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中华医学超声杂志(电子版) ›› 2025, Vol. 22 ›› Issue (09) : 794 -799. doi: 10.3877/cma.j.issn.1672-6448.2025.09.002

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超声新技术助力动脉粥样硬化管理范式转变
袁丽君()   
  1. 710038 西安,空军军医大学唐都医院超声诊断科
  • 收稿日期:2025-08-07 出版日期:2025-09-01
  • 通信作者: 袁丽君
  • 基金资助:
    国家自然科学基金面上项目(82272010); 陕西省重点研发计划-重点产业创新链(群)项目(2023-ZDLSF-22); 陕西省三秦英才特殊支持计划创新创业团队项目

New ultrasound technologies facilitate paradigm shift in atherosclerosis management

Lijun Yuan()   

  • Received:2025-08-07 Published:2025-09-01
  • Corresponding author: Lijun Yuan
引用本文:

袁丽君. 超声新技术助力动脉粥样硬化管理范式转变[J/OL]. 中华医学超声杂志(电子版), 2025, 22(09): 794-799.

Lijun Yuan. New ultrasound technologies facilitate paradigm shift in atherosclerosis management[J/OL]. Chinese Journal of Medical Ultrasound (Electronic Edition), 2025, 22(09): 794-799.

1
中华心血管病杂志(网络版)编辑委员会. 动脉粥样硬化斑块的筛查与临床管理专家共识 [J]. 中华心血管病杂志(网络版), 2022, 5(1): 1-13.
2
Groenewegen KA, Den Ruijter HM, Pasterkamp G, et al. Vascular age to determine cardiovascular disease risk: A systematic review of its concepts, definitions, and clinical applications [J]. Eur J Prev Cardiol, 2016, 23(3): 264-274.
3
Nielsen RV, Fuster V, Bundgaard H, et al. Personalized intervention based on early detection of atherosclerosis: JACC state-of-the-art review [J]. J Am Coll Cardiol, 2024, 83(21): 2112-2127.
4
Chirinos JA, Segers P, Hughes T, et al. Large-artery stiffness in health and disease: JACC state-of-the-art review [J]. J Am Coll Cardiol, 2019, 74(9): 1237-1263.
5
Safar ME, Asmar R, Benetos A, et al. Interaction Between Hypertension and Arterial Stiffness [J]. Hypertension, 2018, 72(4): 796-805.
6
Custodis F, Schirmer SH, Baumhakel M, et al. Vascular pathophysiology in response to increased heart rate [J]. J Am Coll Cardiol, 2010, 56(24): 1973-1983.
7
中华医学会心血管病学分会, 中国康复医学会心脏预防与康复专业委员会, 中国老年学和老年医学会心脏专业委员会, 等. 中国心血管病一级预防指南 [J]. 中华心血管病杂志, 2020, 48(12): 1000-1038.
8
Segers P, Rietzschel ER, Chirinos JA. How to measure arterial stiffness in humans [J]. Arterioscler Thromb Vasc Biol, 2020, 40(5): 1034-1043.
9
Williams B, Mancia G, Spiering W, et al. 2018 ESC/ESH Guidelines for the management of arterial hypertension: The Task Force for the management of arterial hypertension of the European Society of Cardiology and the European Society of Hypertension: The Task Force for the management of arterial hypertension of the European Society of Cardiology and the European Society of Hypertension [J]. J Hypertens, 2018, 36(10): 1953-2041.
10
Oztekin U, Turan Y, Selmi V. The association between high-grade varicocele and endothelial dysfunction [J]. Andrologia, 2019, 51(11): e13424.
11
Stoner L, Sabatier MJ. Use of ultrasound for non-invasive assessment of flow-mediated dilation [J]. J Atheroscler Thromb, 2012, 19(5): 407-421.
12
余朝萍, 刘天虎, 王宏宇. 反应性充血指数评价血管内皮功能 [J]. 心血管病学进展, 2015, 36(4): 372-375.
13
Nianyu XMS, Qiaoer GBS. Application and Progress of Ultrasound Technology in Atherosclerosis [J]. Advanced Ultrasound in Diagnosis and Therapy, 2023, 7(1): 8-15.
14
Xing C, Xie X, Wu Y, et al. Reference values of carotid intima-media thickness and arterial stiffness in Chinese adults based on ultrasound radio frequency signal: a nationwide, multicenter study [J]. Chin Med J (Engl), 2024, 137(15): 1802-1810.
15
Laurent S, Cockcroft J, Van Bortel L, et al. Expert consensus document on arterial stiffness: methodological issues and clinical applications [J]. Eur Heart J, 2006, 27(21): 2588-2605.
16
中华医学会健康管理学分会, 中华医学会检验医学分会, 中国医师协会心血管内科医师分会. 生物标志物用于体检人群心血管病风险评估的专家共识 [J]. 中华健康管理学杂志, 2022, 16(8): 505-519.
17
