【2023】MRI-PlaqueView支持文献汇总


编者按:MRI-PlaqueView软件,可以对斑块成分进行量化可视化分析,在斑块诊断,疗效评估,以及优化治疗方案方面应用价值巨大从科学研究到临床应用,从期刊论文到硕士博士学位论文,从中国到世界各地(美国以及欧亚各国等),MRI-PlaqueView持续为全球学者提供先进的斑块分析技术并取得了丰硕成果,现做简要整理,以飨读者。(Update Date: 2023-06-30)




部分解读
2023年上半年,中国医生利用MRI-PlaqueView取得新进展
【中文文献】2020至今,中国医生利用MRI-PlaqueView取得新进展
中药在动脉粥样硬化治疗中的新应用,MRI-PlaqueView提供技术支持
斑块应变环境与破裂风险的关系__爱尔兰都柏林大学(2022)

MRI-PlaqueView又出科研新成果,基于真实世界评估颈动脉易损斑块的转归

MRI-PlaqueView支持文献速递:识别斑块易损特征,预测卒中险!

他汀治疗后,炎症因子与斑块负荷如何变化?MRI-PlaqueView提供技术支持

小剂量羟氯喹药物干预实验!MRI-PlaqueView提供技术支持

他汀类药物治疗后斑块消退情况如何?MRI-PlaqueView提供技术支持

糖尿病患者的颈动脉斑块NWI显著增大,多负性重构!MRI-PlaqueView提供技术支持

管腔狭窄是斑块易损性成分的重要预测因子
艾塞那肽对2型糖尿病患者颈动脉粥样硬化的影响:RCT研究
负荷超声心动图与颈动脉造影联合使用,监测斑块内新生血管
论文速递 | 3.0T磁共振颈动脉斑块高分辨成像的临床应用及炎症指标NLR在易损斑块诊断中的参考价值
论文速递 | 血清CDl47对颈动脉斑块内出血的相关性分析
有研究指出:具有某些特征的颈动脉斑块进行CAS,存在重大风险
高分辨MRI鉴别颈动脉斑块的重要意义
又找到四篇论文,MRI-PlaqueView提供技术支持

美国,意大利,瑞典,韩国争相发文,国内同行必将后来居上
国外硕果累累,国内奋起直追,MRI-PlaqueView全球应用版图
MRI-PlaqueView : 不止在中国,北欧、日韩、美国梅奥等都在用!
影响因子23!意大利实验组发文,MRI-PlaquView参与···
瑞典皇家理工学院开发诊断新方法,以MRI-PlaqueView分析结果为金标准
美国梅奥,瑞典皇家理工学院以及日本学者联合发布创新型实验结果
MRI-PlaqueView在西班牙再出科研新成果,分析范围扩大至髂股动脉
MRI-PlaqueView参与都柏林大学科研,成果在欧洲卒中组织大会分享
【科研】厉害!这个课题已经发了4篇文章了!!!
连续发文5篇,他们怎么做到的?
这个实验刚开始做,快来看看有没有借鉴价值


已发表文献列举

USA(13)

  1. Shukla, A.M., Segal, M. S., Pepine, C. J., Cheung, A. K., Shuster, J., Mohandas, R., ...& Shah, S. V. (2021). Management of Cardiovascular Disease in KidneyDisease Study: Rationale and Design. American Journal of Nephrology, 52(1),36-44.

  2. Doherty, J.R., Dahl, J. J., Kranz, P. G., El Husseini, N., Chang, H. C., Chen, N. K.,Allen, J. D., Ham, K. L., & Trahey, G. E. (2015). Comparison of AcousticRadiation Force Impulse Imaging Derived Carotid Plaque Stiffness With SpatiallyRegistered MRI Determined Composition. IEEE transactions on medicalimaging, 34(11), 2354–2365. https://doi.org/10.1109/TMI.2015.2432797

  3. PCSK9Inhibition in Patients With Symptomatic Intracranial Atherosclerosis (PINNACLE)(https://clinicaltrials.gov/ct2/show/NCT03507374)


