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Development and application of a high-fidelity computational model of diabetic retinopathy hemodynamics: Coupling single-cell biophysics with retinal vascular network topology and complexity

Development and application of a high-fidelity computational model of diabetic retinopathy hemodynamics: Coupling single-cell biophysics with retinal vascular network topology and complexity
糖尿病视网膜病变血流动力学高保真计算模型的开发和应用:将单细胞生物物理学与视网膜血管网络拓扑和复杂性耦合
批准号:
10279068
负责人:
Prosenjit Bagchi
金额:
$35.13万
依托单位国家:
美国
项目类别:
财政年份:
2021
资助国家:
美国
项目状态:
未结题
起止时间:
2021-09-01 至 2025-07-31

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中文摘要
翻译
糖尿病性视网膜病变的发病机制的特征在于在视网膜中出现形态学异常。 视网膜毛细血管尽管这些异常用于疾病严重程度的临床评价, 其发展和进展的血液动力学机制仍然未知。这些 形态学异常高度局限于视网膜血管网的特定区域, 与血流动力学参数和力的局部变化相关。糖尿病症状显著 改变血细胞的生物物理性质,然而,这种改变的生物物理性质的影响 对视网膜血流动力学和视网膜病变的发病机制尚不清楚。现有体内成像 技术在拓扑学复杂和多通道的血流动力学测量方面具有局限性, 视网膜血管丛此外,组织缺氧和血流自动调节的丧失是致病的 视网膜病变的病因没有研究表明糖尿病介导的个体生物物理学改变 血细胞的视网膜组织氧合和流动调节的损失。我们的基本假设是:(一) 糖尿病红细胞(RBC)的生物物理学改变单独可以通过改变 血流动力学参数和力;以及(ii)这种变化在视网膜上是空间异质的。 血管网络,并与血管异常的局灶性和异质性相关。广大 本项目的目的是了解糖尿病血细胞的血流动力学之间的关系, 视网膜血管网络拓扑结构和视网膜病变的发病机制,使用高保真,预测 计算机模拟研究具体目标是:1)开发一个多尺度的计算模型, 糖尿病视网膜病变血流动力学考虑到精确的微观结构和几何细节 的3D血管网络,如从人视网膜的体内图像获得的,以及每个血管网络的3D变形。 具有代表糖尿病状况的改变的生物物理特性的单个血细胞。2)预测糖尿病 RBC介导的视网膜血流动力学改变,以及这些变化如何与视网膜血管形成相关。 微血管异常和血管适应在不同阶段的进展性 视网膜病变3)评价不同细胞尺度血流动力学通路的意义。4)到 预测红细胞血流动力学对视网膜缺氧和一氧化氮生物利用度丧失的作用, 视网膜病变的病因这项研究是有意义的和创新的,因为它将(i)开发第一个高保真, 预测计算模型,结合了超大规模和多丛的精确3D几何形状, 硅视网膜脉管系统和每个血细胞的3D变形和流变学,(ii)提供流变学- 拓扑耦合机制作为血流动力学介导的血管起始和进展的基础 异常,(ii)直接模拟异型个体细胞-细胞和细胞-内皮相互作用,和(iv) 将个体RBC瞬时变形与血液和视网膜组织气体运输耦合。
英文摘要
Pathogenesis of diabetic retinopathy is characterized by the appearance of morphological abnormalities in the retinal capillary vessels. Although such abnormalities are used in the clinical evaluation of the disease severity, the hemodynamic mechanisms underlying their development and progression remain unknown. These morphological abnormalities are highly localized in specific regions of the retinal vascular network, and may correlate with the local variations of the hemodynamic parameters and forces. Diabetic conditions significantly alter the biophysical properties of the blood cells, however the influence of such altered biophysical properties on the retinal hemodynamics and pathogenesis of retinopathy are not known. Existing in vivo imaging techniques have limitations in terms of the hemodynamic measurements in the topologically complex and multi- plexus retinal vasculature. Additionally, tissue hypoxia and the loss of blood flow autoregulation are pathogenic factors in retinopathy. No study exists that correlates diabetes-mediated altered biophysics of the individual blood cell to the loss of retinal tissue oxygenation and flow regulation. Our underlying hypotheses are: (i) altered biophysics of diabetic red blood cells (RBC) alone can mediate vascular abnormalities by altering the hemodynamic parameters and forces; and (ii) such changes are spatially heterogeneous across the retinal vascular network, and correlate with the focal and heterogeneous nature of vascular abnormalities. The broad objective of this project is to understand the relationship between the hemodynamics of diabetic blood cells, retinal vascular network topology, and pathogenesis of retinopathy, using a high-fidelity, predictive computational modeling study. Specific aims are: 1) To develop a multiscale computational model of the diabetic retinopathy hemodynamics taking into consideration the precise microstructural and geometric details of the 3D vascular networks as obtained from in vivo images of the human retina, and 3D deformation of every single blood cell with altered biophysical properties representing diabetic conditions. 2) To predict diabetic RBC-mediated alteration in the retinal hemodynamics, and how such changes are correlated to the formation and heterogeneity of microvascular abnormalities and vascular adaptation at different stages of progressive retinopathy. 3) To evaluate the significance of diverse cellular-scale hemodynamic pathways involved. 4) To predict the role of RBC hemodynamics on retinal hypoxia and loss of nitric oxide bioavailability as pathogenic factors in retinopathy. This study is significant and innovative because it will (i) develop the first high-fidelity, predictive computational model that combines the exact 3D geometry of ultra-large-scale and multi-plexus in silico retinal vasculature, and 3D deformation and rheology of every blood cell, (ii) provide a rheology- topology coupling mechanism as a basis of hemodynamics-mediated initiation and progression of vascular abnormalities, (ii) directly model heterotypic individual cell-cell and cell-endothelium interactions, and (iv) couple individual RBC transient deformation with blood and retinal tissue gas transport.
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