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: 2019
• 资助国家: 加拿大
• 起止时间: 2019-01-01 至 2020-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=681988
• 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-invasivelycurrent 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）成像的使用正在迅速成为了解各种疾病和干预措施的重要工具。这在其他领域也很关键，从工程和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评估组织功能。我们最近的工作表明，目前的动力学模型的可靠性大大降低，在组织缺氧和高压。获得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，并增加DCE成像用于诊断目的的价值，并评估药物输送机制的有效性和对靶向干预措施的反应。间质流体压力（IFP）是一个很有价值的功能，以获取非侵入性的IFP电流测量需要一个基于针的方法，只能在可访问的组织位置使用，是难以重复。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成像中获得。为了创建这些功能并改善DCE衍生测量的量化，我们将创建一个组织中的液体传输模型，该模型在交叉体素方法中将药物/造影剂对流和扩散、间质液压力和缺氧条件联系起来。下面描述的技术目标列出了一项研究计划，该计划解决了实现快速，基于GPU的计算机模型所需的潜在物理学相关发展，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转运模型。将结合CT和MRI造影剂的基本对流、扩散和热力学行为，以描述计算机模拟运输框架内的压力、渗透性、流动和滞留; * 使用可渗透组织聚合物体模进行确认。将使用生物聚合物和凝胶系统开发和制造仿组织灌注体模，该系统可匹配正常和病变组织的光谱，作为测量确认工具。* 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计划包括生物物理学，材料工程，计算分析和HPC开发。HQP直接参与创建改进的传输模型的设计，实施和验证，每个模型都专注于计算机模拟和体模材料工程，使他们能够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。**