3-21Image-BasedModelingforBetterUnderstandingandAssessmentofAtheroscleroticPlaqueProgressionandVulnerability
發布時間 :2014-03-17  閱讀次數 🔽:2449
 

報告題目:  Image-Based Modeling for Better Understanding and Assessment of Atherosclerotic Plaque Progression and Vulnerability

講 演 人:  唐達林(Dalin Tang)教授

報告時間:  3月21日(星期五)14:00

報告地點:  生物樓3號樓105會議室

聯 系 人🚣‍♀️🧯: 齊穎新 This e-mail address is being protected from spambots. You need JavaScript enabled to view it. ; 13681951183

講演人簡介: 唐達林(Dalin Tang)博士,現任美國伍斯特理工EON4(Worcester Polytechnic Institute)數學和生物醫學工程終身教授,東南大學特聘教授、美國心臟學會會士(AHA Fellow)、ASME-JBiomech Eng 副主編等。長期從事心血管疾病臨床與基礎研究,先後發表學術論文200 余篇;2010 年獲WPI 最佳科學研究教授獎、2008 年獲WPI 軟件開發獎(KalenianAward),2007 年代表美國數學學會向美國國會報告以醫學圖像為基礎的心血管疾病計算力學分析診斷方法的研究成果🛌🏼。美國NIH 曾發表專文高度評價其在心血管疾病的計算力學分析診斷方法的貢獻🤽🏼‍♂️,眾多媒體多次轉載報道其最新的研究進展🧑🏻‍🦯。

Abstract: Medical imaging and image-based modeling have made considerable progress in recent years in identifying atherosclerotic plaque morphological and mechanical risk factors which may be used in developing improved patient screening strategies. However, a clear understanding is needed about what we have achieved and what is really needed to translate research to actual clinical practices and bring benefits to public health. Histopathological analysis has served as the gold standard for validation and verification of vulnerable plaque studies. Lack of in vivo data and clinical events to serve as gold standard to validate model predictions is a severe limitation. A review of the key steps and findings of our group in image-based models for human carotid and coronary plaques will be provided, including image and data acquisition, model construction, data analysis and identification of mechanisms and risk factors for plaque progression and rupture. Predictive methods to quantify prediction accuracy of risk factors leading to prediction of acute clinical events will be presented.
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