Medical College of Wisconsin

  1. Koska, J.,Migrino, R. Q., Chan, K. C., Cooper-Cox, K., & Reaven, P. D. (2021). Theeffect of exenatide once weekly on carotid atherosclerosis in individuals withtype 2 diabetes: an 18-month randomized placebo-controlled study. Diabetescare44(6), 1385-1392.
  2. Reichert,W. B., Parrington, D., Goldstein, E., Chan, K., Kurtz, J., & Migrino, R. Q.(2019). Evaluation of Glucose Metabolic Activity of Carotid Artery PlaqueComponents: A Structural-Functional Assessment Using PET-MRI. Circulation140(Suppl_1),A14212-A14212.
  3. Migrino, R.Q., Harmann, L., Prost, R., & Bowers, M. (2010). Relating Carotid PlaqueVolume Reduction Assessed by 3T MRI with Inflammatory Cytokine Change Following6 Month Statin Treatment. Journal of the American College of Cardiology55(10S),A158-E1477.
  4. Migrino, R.Q., Bowers, M., Harmann, L., Prost, R., Doppalapudi, A., Mohyuddin, T., ...& LaDisa, J. (2009). Relationship between regional wall shear stress andcarotid plaque composition using 3 T MRI and patient-specific computationalfluid dynamics. Journal of Cardiovascular Magnetic Resonance11(1),1-316.


Mayo Clinic

  1. Huang, R.,DeMarco, J. K., Ota, H., Macedo, T. A., Abdelmoneim, S. S., Huston III, J., ...& Mulvagh, S. L. (2021). Prognostic value of intraplaque neovascularizationdetected by carotid contrast-enhanced ultrasound in patients undergoing stressechocardiography. Journal of the American Society of Echocardiography, 34(6),614-624.
  2. Brinjikji,W., DeMarco, J. K., Shih, R., Lanzino, G., Rabinstein, A. A., Hilditch, C. A.,... & Huston III, J. (2018). Diagnostic accuracy of a clinical carotidplaque MR protocol using a neurovascular coil compared to a surface coilprotocol. Journal of Magnetic Resonance Imaging, 48(5),1264-1272.


University of Washington

  1. Laugesen,E., Høyem, P., Thrysoe, S., Hansen, E. S. S., Mikkelsen, A. F. S., Kerwin, W.S., ... & Kim, W. Y. (2018). Negative carotid artery remodeling in earlytype 2 diabetes mellitus and increased carotid plaque vulnerability in obesityas assessed by magnetic resonance imaging. Journal of the AmericanHeart Association7(16), e008677.
  2. Kerwin, W.S. (2012). Carotid artery disease and stroke: assessing risk with vessel wallMRI. International Scholarly Research Notices, 2012.
  3. Ota, H.,Reeves, M. J., Zhu, D. C., Majid, A., Collar, A., Yuan, C., & DeMarco, J.K. (2010). Sex differences in patients with asymptomatic carotidatherosclerotic plaque: in vivo 3.0-T magnetic resonance study. Stroke, 41(8),1630-1635.
  4. Kerwin, W.S., Liu, F., Yarnykh, V., Underhill, H., Oikawa, M., Yu, W., Hatsukami, T. S.,& Yuan, C. (2008). Signal features of the atherosclerotic plaque at 3.0Tesla versus 1.5 Tesla: impact on automatic classification. Journal ofmagnetic resonance imaging : JMRI, 28(4), 987–995. https://doi.org/10.1002/jmri.21529



Europe(11)

