JACC Cardiovasc Imaging，2020，13(8)：1704-1717.DOI：10.1016/j.jcmg.2019.06.019. ［32］Ridker PM，Bhatt DL，Pradhan AD，et al.Inflammation and cholesterol as predictors of cardiovascular events among patients receiving statin therapy：a collaborative analysis of three randomised trials［J］.Lancet，2023，401(10384)：1293-1301.DOI：10.1016/S0140-6736(23)00215-5.