Shengxian Tu

Dr. Shengxian Tu is a distinguished professor at the School of Biomedical Engineering, Shanghai Jiao Tong University and the director of Cardiovascular Innovative Instrument and Intelligent Computing lab at biomedical instrument institute and director of Shanghai Jiao Tong University-Pulse Medical imaging joint lab. He received his master degree in Biomedical Engineering from Shanghai Jiao Tong University in 2008. After that, he joined the Medis Applied Research group as a scientific researcher, while at the same time pursuing a PhD degree at the Division of Image Processing (LKEB), Department of Radiology, Leiden University Medical Center, the Netherlands. He graduated cum laude in February 2012. He joined Shanghai Jiao Tong University as a Faculty in 2014. He is the inventor of several patents including the methods for computation of fractional flow reserve from imaging data (QFR, OFR and UFR), which are being used for clinical decisions or studies by a number of hospitals in Europe, Asia, and America. Over the past few years he has published several articles in the leading cardiovascular journals such as Lancet, Eur Heart J, J Am Coll Cardiol, J Am Coll Cardiol Interv, and Circ Cardiovasc Interv. In 2014 he was accepted as a Fellow of European Society of Cardiology (FESC) and in 2017 he was accepted as a Fellow of American College of Cardiology (FACC). Currently, he serves as an associate editor of the International Journal of Cardiovascular Imaging and section editor of JACC: Asia. So far, he has coauthored more than 100 peer-reviewed papers and 30 patents.

cardiovascular imaging and quantitative analysis, vascular hemodynamics, coronary intervention, fractional flow reserve, shear stress, optical coherence tomography, artificial intelligence.

1.  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]

2. 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. JACC: Cardiovascular Interventions. 2023,16(9):1039-1049. [view]

3. 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]

4. 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]

5. 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]

6. 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]

7. 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]

8. 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; 3982149-2159. [view

9. 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]

10. 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]

11. 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]

12. 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]

13. 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]

14. 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]

15. 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]

16. 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 CardiolInterv 2016; 9:2024–35. [view]

17. 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]

18. 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 modera


address:Med-X研究院 123室