From the Institute of Microcirculation, Chinese Academy of Medical Sciences & Peking Union Medical College.
Pancreas. 2020 Sep;49(8):1075-1082. doi: 10.1097/MPA.0000000000001627.
Pancreatic microcirculation has an essential role in orchestrating pancreatic homeostasis. Inherent complexity and technological limitation lead to interobserver variability and 1-sided microcirculatory data. Here, we introduce a multimodal device and computer algorithm-based platform for monitoring and visualizing integrated pancreatic microcirculation profiles.
After anesthetizing and exposing pancreas tissue of BALB/c mice, probes of Oxygen to See, Microx TX3, and MoorVMS-LDF2 were positioned at pancreas in situ to capture the pancreatic microcirculatory oxygen (hemoglobin oxygen saturation, relative amount of hemoglobin, and partial oxygen pressure) and microhemodynamic data (microvascular blood perfusion and velocity). To assess and visualize pancreatic microcirculation profiles, raw data of pancreatic microcirculation profiles were processed and transformed using interquartile range and min-max normalization by Python and Apache ECharts.
The multimodal device-based platform was established and 3-dimensional microcirculatory modules were constructed. Raw data sets of pancreatic microcirculatory oxygen and microhemodynamic were collected. The outlier of data set was adjusted to the boundary value and raw data set was preprocessed. Normalized pancreatic microcirculation profiles were integrated into the 3-dimensional histogram and scatter modules, respectively. The 3-dimensional modules of pancreatic microcirculation profiles were then generated.
We established a multimodal device and computer algorithm-based monitoring platform for visualizing integrated pancreatic microcirculation profiles.
胰腺微循环在调节胰腺稳态方面起着至关重要的作用。由于内在的复杂性和技术限制,导致了观察者间的变异性和片面的微循环数据。在这里,我们引入了一种基于多模态设备和计算机算法的平台,用于监测和可视化综合胰腺微循环谱。
在麻醉并暴露 BALB/c 小鼠的胰腺组织后,将 Oxygen to See、Microx TX3 和 MoorVMS-LDF2 探头置于原位胰腺,以捕获胰腺微循环的氧(血红蛋白氧饱和度、血红蛋白相对量和部分氧分压)和微血流动力学数据(微血管血流灌注和速度)。为了评估和可视化胰腺微循环谱,使用 Python 和 Apache ECharts 对胰腺微循环谱的原始数据进行了中值范围和最小-最大值归一化处理。
建立了基于多模态设备的平台,并构建了 3 维微循环模块。收集了胰腺微循环氧和微血流动力学的原始数据集。数据集的异常值被调整到边界值,原始数据集被预处理。归一化的胰腺微循环谱分别集成到 3 维直方图和散点模块中。然后生成了胰腺微循环谱的 3 维模块。
我们建立了一种基于多模态设备和计算机算法的监测平台,用于可视化综合胰腺微循环谱。