血管生成的CT成像。

T-Y Lee, T G Purdie, E Stewart
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引用次数: 0

摘要

肿瘤血管生成在各种实体瘤的诊断和治疗中具有重要意义。随着快速多层CT扫描仪的出现,能够对肿瘤血管生成进行定性和定量分析的CT成像技术在过去20年里得到了广泛的研究。血管生成的CT成像的基础是静脉注射碘造影剂到组织的血流运输以及这些造影剂分子在血管内间隙和血管外间隙之间的扩散交换。使用目前的快速CT扫描仪,组织和血管增强都可以在短时间间隔内测量和跟踪,从而可以对组织中造影剂的分布进行详细建模。对比剂运输和交换的室室参数模型和分布参数模型已经被开发出来,从CT数据中量化以下血管生成相关参数:组织血流量、血容量、平均运输时间、对比剂到达时间、毛细血管通透性表面积积和肝动脉分数。本文综述了血管生成的CT成像的以下几个方面:1)与室室和分布参数模型的理解相关的基本概念;2)两种模型的比较;3)关于动脉输入函数测量的实际问题,这是两种模型求解所必需的;4)说明分布参数模型,即Johnson和Wilson模型在一些实验研究中的应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
CT imaging of angiogenesis.

Tumor angiogenesis has significant implications in the diagnosis and treatment of various solid tumors. With the advent of fast, multi-slice CT scanners, CT imaging techniques capable of qualitative and quantitative analysis of tumor angiogenesis have been the subject of extensive investigation in the past 2 decades. The fundamental bases for CT imaging of angiogenesis are both the transport by blood flow of intravenously administered iodinated contrast material to tissue and the exchange by diffusion of these contrast molecules between the intravascular space and the extravascular interstitial space. With current fast CT scanners both tissue and vascular enhancement can be measured and traced over time at small time intervals to allow detailed modeling of the distribution of contrast agent in tissue. Both compartmental and distributed parameter models for contrast transport and exchange have been developed to quantify from the CT data the following angiogenesis related parameters: tissue blood flow, blood volume, mean transit time, contrast arrival time, capillary permeability surface area product and hepatic arterial fraction in case of the liver. This review addresses the following aspects of CT imaging of angiogenesis: 1) basic concepts related to the understanding of both compartmental and distributed parameter models; 2) comparison between both types of models; 3) practical issues with respect to the measurement of the arterial input function, which is required for the solution of both types of models; and, 4) illustration of the application of a distributed parameter model, the Johnson and Wilson model, in a number of experimental studies.

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