Advanced Ultrasound in Diagnosis and Therapy ›› 2023, Vol. 7 ›› Issue (3): 217-227.doi: 10.37015/AUDT.2023.230030

• Review Articles • Previous Articles     Next Articles

Artificial Intelligence-assisted Medical Imaging in Interventional Management of Valvular Heart Disease

Wenwen Chen, BSa,b,c, Yuji Xie, MDa,b,c, Zisang Zhang, MDa,b,c, Ye Zhu, MSa,b,c, Yiwei Zhang, MDa,b,c, Shuangshuang Zhu, MD, PhDa,b,c, Chun Wu, MD, PhDa,b,c, Ziming Zhang, MDa,b,c, Xin Yang, PhDa,b,c, Man wei Liu, MD, PhDa,b,c, Mingxing Xie, MD, PhDa,b,c,*(), Li Zhang, MD, PhDa,b,c,*()   

  1. a Department of Ultrasound, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
    b Clinical Research Center for Medical Imaging in Hubei Province, Wuhan, China
    c Hubei Province Key Laboratory of Molecular Imaging, Wuhan, China
  • Received:2023-04-08 Revised:2023-04-16 Accepted:2023-07-27 Online:2023-09-30 Published:2023-10-09
  • Contact: Mingxing Xie, MD, PhD, Li Zhang, MD, PhD,;


The integration of medical imaging and artificial intelligence (AI) has revolutionized interventional therapy of valvular heart diseases (VHD), owing to rapid development in multimodality imaging and healthcare big data. Medical imaging techniques, such as echocardiography, cardiovascular magnetic resonance (CMR) and computed tomography (CT), play an irreplaceable role in the whole process of pre-, intra- and post-procedural intervention of VHD. Different imaging techniques have unique advantages in different stages of interventional therapy. Therefore, single imaging technique can’t fully meet the requirements of complicated clinical scenarios. More importantly, a single intraoperative image provides only limited vision of the surgical field, which could be a potential source for unsatisfactory prognosis. Besides, the non-negligible inter- and intra-observer variability limits the precise quantification of heart valve structure and function in daily clinical practice. With the help of analysis clustered and regressed by big data and exponential growth in computing power, AI broken grounds in the interventional therapy of VHD, including preoperative planning, intraoperative navigation, and postoperative follow-up. This article reviews the state-of-the-art progress and directions in the application of AI for medical imaging in the interventional therapy of VHD.

Key words: VHD; AI; Machine learning; Medical imaging