Yuehong Zheng, MD; Rong Zeng, MD; Zhili Liu, MD; Fangda Li, MD; Hui Zhang, MD; Chuxiang Lei; Jinrui Ren; Xiaoning Sun, MD; Guangchao Gu, MD; Haoxuan Kan, Jiawei Zhou, Zijian Wang | Peking Union Medical College Hospital, Chinese Academy of Medical Sciences
Competition Sponsor: Chinese Academy of Medical Sciences
Award year: 2021
Thoracic-abdominal aortic aneurysm (TAAA) is an aneurysm involving the aorta, multiple visceral arteries in the thoracic and abdominal segments, and the blood supply arteries of the spinal cord. It is more common in elderly patients, and is characterized by challenging surgical treatment, high incidence of serious complications such as paraplegia, and large individual heterogeneity. In response to this, there is currently a lack of TAAA’s precise diagnosis and treatment decision-making system and a mature patient management system. Therefore, there is an urgent need to efficiently integrate clinical case data, diagnosis and treatment experience, and basic research data to develop a TAAA precision diagnosis and treatment system to provide important references for disease supervision, treatment decision-making, and patient management to improve the level of disease diagnosis and treatment.
This project intends to use the database architecture of the panoramic data cloud platform to integrate clinical data, blood flow simulation parameters, omics analysis results, and use intelligent platform machine learning methods to establish a precise diagnosis and treatment system for TAAAs, including disease management systems, clinical decision-making systems, technology optimization systems, and device development systems.
On the basis of this system, optimize the disease diagnosis and treatment process and the patient’s in- and out-of-hospital management mode, improve the intracavitary technology, develop new monitors and drug treatment targets. Through the promotion of this system, we can improve the level of diagnosis and treatment of TAAA in China, improve the quality of life of patients, and reduce related medical expenses.