Transport modeling for multi-modality contrast-enhanced imaging

多模态对比增强成像的传输建模

• 批准号: RGPIN-2016-06641
• 负责人: Coolens, Catherine
• 金额: $ 1.97万
• 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: 2018
• 资助国家: 加拿大
• 起止时间: 2018-01-01 至 2019-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=648039
• 关键词: Transport; modeling; multi; modality; contrast

The use of dynamic contrast-enhanced (DCE) imaging is rapidly becoming an important tool to understand a variety of diseases and interventions. This is critical in other fields as well ranging from engineering and chemistry to structural and cell biology. At present DCE imaging is able to assess tissue functionality through blood flow and perfusion. Our most recent work has shown that the reliability of current kinetic models is much reduced in tissues with poor oxygenation and high pressure. Incorporating more information on the micro-environmental conditions of tissue would help illuminate more disease processes and increase the value of DCE imaging for diagnostic purposes and to assess the efficacy of drug delivery mechanisms and the response to targeted interventions.*Interstitial fluid pressure (IFP) is one feature that would be valuable to acquire non-invasively—current measurements of IFP require a needle-based approach that can only be used on accessible tissue locations and is difficult to repeat. Preliminary work from our lab indicates that these types of parameters can be derived from non-invasive DCE imaging.***To create these capabilities and improve the quantification of DCE-derived measures, we will create a model of fluid transport in tissue that links drug/contrast agent convection and diffusion, interstitial fluid pressure and hypoxia conditions in a cross-voxel approach. The technical aims described below set out a plan of research that addresses the underlying physics-related developments needed to achieve a fast, GPU-based computer model that provides measures of important tissue characteristics independent of observer interpretation: ******• Development of a robust composite microenvironment drug transport model. Fundamental convection, diffusion and thermodynamic behavior of CT and MRI contrast agents will be combined to describe pressure, permeability, flow and retention within a computer simulated transport framework; ***• Validation using a permeable tissue polymer phantom. A tissue-mimicking perfusion phantom will be developed and manufactured using biopolymers and gel systems that can match the spectrum of normal and diseased tissues to act as a measurement validation tool. ***• Acceleration using GPU-based implementation of composite transport modeling. ******This highly interdisciplinary research program embraces biophysics, material engineering, and computational analytics and HPC development. HQP are directly involved in the design, implementation and validation of creating improved transport models, each with a specific focus on computer simulations and phantom material engineering allowing them to be fully immersed in all components and applications of this unique imaging research project. **

动态对比增强（DCE）成像的使用正迅速成为了解各种疾病和干预措施的重要工具。这在其他领域也是至关重要的，从工程、化学到结构和细胞生物学。目前，DCE成像能够通过血流和灌注来评估组织功能。我们最近的工作表明，在缺氧和高压的组织中，当前动力学模型的可靠性大大降低。纳入更多关于组织微环境条件的信息将有助于阐明更多的疾病过程，提高DCE成像在诊断目的中的价值，并评估药物输送机制的功效和对目标干预的反应。*间质液压力（IFP）是获得非侵入性测量IFP的一个有价值的特征，需要基于针头的方法，只能在可接近的组织位置使用，并且难以重复。我们实验室的初步工作表明，这些类型的参数可以从非侵入性DCE成像中得到。***为了创建这些功能并改进dce衍生测量的量化，我们将创建一个组织中流体传输的模型，该模型将药物/造影剂的对流和扩散、间质流体压力和缺氧条件以跨体素的方式联系起来。下面描述的技术目标制定了一个研究计划，解决了实现快速、基于gpu的计算机模型所需的基础物理相关发展，该模型提供了独立于观察者解释的重要组织特征的测量：******•开发一个强大的复合微环境药物运输模型。CT和MRI造影剂的基本对流、扩散和热力学行为将结合起来，在计算机模拟的传输框架内描述压力、渗透率、流动和保留；***•使用渗透性组织聚合物模体进行验证。将使用生物聚合物和凝胶系统开发和制造组织模拟灌注幻影，该系统可以匹配正常和病变组织的光谱，作为测量验证工具。***•使用基于gpu的复合传输建模实现加速。******这个高度跨学科的研究项目包括生物物理学，材料工程，计算分析和高性能计算开发。HQP直接参与改进运输模型的设计、实施和验证，每个模型都专注于计算机模拟和幻影材料工程，使他们完全沉浸在这个独特的成像研究项目的所有组件和应用中。**