An imaging-based computational model for simulating angiogenesis and tumour oxygenation dynamics.
An imaging-based computational model for simulating angiogenesis and tumour oxygenation dynamics.
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DOI：
10.1088/0031-9155/61/10/3885
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发表时间：
2016-05-21
影响因子：
3.5
通讯作者：
Jeraj R
中科院分区：
文献类型：
--
作者：
Adhikarla V;Jeraj R
肿瘤的生长、血管生成和氧合作用在不同的肿瘤中有很大的不同，并显著影响其治疗结果。成像为研究这些肿瘤特异性特征提供了一种独特的手段。在这里，我们提出了一个基于分子成像数据的计算模型来模拟肿瘤特异性氧合变化。模型中的肿瘤氧合反应由灌流的血管密度来反映。肿瘤的生长取决于其倍增时间(Td)和成像的增殖。血管密度募集率取决于肿瘤周围的血管密度(sMVD组织)和完全血管功能障碍的最大血管内皮生长因子浓度(VEGFmax)。模型参数的基准是再现肿瘤整个生命周期的氧合动力学，这是最具挑战性的测试。用氧分压峰值(pO2峰值)和氧分压达峰时间(TPeak)来定量肿瘤氧合动力学。通过改变每个参数20%来评估肿瘤氧合对模型参数的敏感性。与组织血管密度(~10%)相比，Tak对肿瘤细胞系相关倍增时间(~30%)更为敏感。另一方面，pO2峰值也同样受到上述肿瘤和血管相关参数的影响(~30-40%)。有趣的是，VEGFmax(~5%)对pO2峰和tPeak的影响都很小。随着肿瘤的生长，低氧(低氧)核心的形成增加了血管内皮生长因子的积累，从而破坏了血管的灌流，并随着时间的推移进一步增加了低氧。该模型及其基准参数被应用于使用[64Cu]Cu-ATSM PET扫描获得的小鼠肿瘤的缺氧成像数据，并显示了血管系统的时间发展和缺氧地图。这项工作强调了使用肿瘤特异性输入来分析肿瘤进化的重要性。一个包含治疗效果的扩展模型可以作为一个强大的工具来分析肿瘤对抗血管生成治疗的反应。
Tumour growth, angiogenesis and oxygenation vary substantially among tumours and significantly impact their treatment outcome. Imaging provides a unique means of investigating these tumour-specific characteristics. Here we propose a computational model to simulate tumour-specific oxygenation changes based on the molecular imaging data. Tumour oxygenation in the model is reflected by the perfused vessel density. Tumour growth depends on its doubling time (Td) and the imaged proliferation. Perfused vessel density recruitment rate depends on the perfused vessel density around the tumour (sMVDtissue) and the maximum VEGF concentration for complete vessel dysfunctionality (VEGFmax). The model parameters were benchmarked to reproduce the dynamics of tumour oxygenation over its entire lifecycle, which is the most challenging test. Tumour oxygenation dynamics were quantified using the peak pO2 (pO2peak) and the time to peak pO2 (tpeak). Sensitivity of tumour oxygenation to model parameters was assessed by changing each parameter by 20%. tpeak was found to be more sensitive to tumour cell line related doubling time (~30%) as compared to tissue vasculature density (~10%). On the other hand, pO2peak was found to be similarly influenced by the above tumour- and vasculature-associated parameters (~30–40%). Interestingly, both pO2peak and tpeak were only marginally affected by VEGFmax (~5%). The development of a poorly oxygenated (hypoxic) core with tumour growth increased VEGF accumulation, thus disrupting the vessel perfusion as well as further increasing hypoxia with time. The model with its benchmarked parameters, is applied to hypoxia imaging data obtained using a [64Cu]Cu-ATSM PET scan of a mouse tumour and the temporal development of the vasculature and hypoxia maps are shown. The work underscores the importance of using tumour-specific input for analysing tumour evolution. An extended model incorporating therapeutic effects can serve as a powerful tool for analysing tumour response to anti-angiogenic therapies.
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影响因子：
3.5
作者：
Adhikarla V;Jeraj R
通讯作者：
Jeraj R
影响因子：
2
作者：
Bartha, K.;Rieger, H.
通讯作者：
Rieger, H.
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2
作者：
Cai, Yan;Xu, Shixiong;Long, Quan
通讯作者：
Long, Quan
影响因子：
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通讯作者：
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影响因子：
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作者：
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通讯作者：
MICHELSON, S