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Zhonghua Sun

John Curtin Distinguished Professor and Professor
Diagnostic and Therapeutic Sciences

Cardiovascular imaging research

Professor Zhonghua Sun is a John Curtin Distinguished Professor in the Curtin Medical School. His research focuses on diagnostic medical imaging, cardiovascular CT, 3D image visualisation, and the use of 3D printing, immersive technologies and artificial intelligence in cardiovascular disease. He is recognised globally for advancing the clinical application of these technologies and has been listed among the World Top 2 percent of Scientists in cardiovascular research since 2019. In 2024, ScholarGPS ranked him in the top 0.05 percent of experts worldwide in computed tomography angiography.      


About

Professor Zhonghua Sun is a John Curtin Distinguished Professor in Medical Imaging at Curtin University and an internationally recognised researcher in advanced medical imaging, particularly cardiovascular imaging. His research focuses on improving the diagnosis and management of cardiovascular disease through the development and application of advanced imaging technologies.


Professor Sun’s work centres on coronary CT angiography, 3D medical image visualisation, artificial intelligence in medical imaging, and the use of 3D printing and virtual reality for clinical planning and medical education. His research aims to enhance the accuracy, efficiency and clinical value of non invasive imaging techniques.


He completed his medical degree at Harbin Medical University in China and later earned a PhD in Medical Imaging from the University of Ulster in the United Kingdom. Before pursuing an academic career, he worked as a radiologist at Peking Union Medical College Hospital.


Professor Sun has published more than 500 peer reviewed papers and book chapters and his work has been widely cited internationally. He serves on the editorial boards of several international medical imaging journals and collaborates with researchers and clinical partners across Australia, Europe and Asia.


Through his research and academic leadership, Professor Sun continues to contribute to advancements in medical imaging and to improving the early detection and treatment of cardiovascular disease.


 
  • 2016- Fellow of Society of Cardiovascular Computed Tomography (FSCCT)
  • 2016-2018 Overseas Fellow of Royal Society of Medicine
  • 2017- Member of Australian Society for Medical Research
  • ]2016- Founder and Council Member of International Society of Digital Medicine
  • 2015-2017 Premium Professional Plus, American Heart Association
  • 2015-2018 Member of American Roentgen Ray Society
  • 2014- Member of Asian Society of Cardiovascular Imaging
  • 2014- Member of Society of Cardiovascular Computed Tomography
  • 2013- Member of European Atherosclerosis Society
  • 2012- Overseas Associate member of IPEM (Institute of Physics in Engineering and Medicine)
  • 2011-2013 Deputy member of Radiological Council of Western Australia
  • 2007- Associate Member of Australian Institute of Radiography
  • 2002-2004 Member of European Society of Radiology

Research Focus

Professor Zhonghua Sun focuses on advancing medical imaging technologies to improve the diagnosis and management of cardiovascular disease. His research primarily centres on cardiovascular imaging, particularly coronary CT angiography and the imaging of coronary artery disease, with an emphasis on enhancing the accuracy and diagnostic performance of non invasive imaging techniques. He also works on the development of advanced imaging technologies such as 3D medical image visualisation, image reconstruction and optimisation, and digital variance angiography. In addition, Professor Sun explores emerging digital approaches in healthcare, including artificial intelligence for automated image analysis, as well as the use of 3D printing, virtual reality and mixed reality to support surgical planning, medical training and the visualisation of complex anatomical structures. Through this work, he aims to improve imaging quality, diagnostic capability and clinical decision making in modern medicine.

Research Team

Dr Michael Ovens

Visualisation Technology Specialist

Dr Yin How Wong

Taylors University

Dr Ashu Gupta

Fiona Stanley Hospital

Chai Hong Yeong

Taylors University

Lei Xu

Capital Medical University China

Yu Li

San Yatsen University China

Publications

ABSTRACT
Lifetime management of aortic stenosis represents a growing procedural and clinical challenge. With recent clinical trials indicating that transcatheter aortic valve replacement (TAVR) is at least on par with surgical aortic valve replacement (SAVR) in treating lower risk patients, there has been a rise in TAVR uptake in younger, lower risk patients, leading to an increased likelihood of bioprosthetic valve degradation within a patient's lifetime. This shift in treatment has changed the landscape of interventional cardiology, incentivising the Heart Team to now plan for the initial procedure with subsequent interventions in mind. While traditional multi-slice computed tomography image-based risk assessments are sufficient for initial valve placement, they fall short in their ability to accurately predict post-procedural outcomes and future interventions. Therefore, the need to balance competing risks to optimise patient outcomes over multiple interventions requires innovation. CT-derived computational techniques are being developed to incorporate biomechanics and fluid dynamics into the risk assessment process to allow more comprehensive analysis of the risks associated with different procedures. The goal of this review is to provide an overview of computational techniques that are being developed for the purposes of optimising outcomes in both the index and valve-in-valve interventions and to give cardiologists an understanding of how they may use computational modelling as an additional tool in the lifetime management of aortic stenosis.


Khinsoe, G., C. Ream, A. Venkatesh, T. Sirset-Becker, E. M. De-Juan-Pardo, Z. Sun, S. L. Sellers, J. Leipsic, L. P. Dasi, and A. Ihdayhid. 2026. CT-derived computational modelling in the lifetime management of aortic stenosis.Journal of Cardiovascular Computed Tomography 20 (1): 3-12.
ABSTRACT

Microwave sintering enabled the efficient fabrication of bulk Mn3Cu0.5Ge0.5N0.9C0.1 NTE materials in 3–5 h, versus 2 to 8 days for conventional methods. The microwave approach demonstrated high efficiency and energy savings. By adjusting temperature and dwell time, the NTE operating range can be shifted to lower temperatures. Under the optimized condition of 800 °C for 4 h, the resulting bulk material achieved an NTE coefficient of −20.56 × 10−6 K−1 over a temperature interval ΔT of 88 K (from 159 K to 247 K), along with favorable densification and high hardness. The demonstrated processing efficiency, microstructural control, and tunable NTE properties establish a solid foundation for potential industrial scale-up.

Zhang, H., Y. Dai, Z. Hu, C. Han, B. Li, D. Guo, and Z. Sun. 2026. Thermal Expansion, Microstructure and Mechanical Properties of Rapid Microwave Sintering Mn3Cu0.5Ge0.5N0.9C0.1 in Nitrogen Atmosphere.Crystals 16 (1)

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