Computational and theoretical fluid mechanics modeling for transport in dense tumors

瘤内灌注一直被认为是致密性实体癌临床诊断和治疗的关键问题。在这种情况下，基于第一性原理的力学模型可以量化肿瘤内细胞外空间的灌注，作为肿瘤血管形状和基质中纤维堆积分数的功能，可以为癌症诊断和治疗开辟新的途径。有了这个愿景，拟议的项目将把计算流体动力学（CFD）跟踪与理论流体力学分析结合起来，生成一个可以在广泛参数空间上运行的计算机肿瘤摄取建模框架。测试几何图形将基于植入小鼠体内的人类胰腺肿瘤的计算机断层扫描（CT）。该项目还将在微流体装置和人造肿瘤球体中设计补充物理实验，以基准和验证所提出的计算机方法。由于使用平均连续水平输移框架（如Darcy’s Law和Starling模型）仍然是肿瘤内摄取量化的基本流体建模的首选方法，所提出的基于cfd的先进理论流体力学方法将基于肿瘤几何形状和肿瘤内应力参数化肿瘤灌注，这将是本项目对文献的关键贡献。该项目的长期目标如下：在临床环境中，通过对肿瘤ct切片进行图像处理，可以很容易地评估基质内纤维束的堆积比例，它与肿瘤内应力成对数比例。所提出的数值-理论模型将被设计为将肿瘤摄取作为包装分数的函数。这可以触发新的诊断/治疗解决方案，实体肿瘤内部的流体传输趋势仅通过评估填充分数的医学扫描来预测。我们的中心假设是：数值计算与理论建模的结合可以覆盖各种肿瘤微环境，为流体力学工具提供更大的可用性。由此产生的硅框架将在肿瘤几何特征的广泛参数空间上生成渗透数据，例如，基质内的填充分数和肿瘤脉管系统中血管的局部曲率。这项工作围绕以下具体目标进行：(a)目标1将数值模拟肿瘤血管内的多相运输，考虑到现实的血管形状和电流体动力学对平均运输的影响；(b)目标2将从目标1中导入内皮开口处的等离子体动力学信息，并将这些数据作为初始条件，开发一个通过细胞外基质的肿瘤内运输的综合数值理论模型。理论设置将调用对流扩散方法，其中肿瘤入口和坏死核心附近（肿瘤深处）的局部浓度的边界条件将从数值模拟中得到。最后，将硅灌注预测与在简化的生物启发微流体系统中进行的物理实验以及嵌入在流体环境中的细胞培养衍生的现实肿瘤球体进行比较。

Intratumoral perfusion has long been recognized as a critical issue in both clinical diagnosis and therapy of dense solid cancerous tumors. In such context, a first-principles mechanics-based model that can quantify perfusion in the intratumoral extracellular spaces as a function of the tumor vasculature shapes and the fiber packing fraction in the stroma – can launch new avenues in cancer diagnosis and care. With that vision, the proposed project will integrate computational fluid dynamics (CFD) tracking with theoretical fluid mechanics analysis to generate an in silico tumor uptake modeling framework, that can operate over a wide parametric space. The test geometries will be based off computed tomography (CT) scans of human pancreatic tumors implanted in mice. The project will also design supplementary physical experiments in microfluidic setups and artificial tumor spheroids to benchmark and validate the proposed in silico approach. With use of mean continuum-level transport frameworks such as Darcy's Law and Starling model still a go-to resort for basic fluids modeling of intratumoral uptake quantification, the proposed CFD-informed advanced theoretical fluid mechanics approach to parameterize tumor perfusion based on tumor geometry and intratumoral stress will constitute this project's key contribution to the literature. The long-term objective of the project is as follows: in a clinical setting, the packing fraction of the fiber bundles inside the stroma can be readily assessed from image-processing the CT-slices from a tumor, it being logarithmically proportional to the intratumoral stress. The proposed numerical-theoretical model will be designed such as to project the tumoral uptake as a function of the packing fraction. This can trigger new diagnostic/therapeutic solutions with the fluidic transport trends inside a solid tumor predictable solely from the medical scans through assessment of the packing fraction. Our central hypothesis is: an integration of numerical computations with theoretical modeling can cover a diverse range of tumor microenvironments, rendering greater usability for the fluid mechanics tools. The resulting in silico framework will generate percolation data over a wide parameter space of tumor geometry features, e.g., the packing fraction inside the stroma and the local curvatures of blood vessels in the tumor vasculature. The work is structured around the following specific aims: (a) Aim 1 will numerically simulate multiphase transport inside the tumor vasculature, considering realistic blood vessel shapes and electrohydrodynamic effects on the mean transport, (b) Aim 2 will import from Aim 1 the plasma dynamics information at the endothelial openings and use the data as initial conditions to develop an integrative numerical-theoretical model for intratumoral transport through the extracellular matrix. The theoretical setup will invoke a convection-diffusion approach, where the boundary conditions on the local concentrations at the tumor inlet and near the necrotic core (deep into the tumor) will be fed from the numerical simulations. Finally, the in silico perfusion predictions will be compared against physical experiments performed in simplified bio-inspired microfluidic systems and with cell culture-derived realistic tumor spheroids embedded in a fluidic environment.