光学 精密工程, 2017, 25 (12): 3111, 网络出版: 2018-01-10  

基于脉搏色素法/近红外光谱术测量脑血流参数

Measurement of cerebral blood flow parametres based on PDD-NIRS
作者单位
吉林大学 仪器科学与电气工程学院,吉林 长春 130026
摘要
采用传统的热稀释法和指示剂稀释法测量脑血流参数(cerebral blood flow,CBF)需要导管插植和定时采血,会对机体造成一定的损伤。本文针对上述测量方法存在的有创且操作复杂等问题,提出了一种基于Fick定律和朗伯比尔定律的快速、无创脑血流测量方法。该方法基于脉搏色素法/近红外光谱术(PDD-NIRS)技术,选用吲哚氰绿(indocyanine green,ICG)作为指示剂,通过对脑部和动脉ICG引入量的计算得到CBF。为验证模型的正确性,采用成年白兔进行了动物实验。对白兔静脉快速推注ICG色素,应用PDD-NIRS方法测量其CBF,然后计算出CBF值。 实验显示;应用PDD-NIRS方法测得的CBF相对误差为2%~4%,验证了该方法测量CBF的可行性;临床对比测量显示其平均误差满足临床诊断要求。该方法为临床诊断心脑血管疾病以及临床脑血流监护提供了有益的参考手段。
Abstract
When thermal dilution method and indicator dilution method are used to measure Cerebral Blood Flow (CBF)parameters, it requires catheter insertion and timing blood collection ,which will cause some damage to the human body. To solve their invasive and complex operations, a new noninvasive and rapid method for measuring the CBF was proposed based on Fick's law and Lambert's law. On the basis of Pulse Dye Densitometry/Near Infrared Spectrometry(PDD/NIRS), Indocyanine Green(ICG) was used as an indicator, and the ICG introducing brain and arterial were calculated to obtain the CBF. In order to verify the correctness of the model, an adult rabbit was used as the experimental object. The ICG pigment was injected rapidly in rabbits, at the same time the CBF was measured by PDD-NIRS method and the CBF value was calculated. Experiment shows that the relative error of CBF measured by PDD-NIRS method is 2% to 4%, which verifies the feasibility of the proposed method. The clinical comparison experiments also demonstrate that the average errors meet the clinical diagnosis requirement. This method provides a useful way for clinical diagnosis of cardiovascular and cerebrovascular diseases and clinical cerebral blood flow monitoring.

刘光达, 王郁霖, 秦琪, 张蓝溪, 千承辉, 尚小虎, 查雨彤, 蔡靖. 基于脉搏色素法/近红外光谱术测量脑血流参数[J]. 光学 精密工程, 2017, 25(12): 3111. LIU Guang-da, WANG Yu-lin, QIN Qi, ZHANG Lan-xi, QIAN Cheng-hui, SHANG Xiao-hu, ZHA Yu-tong, CAI Jing. Measurement of cerebral blood flow parametres based on PDD-NIRS[J]. Optics and Precision Engineering, 2017, 25(12): 3111.

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