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  涂圣贤

  上海交通大学特聘教授，博士生导师，bat365中文官方网站生物医疗仪器纵主任，生物医学仪器研究所心血管创新器械与智能计算实验室主任，上海交通大学-博动医学影像技术联合实验室主任，荷兰Erasmus大学医学院客座教授。主要从事心血管成像及生理功能学评估技术的研发与临床应用研究。2012年2月获得荷兰莱顿大学优秀博士学位，2014年回国加入上海交通大学bat365中文官方网站陈亚珠院士研究团队，创建心血管影像研究方向。他发明了QFR、OFR、UFR与RWS等序列计算冠脉功能学评估技术，并主持完成这些技术的产学研与临床转化。近5年以第一作者或通讯作者（含共同）在Lancet, Nature Review Cardiology, JACC, European Heart Journal等国际知名期刊发表多篇论文。主持的项目“Real-time comprehensive assessment of coronary physiology and biomechanics from a single angiographic projection”获得2022年EuroPCR大会评选的心血管器械最佳创新奖与Jon DeHaan基金会奖金，成为该奖项设立以来首个获得殊荣的来自亚洲的项目。担任The International Journal of Cardiovascular Imaging期刊副主编，JACC: Asia期刊栏目编辑，Lancet、JACC、European Heart Journal等二十种国际期刊的审稿专家，TCT与EuroPCR等多个心血管介入临床大会的Faculty/主席团成员。获得2022年度上海市技术发明奖一等奖、2019年度教育部长江学者特聘教授、2019年度上海市优秀技术带头人，第四届转化医学创新奖等荣誉称号。

  E-mail: sxtu@sjtu.edu.cn

  电话：021-62932631

  
  

  
  

  
  

国家自然科学基金委重大科研仪器研制项目，项目名称：血管内多模态成像与生物力学分析融合系统的研制；项目编号：82327808；时间：2024/1-2028/12。主持。

国家自然科学基金重点国际合作项目，项目名称：影响冠心病患者生物可降解支架疗效的关键生物力学问题研究；项目编号：82020108015；时间：2021/1-2025/12。主持。

国家自然科学基金面上项目，项目名称：冠心病患者非靶病变快速进展与斑块破裂的生物力学机制研究；项目编号：81871460；时间：2019/1-2022/12。主持。

国家自然科学基金面上项目，项目名称：结合计算流体力学与三维光学相干断层成像评价冠心病支架治疗后的局部血流动力学；项目编号：81570456；时间：2016/1-2017/12。 主持。

国家自然科学基金青年科学基金项目，项目名称：基于冠状动脉CT血管造影评估血流储备分数与微循环阻力；项目编号：31500797；时间：2016/1-2018/12。主持。



国家重点研发计划“科技助力经济2020”重点专项，项目名称：融合光学血流分数与虚拟组织学的一站式冠心病评估系统研发和应用示范；时间：2020/7-2022/6。主持。

国家重点研发计划“数字诊疗装备研发重点专项”，项目名称：融合光学相干断层成像与血流动力学的一站式冠心病评估系统的研制；项目编号：2016YFC0100500；时间：2016/7-2018/12。主持。

1. Chu M, De Maria G*, Dai R, Benenati S, Yu W, Zhong J, Kotronias R, Walsh J, Andreaggi S, Zuccarelli V, Chai J, Oxford Acute Myocardial Infarction (OxAMI) Study, Channon K, Banning A, Tu S*. DCCAT: Dual-Coordinate Cross-Attention Transformer for thrombus segmentation on coronary OCT. Medical Image Analysis. 2024, 97: p103265. [view]
2. Fezzi S, Ding D, Mahfoud F, Huang J, Lansky AJ, Tu S*, Wijns W*. Illusion of revascularization: does anyone achieve optimal revascularization during percutaneous coronary intervention? Nature Reviews Cardiology. 2024. DOI: 10.1038/s41569-024-01014-0 [view]
3. Yang S, Wang Z, Park S, Hong H, Li C, Liu X, Chen L, Hwang D, Zhang J, Hoshino M, Yonetsu T, Shin E, Doh J, Nam C, Wang J, Chen S, Tanaka N, Matsuo H, Kubo T, Chang H, Kakuta T, Koo B*, Tu S*. Relationship of Coronary Angiography-Derived Radial Wall Strain With Functional Significance, Plaque Morphology, and Clinical Outcomes. J Am Coll Cardiol Interv 2024; 17(1): 46-56. [view]
   