Xing C, Xie X, Wu Y, et al. Reference values of carotid intima-media thinkness and arterial stiffness in Chinese adults based on ultrasound radio frequency signal: A nationwide, multicenter study [J]. Chir Med J (Enql), 2024, 137(15): 1802-1810.
18
中华医学会老年医学分会. 血管衰老临床评估与干预中国专家共识(2024版) [J]. 中华老年医学杂志, 2024, 43(11): 1371-1381.
19
Williams B, Mancia G, Spiering W, et al. 2018 ESC/ESH Guidelines for the management of arterial hypertension [J]. Eur Heart J, 2018, 39(33): 3021-3104.
20
Eskurza I, Kahn ZD, Seals DR. Xanthine oxidase does not contribute to impaired peripheral conduit artery endothelium-dependent dilatation with ageing [J]. J Physiol, 2006, 571(Pt 3): 661-668.
21
中国医药教育协会血管医学专业委员会, 中华医学会北京心血管学分会血管专业学组, 北京大学医学部血管疾病社区防治中心. 中国血管健康评估系统应用指南(2018第三次报告) [J]. 中华医学杂志, 2018, 98(37): 2955-2967.
22
Babcock MC, Dubose LE, Witten TL, et al. Assessment of macrovascular and microvascular function in aging males [J]. J Appl Physiol (1985), 2021, 130(1): 96-103.
23
Donato AJ, Eskurza I, Silver AE, et al. Direct evidence of endothelial oxidative stress with aging in humans: relation to impaired endothelium-dependent dilation and upregulation of nuclear factor-kappaB [J]. Circ Res, 2007, 100(11): 1659-1666.
24
Vasan RS, Larson MG, Benjamin EJ, et al. Echocardiographic reference values for aortic root size: the Framingham Heart Study [J]. J Am Soc Echocardiogr, 1995, 8(6): 793-800.
25
D'agostino RB, Vasan RS, Pencina MJ, et al. General cardiovascular risk profile for use in primary care: the Framingham Heart Study [J]. Circulation, 2008, 117(6): 743-753.
26
Nilsson Wadstrom B, Fatehali AH, Engstrom G, et al. A vascular aging index as independent predictor of cardiovascular events and total mortality in an elderly urban population [J]. Angiology, 2019, 70(10): 929-937.
27
Tang Q, Liu S, Tao C, et al. A new method for vascular age estimation based on relative risk difference in vascular aging [J]. Comput Biol Med, 2024, 171: 108155.
28
崔伟锋, 林萍, 刘萧萧, 等. 基于机器学习的原发性高血压心血管风险预后模型 [J]. 中国老年学杂志, 2022, 42(15): 3625-3629.
29
Tamarappoo BK, Lin A, Commandeur F, et al. Machine learning integration of circulating and imaging biomarkers for explainable patient-specific prediction of cardiac events: a prospective study [J]. Atherosclerosis, 2021, 318: 76-82.
30
Hu Y, Xu H, Zhu X, et al. An exploratory study on ultrasound image denoising using feature extraction and adversarial diffusion model [J]. Med Phys, 2025, 52(10): e70023.
31
Liapi GD, Loizou CP, Pattichis CS, et al. Assessing the impact of ultrasound image standardization in deep learning-based segmentation of carotid plaque types [J]. Comput Methods Programs Biomed, 2024, 257: 108460.
32
Xu Z, Tang F, Quan Q, et al. Fair ultrasound diagnosis via adversarial protected attribute aware perturbations on latent embeddings [J]. NPJ Digit Med, 2025, 8(1): 291.
33
Teo ZL, Thirunavukarasu AJ, Elangovan K, et al. Generative artificial intelligence in medicine [J]. Nat Med, 2025, 31(10): 3270-3282.
34
Sudha S, Jayanthi KB, Rajasekaran C, et al. Convolutional neural network for segmentation and measurement of intima media thickness [J]. J Med Syst, 2018, 42(8): 154.
35
Chen QS, Bergman O, Ziegler L, et al. A machine learning based approach to identify carotid subclinical atherosclerosis endotypes [J]. Cardiovasc Res, 2023, 119(16): 2594-2606.
36
Gan H, Zhou R, Ou Y, et al. A region and category confidence-based multi-task network for carotid ultrasound image segmentation and classification [J]. IEEE J Biomed Health Inform, 2025, PP. Online ahead of print.
37
Qian C, Yang X. An integrated method for atherosclerotic carotid plaque segmentation in ultrasound image [J]. Comput Methods Programs Biomed, 2018, 153: 19-32.
