Virtual Imaging and Visualization of Blood Flow Dynamics

血流动力学的虚拟成像和可视化

• 批准号: 249746-2013
• 负责人: Steinman, David
• 金额: $ 3.28万
• 依托单位: University of Toronto
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2015
• 资助国家: 加拿大
• 起止时间: 2015-01-01 至 2016-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=570712
• 关键词: Virtual; Imaging; Visualization; Blood; Flow

Heart attacks and strokes are caused by cardiovascular diseases that disturb, or are disturbed by, blood flow patterns. These flow patterns are difficult to image or measure directly in patients, which can make it harder for doctors to properly diagnosis and treat these diseases. Our research has sought to overcome this via the integration of medical imaging and computational fluid dynamics (CFD). An essential ingredient has been our development of medical imaging simulations, which allow us to understand how disturbed flow can alter the appearance of arteries and blood flow in the clinical images that we rely on for our CFD models. With the support of NSERC, we have developed new ultrasound and magnetic resonance imaging (MRI) simulation techniques that are both fast and realistic (unlike other approaches, which tend to be one or the other). This allows us to now consider new ways of detecting and correcting for distortions in cardiovascular imaging and modelling, which could ultimately see their way into medical imaging scanners or analysis workstations. Specifically, we will focus on two important problems that have plagued our and others' research: accurate measurement of blood velocities and flow rates by Doppler ultrasound; and automated measurement of blood vessel shape and size from MRI. At the same time, through our collaborations with radiologists and surgeons we have learned that the blood flow visualizations typically provided to them are less interactive or more detailed than they need, making it difficult for them to "see the forest for the trees". Building upon ideas from our medical imaging simulation work, we will develop a new approach for storing and retrieving complex blood flow datasets to allow for real-time interaction; and we will merge principles of fluid mechanics and the graphic arts to highlight only the most relevant flow patterns.

心脏病发作和中风是由扰乱血流模式或受血流模式干扰的心血管疾病引起的。这些血流模式很难在患者体内直接成像或测量，这使得医生更难正确诊断和治疗这些疾病。我们的研究试图通过医学成像和计算流体动力学 (CFD) 的集成来克服这个问题。我们开发的医学成像模拟是一个重要组成部分，它使我们能够了解血流扰动如何改变我们 CFD 模型所依赖的临床图像中的动脉和血流的外观。 在 NSERC 的支持下，我们开发了新的超声和磁共振成像 (MRI) 模拟技术，这些技术既快速又逼真（与其他方法不同，它们往往是其中之一）。这使我们现在可以考虑检测和校正心血管成像和建模中的失真的新方法，这最终可能会进入医学成像扫描仪或分析工作站。具体来说，我们将重点关注困扰我们和其他人研究的两个重要问题：通过多普勒超声精确测量血流速度和流速；以及通过 MRI 自动测量血管形状和尺寸。 与此同时，通过我们与放射科医生和外科医生的合作，我们了解到通常提供给他们的血流可视化的交互性较低或比他们需要的更详细，这使得他们很难“只见树木”。基于我们的医学成像模拟工作的想法，我们将开发一种新方法来存储和检索复杂的血流数据集，以实现实时交互；我们将融合流体力学和图形艺术的原理，只突出最相关的流动模式。