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: 2017
• 资助国家: 加拿大
• 起止时间: 2017-01-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=638942
• 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心血管疾病引起的，这些疾病会干扰或受到血液流动模式的干扰。这些流动模式很难直接在患者中进行图像或测量，这可能使医生更难正确诊断和治疗这些疾病。我们的研究试图通过整合医学成像和计算流体动力学（CFD）来克服这一点。一种重要的成分是我们开发了医学成像模拟，这使我们能够理解流动如何改变我们为CFD模型所依赖的临床图像中动脉和血流的外观。在NSERC的支持下，我们有开发了新的超声和磁共振成像（MRI）仿真技术，这些模拟技术既快速又逼真（与其他方法不同，往往是一种或另一种方法）。这使我们现在可以考虑检测和纠正心血管成像和建模中扭曲的新方法，这些方法最终可以将其进入医学成像扫描仪或分析工作站。具体而言，我们将重点放在困扰我们和其他研究的两个重要问题上：多普勒超声对血液速度和流速的准确测量；以及从MRI的血管形状和大小的自动测量。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，通常提供给它们的血流可视化效果比他们需要的互动率更少或更详细，因此使其难以实现他们要“看到树木的森林”。基于我们的医学成像模拟工作的想法，我们将开发一种新的方法来存储和检索复杂的血流数据集以实时互动；我们将合并流体力学和图形艺术原理，以突出显示最相关的流动模式。