  1. Catalano, Oronzo et al. “Evidence of Carotid Atherosclerosis Vulnerability Regression in Real Life From Magnetic Resonance Imaging: Results of the MAGNETIC Prospective Study.” Journal of the American Heart Association vol. 12,2 (2023): e026469. 
  2. Catalano, Oronzo et al. “Evolving determinants of carotid atherosclerosis vulnerability in asymptomatic patients from the MAGNETIC observational study.” Scientific reports vol. 11,1 2327. 27 Jan. 2021.
  3. Giannotti, Nicola et al. “Association Between 18-FDG Positron Emission Tomography and MRI Biomarkers of Plaque Vulnerability in Patients With Symptomatic Carotid Stenosis.” Frontiers in neurology vol. 12 731744. 23 Dec. 2021, doi:10.3389/fneur.2021.731744
  4. Marlevi,D., Mulvagh, S. L., Huang, R., DeMarco, J. K., Ota, H., Huston, J., ... &Urban, M. W. (2020). Combined spatiotemporal and frequency-dependent shear waveelastography enables detection of vulnerable carotid plaques as validated byMRI. Scientific reports, 10(1), 1-13.
  5. Fernández-Friera,L., Fuster, V., López-Melgar, B., Oliva, B., Sánchez-González, J., Macías, A.,Pérez-Asenjo, B., Zamudio, D., Alonso-Farto, J. C., España, S., Mendiguren, J.,Bueno, H., García-Ruiz, J. M., Ibañez, B., Fernández-Ortiz, A., & Sanz, J.(2019). Vascular Inflammation in Subclinical Atherosclerosis Detected by HybridPET/MRI. Journal of the American College of Cardiology, 73(12).
  6. Catalano,O., Cerabolini, C., Eshja, E., Bendotti, G., De Salvo, M., Aloi, T. L., ...& Pedretti, R. F. E. (2019). 3039 Vulnerability of carotid atherosclerosis:relationship with plaque location, plaque eccentricity and vessel remodelingpatterns. Insight from the the MAGNETIC observational study. EuropeanHeart Journal, 40(Supplement_1), ehz745-0006.
  7. Laugesen, E., Høyem, P., Thrysoe, S., Hansen, E. S. S., Mikkelsen, A. F. S., Kerwin, W. S., ... & Kim, W. Y. (2018). Negative carotid artery remodeling in early type 2 diabetes mellitus and increased carotid plaque vulnerability in obesity as assessed by magnetic resonance imaging. Journal of the American Heart Association, 7(16), e008677.
  8. Skagen, K.,Evensen, K., Scott, H., Krohg-Sørensen, K., Vatnehol, S. A., Hol, P. K., ...& Russell, D. (2016). Semiautomated magnetic resonance imaging assessmentof carotid plaque lipid content. Journal of Stroke and CerebrovascularDiseases, 25(8), 2004-2010.
  9. Smits, L.P. ,  Wijk, D. ,  Duivenvoorden, R. ,  Xu, D. , Yuan, C. , &  Stroes, E. S. ,et al. (2016). Manual versus automated carotid artery plaque componentsegmentation in high and lower quality 3.0 tesla mri scans. PLoS ONE, 11(12),e0164267.
  10. Engelen, A.V. , Dijk, A. V. , Truijman, M. , Klooster, R. V. , Opbroek, A. V. , & Aad,V. , et al. (2015). Multi-center mri carotid plaque component segmentationusing feature normalization and transfer learning. IEEE Transactions onMedical Imaging, 34(6), 1294-1305.
  11.  Helck, A., Bianda, N., Ganton, G., Yuan, C.,Reiser, M., Gallino, A., ... & Saam, T. (2014, April). Intra-individuellerVergleich der Plaquemorphologie in den Karotiden und Femoralarterien mithilfeder nicht-invasiven MRT-Plaquebildgebung. In RöFo-Fortschritte auf dem Gebietder Röntgenstrahlen und der bildgebenden Verfahren (Vol. 186, No. S01, p. VO302_5).



