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基于修正的 Hanai 方程对正常血液中红细胞聚集的定量测量和评估。

Quantitative Measurement and Evaluation of Red Blood Cell Aggregation in Normal Blood Based on a Modified Hanai Equation.

机构信息

The Institute of Precision Machinery and Smart Structures, College of Engineering, Zhejiang Normal University, Jinhua 321004, China.

出版信息

Sensors (Basel). 2019 Mar 4;19(5):1095. doi: 10.3390/s19051095.

DOI:10.3390/s19051095
PMID:30836669
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6427202/
Abstract

The aggregation of red blood cells (RBCs) in normal blood (non-coagulation) has been quantitatively measured by blood pulsatile flow based on multiple-frequency electrical impedance spectroscopy. The relaxation frequencies under static and flowing conditions of blood pulsatile flow are utilized to evaluate the RBC aggregation quantitatively with the consideration of blood flow factors (RBC orientation, deformation, thickness of electrical double layer (EDL)). Both porcine blood and bovine blood are investigated in experiments, for the reason that porcine blood easily forms RBC aggregates, while bovine blood does not. The results show that the relaxation frequencies of porcine blood and bovine blood present opposite performance, which indicates that the proposed relaxation frequency is efficient to measure RBCs aggregation. Furthermore, the modified Hanai equation is proposed to quantitatively calculate the influence of RBCs aggregation on relaxation frequency . The study confirms the feasibility of a high speed, on-line RBC aggregation sensing method in extracorporeal circulation systems.

摘要

基于多频电阻抗谱的血液脉动流中红细胞（RBC）的聚集已被定量测量。利用血液脉动流的静态和流动条件下的弛豫频率，在考虑血流因素（RBC 取向、变形、双电层（EDL）厚度）的情况下定量评估 RBC 聚集。实验中同时研究了猪血和牛血，因为猪血容易形成 RBC 聚集，而牛血则不会。结果表明，猪血和牛血的弛豫频率呈现相反的性能，这表明所提出的弛豫频率可有效地测量 RBC 聚集。此外，还提出了改进的 Hanai 方程来定量计算 RBC 聚集对弛豫频率的影响。该研究证实了在体外循环系统中进行高速、在线 RBC 聚集传感方法的可行性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d591/6427202/bb34f341a74c/sensors-19-01095-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d591/6427202/9b1f1b209000/sensors-19-01095-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d591/6427202/80360af72c01/sensors-19-01095-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d591/6427202/fbffb76ff7bd/sensors-19-01095-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d591/6427202/2a2217fabb1b/sensors-19-01095-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d591/6427202/0ea77615a8ff/sensors-19-01095-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d591/6427202/446a1c863f78/sensors-19-01095-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d591/6427202/bb34f341a74c/sensors-19-01095-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d591/6427202/9b1f1b209000/sensors-19-01095-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d591/6427202/80360af72c01/sensors-19-01095-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d591/6427202/fbffb76ff7bd/sensors-19-01095-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d591/6427202/2a2217fabb1b/sensors-19-01095-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d591/6427202/0ea77615a8ff/sensors-19-01095-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d591/6427202/446a1c863f78/sensors-19-01095-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d591/6427202/bb34f341a74c/sensors-19-01095-g007.jpg

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