4. Tu S*, Xu B*, Chen L, Hong H, Wang Z, Li C, Chu M, Song L, Guan C, Yu B, Jin Z, Fu G, Liu X, Yang J, Chen Y, Ge J, Qiao S, Wijns W, on behalf of the FAVOR III China study group. Short-term risk stratification of non–flow-limiting coronary stenosis by angiographically derived radial wall strain. J Am Coll Cardiol. 2023, 81(8):756–767. [view] 
5. Li C, Wang Z, Yang H, Hong H, Li C, Xu R, Wu Y, Zhang F, Qian J, Chen L, Tu S*, Ge J*. The Association Between Angiographically Derived Radial Wall Strain and the Risk of Acute Myocardial Infarction. J Am Coll Cardiol Interv 2023,16(9):1039-1049. [view]
6. Chu M, Wu P, Li G, Yang W, Gutiérrez-Chico JL, Tu S*. Advances in Diagnosis, Therapy, and Prognosis of Coronary Artery Disease Powered by Deep Learning Algorithms. JACC: Asia 2023; 3(1):1-14. [view]
7. Hong H#, Li C#, Gutiérrez-Chico JL, Wang Z, Huang J, Chu M, Kubo T, Chen L*, Wijns W, Tu S*.  Radial wall strain: a novel angiographic measure of plaque composition and vulnerability. EuroIntervention 2022;18(12):1001-1010. [view]
8. Song L, Xu B, Tu S, Guan C, Jin Z, Yu B, Fu G, Zhou Y, Wang J, Chen Y, Pu J, Chen L, Qu X, Yang J, Liu X, Guo L, Shen C, Zhang Y, Qi Zhang, Pan H, Zhang R, Liu J, Zhao Y, Wang Y, Dou K, Kirtane A, Wu Y, Wijns W, Yang W, Leon M, Qiao S, Stone G, FAVOR III China Study Group. 2-Year Outcomes of Angiographic Quantitative Flow Ratio-Guided Coronary Interventions. J Am Coll Cardiol 2022; 80(22):2089-2101. [view]
9. Wang Z, Xu B, Li C, Guan C, Chang Y, Xie L, Zhang S, Huang J, Serruys PW, Wijns W, Chen L*, Tu S*. Angiography-derived radial wall strain predicts coronary lesion progression in non-culprit intermediate stenosis. J Geriatr Cardiol 2022;19(12):937-948.[view]
10. Hong H#, Jia H#, Zeng M, Gutiérrez-Chico JL, Wang Y, Zeng X, Qin Y, Zhao C, Chu M, Huang J, Liu L, Hu S, He L, Chen L, Wijns W, Yu B*, Tu S*. Risk Stratification in Acute Coronary Syndrome by Comprehensive Morphofunctional Assessment With Optical Coherence Tomography. JACC: Asia 2022; 4: 460-472. [view]
11. Xu B.#*, Tu S.#, Song L.#, Jin Z., Yu B., Fu G., Zhou Y., Wang J. a., Chen Y., Pu J., Chen L., Qu X., Yang J., Liu X., Guo L., Shen C., Zhang Y., Zhang Q., Pan H., Fu X., Liu J., Zhao Y., Escaned J., Wang Y., Fearon W. F., Dou K., Kirtane A. J., Wu Y., Serruys P. W., Yang W., Wijns W., Guan C., Leon M. B., Qiao S., Stone G. W. Angiographic quantitative flow ratio-guided coronary intervention (FAVOR III China): a multicentre, randomised, sham-controlled trial. The Lancet 2021; 398：2149-2159. [view] 
12. Ding D, Huang J, Westra J, Cohen D. J, Chen Y, Andersen B. K, Holm N. R, Xu B, Tu S*, Wijns W*. Immediate post-procedural functional assessment of percutaneous coronary intervention: current evidence and future directions. Eur Heart J 2021; 42:2695-2707. [view]
