Predicting retinal tissue oxygenation using an image-based theoretical model
Predicting retinal tissue oxygenation using an image-based theoretical model
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DOI：
10.1016/j.mbs.2018.08.005
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发表时间：
2018-11-01
影响因子：
4.3
通讯作者：
Arciero, Julia
中科院分区：
文献类型：
--
作者：
Fry, Brendan C.;Coburn, Ehren Brant;Arciero, Julia
氧输送和组织灌注受损已被确定为导致青光眼患者视网膜神经节细胞损失的重要因素。这项研究预测视网膜血液和组织氧合使用的视网膜血管系统的理论模型的基础上，共聚焦显微镜图像的小鼠视网膜。这些图像揭示了复杂和异质的血管几何形状，这些血管在不同的深度不均匀地分布到多个不同的视网膜层中。预测这种不规则排列的视网膜微血管中的氧输送和分布需要使用有效的理论模型。本工作中采用的模型利用基于绿色函数方法的数值方法来模拟视网膜血管网络及其周围组织中氧气水平的空间分布。模型模拟还预测了整个网络中每个微血管的血液流速和压力。正如预期的那样，该模型预测平均血管PO 2随着需氧量的增加而降低。然而，当需氧量从1增加到8 cm（3）O-2/100 cm（3）/min时，血管中PO 2的标准差几乎加倍，表明预测的PO 2水平分布非常广，表明平均PO 2不是异质血管网络中氧合的充分指标。最终，该数学模型的开发将有助于阐明与血流和代谢相关的导致青光眼视力丧失特征的重要因素。
Impaired oxygen delivery and tissue perfusion have been identified as significant factors that contribute to the loss of retinal ganglion cells in glaucoma patients. This study predicts retinal blood and tissue oxygenation using a theoretical model of the retinal vasculature based on confocal microscopy images of the mouse retina. These images reveal a complex and heterogeneous geometry of vessels that are distributed non-uniformly into multiple distinct retinal layers at varying depths. Predicting oxygen delivery and distribution in this irregular arrangement of retinal microvessels requires the use of an efficient theoretical model. The model employed in this work utilizes numerical methods based on a Green's function approach to simulate the spatial distribution of oxygen levels in a network of retinal blood vessels and the tissue surrounding them. Model simulations also predict the blood flow rates and pressures in each of the microvessels throughout the entire network. As expected, the model predicts that average vessel PO2 decreases as oxygen demand is increased. However, the standard deviation of PO2 in the vessels nearly doubles as oxygen demand is increased from 1 to 8 cm(3) O-2/100 cm(3)/min, indicating a very wide spread in the predicted PO2 levels, suggesting that average PO2 is not a sufficient indicator of oxygenation in a heterogeneous vascular network. Ultimately, the development of this mathematical model will help to elucidate the important factors associated with blood flow and metabolism that contribute to the vision loss characteristic of glaucoma.