38
Song J, Zou L, Li Y, et al. Combining artificial intelligence assisted image segmentation and ultrasound based radiomics for the prediction of carotid plaque stability [J]. BMC Med Imaging, 2025, 25(1): 89.
39
Hosseinzadeh Taher MR, Haghighi F, Gotway MB, et al. Large-scale benchmarking and boosting transfer learning for medical image analysis [J]. Med Image Anal, 2025, 102: 103487.
40
Pati S, Baid U, Edwards B, et al. Federated learning enables big data for rare cancer boundary detection [J]. Nat Commun, 2022, 13(1): 7346.
41
Koutsoubis N, Waqas A, Yilmaz Y, et al. Privacy-preserving federated learning and uncertainty quantification in medical imaging [J]. Radiol Artif Intell, 2025, 7(4): e240637.
42
Wang DD, Lin S, Lyu GR. Advances in the application of artificial intelligence in the ultrasound diagnosis of vulnerable carotid atherosclerotic plaque [J]. Ultrasound Med Biol, 2025, 51(4): 607-614.
43
Hu W, Gao YT, Tong N, et al. Dual Branch Network Based on Multi-Directional Feature Cross Fusion for Carotid Plaque and Vessel Co-Segmentation [J]. Biomed Signal Process Control, 2025, 109: 108033.
44
Sun P, Han H, Sun YK, et al. Intelligent handheld ultrasound improving the ability of non-expert general practitioners in carotid examinations for community populations: a prospective and parallel controlled trial [J]. Ultrasonography, 2025, 44(2): 112-123.
45
Jiang H, Zhao A, Yang Q, et al. Towards expert-level autonomous carotid ultrasonography with large-scale learning-based robotic system [J]. Nat Commun, 2025, 16(1): 7893.
46
Mihan A, Pandey A, Van Spall HG. Mitigating the risk of artificial intelligence bias in cardiovascular care [J]. Lancet Digit Health, 2024, 6(10): e749-e754.
47
Schwalbe N, Wahl B. Artificial intelligence and the future of global health [J]. Lancet, 2020, 395(10236): 1579-1586.
48
Byrne MF, Rittscher J, East JE. Synergies Among Clinicians, Academia, and Industry in the Age of Artificial Intelligence [J]. Gastroenterology, 2025, 169(3): 531-544.
49
Liu X, Cruz Rivera S, Moher D, et al. Reporting guidelines for clinical trial reports for interventions involving artificial intelligence: the CONSORT-AI extension [J]. Nat Med, 2020, 26(9): 1364-1374.
50
Cruz Rivera S, Liu X, Chan AW, et al. Guidelines for clinical trial protocols for interventions involving artificial intelligence: the SPIRIT-AI extension [J]. Nat Med, 2020, 26(9): 1351-1363.
51
Hosny A, Parmar C, Quackenbush J, et al. Artificial intelligence in radiology [J]. Nat Rev Cancer, 2018, 18(8): 500-510.
52
Zhou S, Park G, Lin M, et al. Wearable ultrasound technology [J]. Nat Rev Bioeng, 2025, 3(10): 835-854.
53
Jiang S, Zhang T, Zhou Y, et al. Wearable ultrasound bioelectronics for healthcare monitoring [J]. Innovation (Camb), 2023, 4(4): 100447.
54
Amado-Rey AB, Goncalves Seabra AC, Stieglitz T. Towards ultrasound wearable technology for cardiovascular monitoring: from device development to clinical validation [J]. IEEE Rev Biomed Eng, 2025, 18: 93-112.
55
Xue X, Wu H, Cai Q, et al. Flexible ultrasonic transducers for wearable biomedical applications: a review on advanced materials, structural designs, and future prospects [J]. IEEE Trans Ultrason Ferroelectr Freq Control, 2024, 71(7): 786-810.
56
Liu HC, Zeng Y, Gong C, et al. Wearable bioadhesive ultrasound shear wave elastography [J]. Sci Adv, 2024, 10(6): eadk8426.
57
wang CH, Chen XY, Wang L, et al. Bioadhesive ultrasound for long-term continuous imaging of diverse organs [J]. Science, 2022, 377(6605): 517-523.
58
