冠状动脉周围脂肪组织影像组学的研究进展
Journal: Basic Medical Theory Research DOI: 10.12238/bmtr.v6i4.8517
Abstract
冠状动脉疾病是全球范围内的主要死亡原因之一,而急性冠脉综合征(acute coronary syndromes,ACS)则是其中最为严重的类型之一。ACS的发生主要是由于冠状动脉粥样硬化斑块破裂,进而导致血栓形成,具有起病急、病情发展迅速以及高病死率的特点,也是导致患者发生不良心血管事件(major adverse cardiovascular event,MACE)的主要病因[1]。对ACS患者进行MACE的风险评估和预测,对于降低MACE的发生率和患者的死亡率尤为重要。根据前人现有的文献资源,结合最新前沿技术,探究冠周脂肪影像组学及高危斑块在冠心病中的应用。为临床诊断、治疗以及预后提供有意义的指导价值。
Keywords
冠状动脉疾病;冠状动脉周围脂肪组织影像组学;急性冠脉综合征;不良心血管事件
Full Text
PDF - Viewed/Downloaded: 0 TimesReferences
[1] 刘震,韩金花.64层螺旋CT对急性冠脉综合征患者斑块成分的临床研究[J].中国CT和MRI杂志,2017,15(10):84-87.
[2] The S.CT coronary angiography in patients with suspec ted angina due to coronary heart disease(SCOT-HEART):an open -label,parallel-group,multicentre trial[J].The Lancet,2015, 385(9985):2383-2391.
[3] 杨炜琦,周伯良.50岁以下女性急性冠脉综合征患者危险因素及冠状动脉病变特点[J].贵州医药,2017,41(02):169-171.
[4] Goeller M,Tamarappoo B K,Kwan A C,et al. Relationship between changes in pericoronary adipose tissue attenuation and coronary plaque burden quantified from coronary compu ted tomography angiography[J].European Heart Journal-Cardi ovascular Imaging,2019,20(6):636-643.
[5] 陶青,邹伟婕,范艳芬,等.冠状动脉周围脂肪直方图参数鉴别急性冠状动脉综合征及稳定性冠心病的价值初探[J].中华放射学杂志,2020,54(3):192-197.
[6] Oikonomou E K Marwan M, Desai M Y,et al.Non-invasive detection of coronary inflammation using computed tomogra phy and prediction of residual cardiovascular risk (the CRISP CT study):a post-hoc analysis of prospective outcome data[J]. The Lancet,2018,392(10151):929-939.
[7] Kolossváry M, Park J, Bang J I,etal.Identification of invasive and radionuclide imaging markers of coronary plaque vulnerability using radiomic analysis of coronary computed tomography angiography[J]. European Heart Journal-Cardiova scular Imaging,2019,20(11):1250-1258.
[8] Goeller M, Achenbach S, Cadet S, et al. Pericoronary adipose tissue computed tomography attenuation and highrisk plaque characteristics in acute coronary syndrome comp ared with stable coronary artery disease[J]. JAMA cardiology, 2018,3(9):858-863.
[9] Antonopoulos A S, Sanna F, Sabharwal N, et al. Detecting human coronary inflammation by imaging perivascular fat[J].Science translational medicine,2017,9(398):eaal2658.
[10] Oikonomou E K,Marwan M, Desai M Y, et al. Non-invasive detection of coronary inflammation using computed tomograp hy and prediction of residual cardiovascular risk (the CRISP CT study): a post-hoc analysis of prospective outcome data[J]. The Lancet,2018,392(10151):929-939.
[11] Lin A, Dey D, Wong D T L, et al. Perivascular adipose tissue and coronary atherosclerosis: from biology to imaging phenoty**[J].Current atherosclerosis reports,019,21:1-12.
[12] 史晓喆,陶欣慰,胡秀华,等.引起冠状动脉功能学缺血性的斑块特征分析[J].临床放射学杂志,2022,41(05):886-891.
[13] Wen D,XuZ,An R,etal.Predicting haemodynamic signif icance of coronary stenosis with radiomics-based pericorona ry adipose tissue characteristics[J].Clinical Radiology,2022,77(2):e154-e161.
[14] Mancio J, Oikonomou E K, Antoniades C. Perivascular adipose tissue and coronary atherosclerosis[J]. Heart, 2018,104(20):1654-1662.
[15] Kwon O, Kang S J, Kang S H, et al. Relationship between serum inflammatory marker levels and the dynamic changes in coronary plaque characteristics after statin therapy[J]. Circulation: Cardiovascular Imaging, 2017,10(7): e005934.
[16] Antonopoulos A S,Sanna F,Sabharwal N,et al. Detecting human coronary inflammation by imaging perivascular fat[J]. Science translational medicine, 2017, 9(398): eaal2658.
[17] Gillies R J, Kinahan P E, Hricak H. Radiomics: images are more than pictures, they are data[J]. Radiology, 2016,278 (2):563-577.
[18] Oikonomou E K,Williams M C,Kotanidis C P,etal.A novel machine learning-derived radiotranscriptomic signature of perivascular fat improves cardiac risk prediction using coron ary CT angiography[J].European Heart Journal, 2019,40(43):3529-3543.
[19] 尚靳,郭妍,马跃,等.基于CCTA的冠状动脉周围脂肪组织影像组学特征预测急性冠状动脉综合征[J].国际医学放射学杂志,2021,44(05):504-510.