Korea(5)

  1. Song, Y.J., Kwak, H. S., Chung, G. H., & Jo, S. (2019). Quantification of CarotidIntraplaque Hemorrhage: Comparison between Manual Segmentation andSemi-Automatic Segmentation on Magnetization-Prepared Rapid Acquisition withGradient-Echo Sequences. Diagnostics9(4), 184.
  2. Jeong, J.Y., Kwak, H. S., Hwang, S. B., & Chung, G. H. (2018). The Safety ofProtected Carotid Artery Stenting in Patients with Unstable Plaque on CarotidHigh-Resolution MR Imaging. Journal of the Korean Society of Radiology78(6),380-388.
  3. Kim, S.,Kwak, H. S., & Chung, G. H. (2018). Carotid intraplaque hemorrhage inpatients with greater than fifty percent carotid stenosis was associated anacute focal cerebral infarction. Neurol Asia23,209-21.
  4. Lee, K. J.,Kwak, H. S., Chung, G. H., Hwang, S. B., & Song, J. S. (2016). Assessmentof carotid diffusion-weighted imaging for detection of lipid-rich necrotic corein symptomatic carotid atheroma. Journal of the Korean Society ofRadiology, 74(3), 160-168.
  5. Chung, G.H., Jeong, J. Y., Kwak, H. S., & Hwang, S. B. (2016). Associations betweenCerebral Embolism and Carotid Intraplaque Hemorrhage during Protected CarotidArtery Stenting. AJNR. American journal of neuroradiology, 37(4),686–691. https://doi.org/10.3174/ajnr.A4576



China(20)

  1. 杨利新, 于薇, 王占宏, 安靖, & 张天静. (2015). 磁共振单次扫描多组织对比序列对颈动脉粥样硬化斑块评价的临床初步研究. 中华老年心脑血管病杂志, 17(11), 1129-1132.
  2. 杜艳妮, 杨利新, 王艳阳,赵轶轲, 李德彪, & 于薇. (2017). 三维单次扫描多组织对比序列和磁化强度预备梯度回波序列诊断颈动脉斑块内出血的对比研究. 中华放射学杂志, 51(006), 412-416.
  3. 杜艳妮. (2017). 两种重 T1W 序列对颈动脉斑块内出血诊断的价值 (Master's thesis, 首都医科大学).
  4. Niu, P. P.,Yu, Y., Zhou, H. W., Liu, Y., Luo, Y., Guo, Z. N., ... & Yang, Y. (2016).Vessel wall differences between middle cerebral artery and basilar arteryplaque s on magnetic resonance imaging. Scientific reports, 6(1),1-7.(吉大一院)
  5. 牛朋朋. (2017). 高分辨核磁管壁成像在脑血管评估中的应用研究. (Doctoral dissertation, 吉林大学).

  6. Xia, J.,Yin, A., Li, Z., Liu, X., Peng, X., & Xie, N. (2017). Quantitative analysisof lipid-rich necrotic core in carotid atherosclerotic plaques by in vivomagnetic resonance imaging and clinical outcomes. Medical sciencemonitor: international medical journal of experimental and clinical research, 23,2745.(深圳大学第二附属医院)

  7. 郭文城,崔梅,王寻,陶虹月,余波.血清CD147对颈动脉斑块内出血的相关性分析[J].中华医学杂志,2018,98(42):3437-3441.(上海复旦大学附属华山医院)

  8. 李晓光. (2018). 3.0T磁共振颈动脉斑块高分辨成像的临床应用及炎症指标NLR在易损斑块诊断中的参考价值. (Doctoral dissertation, 延边大学).
  9. Ji, A., Lv,P., Dai, Y., Bai, X., Tang, X., Fu, C., & Lin, J. (2019). Associationsbetween carotid intraplaque hemorrhage and new ipsilateral ischemic lesionsafter carotid artery stenting: a quantitative study with conventionalmulti-contrast MRI. The international journal of cardiovascular imaging, 35(6),1047-1054.(上海复旦大学附属中山医院)
  10. 王琳婧. (2019).High-Resolution MRI在判定颅内MCA和BA斑块稳定性的研究价值.(Doctoral dissertation, 吉林大学).
  11. Sun, Y.,Xu, L., Jiang, Y., Ma, M., Wang, X. Y., & Xing, Y. (2020). Significance ofhigh resolution MRI in the identification of carotid plaque. Experimentaland Therapeutic Medicine, 20(4), 3653-3660. (吉大中日友谊医院)
  12. 孙培育, 吴娇艳, 刘梦秋,刘婕, & 刘影. (2020). 应用高分辨mri评估颈动脉斑块与体质指数的相关性. 医学影像学杂志, 030(002),182-186.(中国科学技术大学附属第一医院(安徽省立医院)磁共振室
  13. 周悦,齐恩林,吕士英 & 姜立杰.(2022).MRI评价脑卒中伴T2DM患者颈动脉粥样硬化斑块的研究. 影像科学与光化学(03),636-640.