13. Chu M, Jia H, Gutiérrez-Chico JL, Maehara A, Ali Z, Zeng Z, He L, Zhao C, Matsumura M, Wu P, Zeng M, Kubo T, Xu B, Chen L, Yu B, Mintz GS, Wijns W, Holm NR, Tu S*. Artificial intelligence and optical coherence tomography for the automatic characterisation of human atherosclerotic plaques.  EuroIntervention 2021; 17:41-50. [view]
14. Yu W, Tanigaki T, Ding D, Wu P, Du H, Ling Li, Huang B, Li G, Yang W, Zhang S, Yan F, Okubo M, Xu B, Matsuo H, Wijns W, Tu S*. Accuracy of Intravascular Ultrasound-based Fractional Flow Reserve in Identifying Hemodynamic Significance of Coronary Stenosis. Circ Cardiovasc Interv. 2021;14:e009840. [view]
15. Tu S*, Ding D, Chang Y, Li C, Wijns W, Xu B.  Diagnostic accuracy of quantitative flow ratio for assessment of coronary stenosis significance from a single angiographic view: A novel method based on bifurcation fractal law. Catheter Cardiovasc Interv 2021;97 Suppl 2:1040-1047.  [view]
16. Tu S^#*, Westra J^#, Adjedj J^#, Ding D, Liang F, Xu B, Holm NR, Reiber H, Wijns W. Fractional Flow Reserve in clinical practice: from wire-based invasive measurement to image-based computation. Eur Heart J 2020; 41, 3271–3279. [view]
17. Yu W, Huang H, Jia D, Chen S, Raffel OC, Ding D, Tian F, Kan J, Zhang S, Yan Y, Chen Y, Bezerra HG, Wijns W, Tu S*. Diagnostic Accuracy of Intracoronary Optical Coherence Tomography-derived Fractional Flow Reserve for Assessment of Coronary Stenosis Severity. EuroIntervention 2019;15:189-197.[view]
18. Xu B^#, Tu S^#*, Qiao S, Qu X, Chen Y, Yang J, Guo L, Sun Z, Li Z, Tian F, Fang W, Chen J, Li W, Guan C, Holm NR, Wijns W, Hu S*. Diagnostic Accuracy of the Angiography-Based Quantitative Flow Ratio for Online Assessment of Coronary Stenosis. J Am Coll Cardio 2017; 70: 3077-87.[view]
19. Tu S*, Westra J, Yang J, von Birgelen C, Ferrara A, Pellicano M, Nef H, Tebaldi M, Murasato Y, Lansky A, Barbato E, van der Heijden LC, Reiber JHC, Holm NR, Wijns W,FAVOR Pilot Trial Study Group. Diagnostic Accuracy of Fast Computational Approaches to Derive Fractional Flow Reserve From Diagnostic Coronary Angiography: The International Multicenter FAVOR Pilot Study. J Am Coll Cardiol Interv 2016; 9:2024–35. [view]
20. Li Y, Gutiérrez-Chico JL, Holm NR, Yang W, Hebsgaard L, Christiansen EH, Mæng M, Lassen JF, Yan F, Reiber JHC, Tu S*. Impact of Side Branch Modeling on Computation of Endothelial Shear Stress in Coronary Artery Disease: Coronary Tree Reconstruction by Fusion of 3D Angiography and OCT. J Am Coll Cardio 2015; 66:125-35. [view]
21. Tu S*, Barbato E, Koszegi Z, Yang J, Sun Z, Holm NR, Tar B, Li Y, Rusinaru D, Wijns W, Reiber JHC.Fractional flow reserve calculation from 3-dimensional quantitative coronary angiography and TIMIframe count: A fast computer model to quantify the functional significance of moderately obstructed coronary arteries. J Am CollCardiolInterv 2014, 7:768-777.[view]