[20] Lin A, Nerlekar N, Yuvaraj J,etal. Pericoronary adipose tissue computed tomography attenuation distinguishes differ ent stages of coronary artery disease: a cross-sectional study[J].European Heart Journal-Cardiovascular Imaging,2021, 22(3):298-306.
[21] Si N, Shi K, Li N, et al. Identification of patients with acute myocardial infarction based on coronary CT angiography: the value of pericoronary adipose tissue radiomics[J]. Europ ean Radiology,2022,32(10):6868-6877.
[2] The S.CT coronary angiography in patients with suspec ted angina due to coronary heart disease(SCOT-HEART):an open -label,parallel-group,multicentre trial[J].The Lancet,2015, 385(9985):2383-2391.
[3] 杨炜琦,周伯良.50岁以下女性急性冠脉综合征患者危险因素及冠状动脉病变特点[J].贵州医药,2017,41(02):169-171.
[4] Goeller M,Tamarappoo B K,Kwan A C,et al. Relationship between changes in pericoronary adipose tissue attenuation and coronary plaque burden quantified from coronary compu ted tomography angiography[J].European Heart Journal-Cardi ovascular Imaging,2019,20(6):636-643.
[5] 陶青,邹伟婕,范艳芬,等.冠状动脉周围脂肪直方图参数鉴别急性冠状动脉综合征及稳定性冠心病的价值初探[J].中华放射学杂志,2020,54(3):192-197.
[6] Oikonomou E K Marwan M, Desai M Y,et al.Non-invasive detection of coronary inflammation using computed tomogra phy and prediction of residual cardiovascular risk (the CRISP CT study):a post-hoc analysis of prospective outcome data[J]. The Lancet,2018,392(10151):929-939.
[7] Kolossváry M, Park J, Bang J I,etal.Identification of invasive and radionuclide imaging markers of coronary plaque vulnerability using radiomic analysis of coronary computed tomography angiography[J]. European Heart Journal-Cardiova scular Imaging,2019,20(11):1250-1258.
[8] Goeller M, Achenbach S, Cadet S, et al. Pericoronary adipose tissue computed tomography attenuation and highrisk plaque characteristics in acute coronary syndrome comp ared with stable coronary artery disease[J]. JAMA cardiology, 2018,3(9):858-863.
[9] Antonopoulos A S, Sanna F, Sabharwal N, et al. Detecting human coronary inflammation by imaging perivascular fat[J].Science translational medicine,2017,9(398):eaal2658.
[10] Oikonomou E K,Marwan M, Desai M Y, et al. Non-invasive detection of coronary inflammation using computed tomograp hy and prediction of residual cardiovascular risk (the CRISP CT study): a post-hoc analysis of prospective outcome data[J]. The Lancet,2018,392(10151):929-939.
[11] Lin A, Dey D, Wong D T L, et al. Perivascular adipose tissue and coronary atherosclerosis: from biology to imaging phenoty**[J].Current atherosclerosis reports,019,21:1-12.
[12] 史晓喆,陶欣慰,胡秀华,等.引起冠状动脉功能学缺血性的斑块特征分析[J].临床放射学杂志,2022,41(05):886-891.
[13] Wen D,XuZ,An R,etal.Predicting haemodynamic signif icance of coronary stenosis with radiomics-based pericorona ry adipose tissue characteristics[J].Clinical Radiology,2022,77(2):e154-e161.
[14] Mancio J, Oikonomou E K, Antoniades C. Perivascular adipose tissue and coronary atherosclerosis[J]. Heart, 2018,104(20):1654-1662.
[15] Kwon O, Kang S J, Kang S H, et al. Relationship between serum inflammatory marker levels and the dynamic changes in coronary plaque characteristics after statin therapy[J]. Circulation: Cardiovascular Imaging, 2017,10(7): e005934.
[16] Antonopoulos A S,Sanna F,Sabharwal N,et al. Detecting human coronary inflammation by imaging perivascular fat[J]. Science translational medicine, 2017, 9(398): eaal2658.
[17] Gillies R J, Kinahan P E, Hricak H. Radiomics: images are more than pictures, they are data[J]. Radiology, 2016,278 (2):563-577.
[18] Oikonomou E K,Williams M C,Kotanidis C P,etal.A novel machine learning-derived radiotranscriptomic signature of perivascular fat improves cardiac risk prediction using coron ary CT angiography[J].European Heart Journal, 2019,40(43):3529-3543.
[19] 尚靳,郭妍,马跃,等.基于CCTA的冠状动脉周围脂肪组织影像组学特征预测急性冠状动脉综合征[J].国际医学放射学杂志,2021,44(05):504-510.
[20] Lin A, Nerlekar N, Yuvaraj J,etal. Pericoronary adipose tissue computed tomography attenuation distinguishes differ ent stages of coronary artery disease: a cross-sectional study[J].European Heart Journal-Cardiovascular Imaging,2021, 22(3):298-306.
[21] Si N, Shi K, Li N, et al. Identification of patients with acute myocardial infarction based on coronary CT angiography: the value of pericoronary adipose tissue radiomics[J]. Europ ean Radiology,2022,32(10):6868-6877.
Copyright © 2024 刘靖琳, 赵彬, 王胜林
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License