  14. 李贺,姬寒蕊 & 吴圣贤.(2022).中药治疗颈动脉粥样硬化临床随机对照试验设计与评价技术规范(2021版)的解读. 天津中医药(04),438-442.

  15. Sun, Y.,Xu, L., Jiang, Y., Ma, M., Wang, X. Y., & Xing, Y. (2020). Significance ofhigh resolution MRI in the identification of carotid plaque. Experimentaland Therapeutic Medicine, 20(4), 3653-3660. (吉大中日友谊医院)
  16. Tang, Min et al. (2022). “Radiomics Nomogram for Predicting Stroke Recurrence in Symptomatic Intracranial Atherosclerotic Stenosis.” Frontiers in neuroscience vol. 16 851353. (陕西省人民医院,西安医科大学)
  17. Tang M, Yan X, Gao J, et al.  (2022).High-Resolution MRI for Evaluation of the Possibility of Successful Recanalization in Symptomatic Chronic ICA Occlusion: A Retrospective Study. AJNR Am J Neuroradiol. 43(8):1164-1171. (陕西省人民医院)
  18. Chen YF, Chen ZJ, Lin YY, et al. (2023). Stroke risk study based on deep learning-based magnetic resonance imaging carotid plaque automatic segmentation algorithm. Front Cardiovasc Med. (福建医科大学附属第二医院)
  19. Zhang Y, Cui B, Yang H, et al. (2023). Morphological feature and mapping inflammation in classified carotid plaques in symptomatic and asymptomatic patients: A hybrid 18F-FDG PET/MR study . Front Neurosci.(首都医科大学,宣武医院)
  20. Chen, X. X., Kong, Z. X., Wei, S. F., Liang, F., Feng, T., Wang, S. S., & Gao, J. S. (2023). Ultrasound lmaging-vulnerable plaque diagnostics: Automatic carotid plaque segmentation based on deep learning. Journal of Radiation Research and Applied Sciences.(浙江大学医学院附属杭州市西溪医院)



Meetingand news(5)

  1. Giannotti,N., McNulty, J. P., Barry, M., Crowe, M., Foley, S. J., Kavanagh, E., ... &Kelly, P. (2018, May). High-resolution MRI (HR-MRI) of atherosclerotic plaquein symptomatic carotid stenosis–relationship with risk factors, treatment, andCT angiographic features. In ESOC 2018 4th European Stroke OrganisationConference, Gothenburg, Sweden, 16-18 May 2018.
  2. vanEngelen, A., De Bruijne, M., Schneider, T., van Dijk, A. C., Kooi, M. E.,Hendrikse, J., ... & Botnar, R. M. (2017, July). Evaluating Classifiers forAtherosclerotic Plaque Component Segmentation in MRI. In AnnualConference on Medical Image Understanding and Analysis (pp. 156-168).Springer, Cham.
  3. Yoneyama, T., Sun, J., Hippe, D., Xu, D., Kerwin, W., Hatsukami, T., & Yuan, C. (2014). Is automatic analysis of multicontrast MRI ready for clinical studies on plaque tissue composition?. In Proc. Intl. Soc. Mag. Reson. Med (Vol. 22, p. 2537).
  4. Gundert, T.J., Hayden, P., Migrino, R. Q., & LaDisa Jr, J. F. (2009, June).Visualization of CFD Results in a Virtual Reality Environment. In SummerBioengineering Conference (Vol. 48913, pp. 741-742). American Societyof Mechanical Engineers.
  5. Kahn, J.Atherosclerosis and Aging—Insights Into the Role of the Endothelial Glycocalyxin Cardiovascular Health.



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