Koh T S, Cheong L H Dennis, Tan C K Markus, Lim C C Tchoyoson
Center for Modeling and Control of Complex Systems, School of Electrical and Electronic Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore 639798, Singapore.
Neuroimage. 2006 Apr 1;30(2):426-35. doi: 10.1016/j.neuroimage.2005.09.032. Epub 2005 Oct 24.
Quantitative estimates of physiological parameters associated with cerebral blood flow can be derived from the analysis of dynamic contrast-enhanced (DCE) images, using an appropriate model of the underlying tissue impulse residue function. The theoretical formulation of a distributed parameter model of tissue microcirculation, which accounts for the effects of capillary permeability and transit time distribution, is presented here. This model considers a statistical distribution of capillary-tissue units, each described by a distributed parameter model that accounts for convective transport within the capillary and transcapillary axial diffusion. Monte Carlo simulations were performed to study the confidence of the parameter estimates, and the model was used to analyze DCE CT images of patient study cases with metastatic cerebral tumors. The tumors were found to yield significantly higher estimates than normal tissues for the parameters associated with the extravasation of tracer and for the standard deviation of capillary transit times. The proposed model can be used with DCE imaging to study the microcirculatory characteristics of cerebral tumors.
通过使用基础组织脉冲残留函数的适当模型，对与脑血流量相关的生理参数进行定量估计，可以从动态对比增强（DCE）图像分析中得出。本文提出了一种组织微循环分布参数模型的理论公式，该模型考虑了毛细血管通透性和通过时间分布的影响。该模型考虑了毛细血管 - 组织单元的统计分布，每个单元由一个分布参数模型描述，该模型考虑了毛细血管内的对流传输和跨毛细血管轴向扩散。进行了蒙特卡罗模拟以研究参数估计的置信度，并使用该模型分析转移性脑肿瘤患者研究病例的DCE CT图像。发现肿瘤对于与示踪剂外渗相关的参数以及毛细血管通过时间的标准差产生的估计值明显高于正常组织。所提出的模型可与DCE成像一起用于研究脑肿瘤的微循环特征。
