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Modeling of a three-source perfusion and blood oxygenation sensor for transplant monitoring using Multi-Layer Monte Carlo code

机译:使用多层蒙特卡罗代码进行三源灌注和血氧传感器的建模

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A Multi-Layer Monte Carlo (MLMC) model was developed to predict the results of in vivo blood perfusion and oxygenation measurement of transplanted organs as measured by an indwelling optical sensor. A sensor has been developed which uses three-source excitation in the red and infrared ranges (660, 810, 940 nm). In vitro data was taken using this sensor by changing the oxygenation state of whole blood and passing it through a single-tube pump system wrapped in bovine liver tissue. The collected data showed that the red signal increased as blood oxygenation increased and infrared signal decreased. The center wavelength of 810 nanometers was shown to be quite indifferent to blood oxygenation change. A model was developed using MLMC code that sampled the wavelength range from 600-1000 nanometers every 6 nanometers. Using scattering and absorption data for blood and liver tissue within this wavelength range, a five-layer model was developed (tissue, clear tubing, blood, clear tubing, tissue). The theoretical data generated from this model was compared to the in vitro data and showed good correlation with changing blood oxygenation.
机译:开发了一种多层蒙特卡罗(MLMC)模型以预测通过留置光学传感器测量的移植器官的体内血液灌注和氧合测量的结果。已经开发了一种传感器,它在红色和红外线范围内使用三个源激发(660,810,940nm)。通过改变全血的氧化状态并通过燕尾肝组织包裹的单管泵系统来使用该传感器进行体外数据。所收集的数据显示,随着血氧化的增加和红外信号减小,红色信号增加。显示410纳米的中心波长对于血氧变化非常漠不关心。使用MLMC代码开发了一种模型,其每6纳米从600-1000纳米采样波长范围。使用该波长范围内的血液和肝脏组织的散射和吸收数据,开发了五层模型(组织,透明管,血液,透明管,组织)。将从该模型产生的理论数据与体外数据进行比较,并与改变血氧化良好相关。

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