Wang C, Qi B, Lin M, et al. Continuous monitoring of deep-tissue haemodynamics with stretchable ultrasonic phased arrays [J]. Nat Biomed Eng, 2021, 5(7): 749-758.
59
Wang YQ, Zou Y, Li Z. Emerging intelligent wearable devices for cardiovascular health monitoring [J]. Nano Today, 2024, 59: 102544.
60
Oh C, Kim YM, Lee T, et al. Patch-type capacitive micromachined ultrasonic transducer for ultrasonic power and data transfer [J]. Microsyst Nanoeng, 2025, 11(1): 124.
61
Jang S, Soh K, Lee C, et al. A unipolar-driven synaptic transistor for environment-adaptable vision system [J]. Nat Commun, 2025, 16(1): 7636.
62
Scicolone R, Vacca S, Pisu F, et al. Radiomics and artificial intelligence: general notions and applications in the carotid vulnerable plaque [J]. Eur J Radiol, 2024, 176: 111497.
63
Zhang H, Zhao F. Deep learning-based carotid plaque ultrasound image detection and classification study [J]. Rev Cardiovasc Med, 2024, 25(12): 454.
64
Huang Z, Cheng XQ, Liu HY, et al. Relation of carotid plaque features detected with ultrasonography-based radiomics to clinical symptoms [J]. Transl Stroke Res, 2022, 13(6): 970-982.
65
Zhang L, Lyu Q, Ding Y, et al. Texture analysis based on vascular ultrasound to identify the vulnerable carotid plaques [J]. Front Neurosci, 2022, 16: 885209.
66
Loizou CP, Pattichis CS, Pantziaris M, et al. Texture feature variability in ultrasound video of the atherosclerotic carotid plaque [J]. IEEE J Transl Eng Health Med, 2017, 5: 1800509.
67
Mitchell CC, Korcarz CE, Gepner AD, et al. Carotid artery echolucency, texture features, and incident cardiovascular disease events: the MESA study [J]. J Am Heart Assoc, 2019, 8(3): e010875.
68
Van Engelen A, Wannarong T, Parraga G, et al. Three-dimensional carotid ultrasound plaque texture predicts vascular events [J]. Stroke, 2014, 45(9): 2695-2701.
69
Lin M, Cui H, Chen W, et al. Longitudinal assessment of carotid plaque texture in three-dimensional ultrasound images based on semi-supervised graph-based dimensionality reduction and feature selection [J]. Comput Biol Med, 2020, 116: 103586.
70
Grodecki K, Geers J, Kwiecinski J, et al. Phenotyping atherosclerotic plaque and perivascular adipose tissue: signalling pathways and clinical biomarkers in atherosclerosis [J]. Nat Rev Cardiol, 2025, 22(6): 443-455.
71
De Cecco CN, Van Assen M. Can radiomics help in the identification of vulnerable coronary plaque? [J]. Radiology, 2023, 307(2): e223342.
72
Zhang YJ, Bai DN, Du JX, et al. Ultrasound-guided imaging of junctional adhesion molecule-A-targeted microbubbles identifies vulnerable plaque in rabbits [J]. Biomaterials, 2016, 94: 20-30.
73
Errico C, Pierre J, Pezet S, et al. Ultrafast ultrasound localization microscopy for deep super-resolution vascular imaging [J]. Nature, 2015, 527(7579): 499-502.
74
Demene C, Robin J, Dizeux A, et al. Transcranial ultrafast ultrasound localization microscopy of brain vasculature in patients [J]. Nat Biomed Eng, 2021, 5(3): 219-228.
75
Zhu Y, Jiang L, Zhang Q, et al. Velocity-constraint kalman filtering for enhanced bubble tracking in motion-compensated ultrasound localization microscopy [J]. Research (Wash D C), 2025, 8: 0725.
76
任俊奕, 白文坤, 郑元义. 超高分辨率超声测量兔颈动脉粥样硬化斑块内新生血管的应用价值 [J]. 医学研究杂志, 2024, 53(11): 35-39.
77
Wang T, Zhang Y, Chen J, et al. Ultrasound localization microscopy in identifying high-risk carotid plaque using low-frame-rate ultrasound imaging [J]. Ultrasound Med Biol, 2025, 52(1): 123-132.
78
Leroy H, Wang LZ, Jimenez A, et al. Assessment of microvascular flow in human atherosclerotic carotid plaques using ultrasound localization microscopy [J]. eBioMedicine, 2025, 111: 105528.
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