Kelly Catherine J, Brady Michael
Wolfson Medical Vision Laboratory, Information Engineering, University of Oxford, Parks Road, OX1 3PJ, UK.
Phys Med Biol. 2006 Nov 21;51(22):5859-73. doi: 10.1088/0031-9155/51/22/009. Epub 2006 Oct 26.
The microenvironment of a tumour, in particular its hypoxic status, is a crucial factor in its response to radiotherapy. Conventional techniques for measuring hypoxia are either invasive or follow surgical intervention, and thus not ideal. Positron emission tomography allows the non-invasive pre-surgical assessment of oxygen status by measuring the spatiotemporal distribution of hypoxia-specific tracers. However, the relationship between levels of uptake and the underlying oxygen tension are yet to be elucidated. Furthermore, it is not fully understood how changes in the underlying physiology affect the appearance of uptake. This paper presents a modular simulation of the tumour microenvironment, underpinned by a probability density function (PDF) to model the vasculature. The model is solved numerically, to simulate both the steady-state oxygenation of a tumour and the spatiotemporal distribution of the hypoxia-specific tracer, [18F]-fluoromisonidazole (Fmiso), in a 2D environment. The results show that using a PDF to represent the vasculature effectively captures the 'hypoxic island' appearance of oxygen-deficient tissues seen ex vivo. Simulated tissue activity curves (TACs) demonstrate the general two-stage trend of empirical data, with an initial perfusion-dominated uptake, followed by hypoxia-specific binding. In well-perfused tissue, activity follows plasma levels in early stages, with binding of Fmiso only becoming apparent at a later stage. In structurally hypoxic tissue, a more gradual initial increase in activity is observed, followed by the same accumulation slope. We demonstrate the utility of theoretical modelling of tracer uptake, by quantifying the changes in TAC structure that arise as a result of altering key physiological characteristics. For example, by decreasing either the proximity of tissue to the vasculature, or the effective diffusion coefficient of Fmiso, we can observe a shift of TAC structure from corresponding to well-perfused to avascular regions, despite wholly different underlying causes.
肿瘤的微环境,尤其是其缺氧状态,是影响其放疗反应的关键因素。传统的缺氧测量技术要么具有侵入性,要么需要手术干预,因此并不理想。正电子发射断层扫描能够通过测量缺氧特异性示踪剂的时空分布,对术前氧状态进行非侵入性评估。然而,摄取水平与潜在氧张力之间的关系尚未阐明。此外,对于潜在生理变化如何影响摄取表现,人们也尚未完全理解。本文提出了一种肿瘤微环境的模块化模拟方法,该方法以概率密度函数(PDF)为基础来模拟血管系统。通过数值求解该模型,以模拟肿瘤的稳态氧合以及缺氧特异性示踪剂[18F] - 氟米索硝唑(Fmiso)在二维环境中的时空分布。结果表明,使用PDF来表示血管系统能够有效地捕捉到体外观察到的缺氧组织的“缺氧岛”外观。模拟的组织活性曲线(TAC)显示出经验数据的一般两阶段趋势,即最初以灌注为主的摄取,随后是缺氧特异性结合。在灌注良好的组织中,早期活性跟随血浆水平,Fmiso的结合仅在后期变得明显。在结构缺氧的组织中,观察到活性最初有更缓慢的增加,随后是相同的积累斜率。我们通过量化由于改变关键生理特征而导致的TAC结构变化,证明了示踪剂摄取理论建模的实用性。例如,通过降低组织与血管系统的接近程度或Fmiso的有效扩散系数,我们可以观察到TAC结构从对应于灌注良好区域向无血管区域的转变,尽管其潜在原因完全不同。