Xiaoxin Kan

Xiaoxin Kan is a postdoctoral researcher affiliated with Fudan University, Imperial College London, and Royal Brompton Hospital. Xiaoxin's research focuses on numerical simulation of the thoracic endovascular aortic repair (TEVAR) procedure in treating aortic diseases. This virtual stent-graft deployment model includes most of the currently available commercial stent-graft devices and patient data from two clinical centres. This model will be further explored and developed as a pre-surgical planning tool in future.

Xiaoxin completed his undergraduate study in Theoretical and Applied Mechanics at Fudan University (Shanghai, China), where he started his journey in studying biomechanical problems in aortic diseases. This was followed by an MSc in Biomedical Engineering at Southampton University, with a research topic on fluid-structure simulation of the aortic valve. The following year, Xiaoxin worked as a numerical simulation engineering and research and design engineer for Microport and Medtronic, respectively, where he gained a lot of experience in medical device-related simulation.

Research Interests

My research interests include the numerical simulation of aortic diseases and the intervention procedures. My current research focuses on the virtual stent-graft deployment model in aortic dissection patients, aiming to develop it as a pre-surgical planning tool in the future.

Project title: "Predicting stent-induced new entry evolution in patient-specific Stanford B aortic dissection model". 

Selected Publications

Dr Xiaoxin Kan's publications are publicly available on Google Scholar.

• Kan, X., Ma, T., Lin, J., Wang, L., Dong, Z. and Xu, X.Y., 2021. Patient-specific simulation of stent-graft deployment in type B aortic dissection: model development and validation. Biomechanics and Modelling in Mechanobiology, pp.1-12.
• Kan, X., Ma, T., Dong, Z. and Xu, X.Y., 2021. Patient-Specific Virtual Stent-Graft Deployment for Type B Aortic Dissection: A Pilot Study of the Impact of Stent-Graft Length. Frontiers in Physiology, 12.
• Yuan, X.*, Kan, X.*, Xu, X.Y. and Nienaber, C.A., 2020. Finite element modelling to predict procedural success of thoracic endovascular aortic repair in type A aortic dissection. JTCVS Techniques, 4, pp.40-47.

Conferences

• Kan, X., Yuan, X., Salmasi, M.Y., Moore, J., Sasidharan, S., Athanasiou, A., Xu, X.Y. and Nienaber, C.A., 2021. Comprehensive Mechanical Modelling of Thoracic Endovascular Aortic Repair in Type A Aortic Dissection. Circulation, 144(Suppl_1), pp.A10478-A10478.
• Yuan, X., Kan, X., Xu, X.Y. and Nienaber, C., 2021. Identifying and quantifying the 4D motion of aortic root. Journal of the American College of Cardiology, 77(18_Supplement_1), pp.1832-1832.

Funding and Awards 

Fully funded PhD scholarship awarded by the China Scholarship Council (CSC).

Email
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