PhD Proposal by David Immanuel Madukauwa-David

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David Immanuel Madukauwa-David BioEngineering PhD Proposal   Date: Wednesday February 7th, 2018 Time: 9:00 AM Location: TEP, 387 Technology Cir NW, Atlanta, GA 30313, RM 104   Thesis advisor: Ajit P. Yoganathan, PhD (Georgia Tech, Biomedical Engineering)   Thesis Committee: Vasilis Babaliaros, MD (Emory University, Medicine) Rahul Sharma, MD (Cedars Sinai Medical Center, Los Angeles, CA) Wei Sun, PhD (Georgia Tech, Biomedical Engineering) John Oshinski, PhD (Georgia Tech, Biomedical Engineering) Cyrus Aidun, PhD (Georgia Tech, Mechanical Engineering)   A Comprehensive Analysis of Potential Factors for Transcatheter Aortic Valve Thrombosis Risk Transcatheter aortic valve replacement (TAVR) is indicated for aortic stenosis (AS) patients who are deemed intermediate or greater surgical risk. Recent evidence of leaflet thrombosis and reduced leaflet mobility in TAVR devices has led to concerns of stroke and long-term valve durability. Risk factors for thrombosis in TAVR patients remain poorly defined. While materials and blood chemistry are likely to be contributing factors to thrombosis risk, early clinical evidence and experimental data suggest that the fluid dynamic environment in the specific setting of the transcatheter aortic valve (TAV) is a major factor in the development of leaflet thrombosis. This environment can be altered by anatomical, procedural, and device related parameters. Additionally, it has been demonstrated that the thrombus originates in the “neo-sinus,” which is the pocket formed between the TAV leaflets and the native aortic valve leaflets. This study aims to elucidate the contribution of anatomical, deployment, and fluid dynamic factors to a thrombogenic environment in the neo-sinus region of transcatheter aortic valves via analyses of clinical imaging data, the development of predictive statistical models, and a battery of well controlled benchtop experiments on select commercial TAVs. The findings from these studies could provide a vital tool to help predict which valves, deployments, and/or patient may be at a higher risk of valve thrombosis.  


  • Workflow Status: Published
  • Created By: Tatianna Richardson
  • Created: 01/04/2018
  • Modified By: Tatianna Richardson
  • Modified: 01/04/2018