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学术报告:Cardiovascular Modeling and Function: From Bench to Bedside


发布日期:2015-11-09 浏览数:

时间:2015年11月12日下午2:30
  地点:信工楼E301
  讲座人:Liang Zhong, 博士(1National Heart Research Institute of Singapore, National Heart Centre Singapore;2Duke-NUS Graduate Medical School, Cardiovascular and Metabolic Disorders Programme)
  简介:
Heart failure (HF) is a major health care burden on society and suffering for the individual. In the United States, HF affects 5 million patients, and it is the leading cause of hospitalization for people 65 years and rates of hospital readmission within 6 months range from 25% to 50%. In Singapore, it accounted for 4.5% of all hospital admissions and 2.5% of overall mortality in the geriatric age group. It confers an annual mortality of 10%.
Heart failure (HF) can occur with either preserved or reduced left ventricular (LV) ejection fraction (EF), depending on different degrees of cardiac remodelling. Cardiac remodelling can be defined as changes in shape, size and function of the heart due to the physiological and pathological conditions (e.g., after heart attack). Quantification of cardiac remodelling is important both for HF diagnosis and monitoring of progress in clinical cardiology.
Extensive research by Dr Zhong’ group has developed a suite of heart image analysis technologies to detect and track the progression of heart disease such as myocardial infarction, hypertrophic cardiomyopathy, congenital heart disease and heart failure. The technology enables segment automatically, reconstruct three-dimensional cardiac structure and derive quantitative measures to assess the cardiac remodelling (i.e., curvedness, wall stress and area strain). The technology is a user-friendly platform with accurate and robust algorithms. The complete computational pipeline involves a series of complex algorithmic procedures: (1) 3D synthesis, (2) data processing and curation, (3) generation of geometrical dynamics, (4) analysis processes, and (5) generation of cardiac indices. The technology has been used in a wide range of cardiac-related applications, such as i) assessment of left ventricular remodelling in patients with ischemic cardiomyopathy and in patients after myocardial infarction, ii) assessment of right ventricular remodelling in congenital heart disease, iii) quantification of ventricular dyssynchrony, and iv) evaluation of surgical efficacy in heart failure.
The technology greatly reduces the time a radiologist or cardiologist spends in analysing cardiac images. It produces comprehensive curvedness-based measures of cardiac remodelling. Incorporating such a technology into the clinical management pathways may improve treatment choice and prognostication, potentially reducing overall healthcare costs.

南昌大学科技处
信息工程学院
2015年11月9日

 

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