Sun Yi
Department of Electrical Engineering, The City College of City University of New York, New York, NY, USA.
J Med Signals Sens. 2014 Jul;4(3):159-70.
In this paper, we propose and investigate distribution of intravascular and extravascular extracellular volume fractions (DIEEF) as a noninvasive biomarker for neovascularization assessment by dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). A generalized two-compartment exchange model (G2CXM) that uniformly includes the Patlak model, Tofts model, extended Tofts model, and recent two-compartment exchange model as special instances is first presented. Based on the total area under curve of the G2CXM a method of DIEEF estimation without knowing the artery input function is proposed. The mean square error of DIEEF estimate in the presence of noise and with incomplete DCE-MRI data is analyzed. Simulation results demonstrate that DIEEF estimate is accurate when signal to noise ratio is only 5 dB in both cases of tracer infusion and bolus injection, and slightly favors the bolus injection. Tested on a model of atherosclerotic rabbits, the DIEEF of aorta plaques is positively correlated with the histological neovessel count with correlation coefficient of 0.940 and P = 0.017, and outperforms six semiquantitative parameters in the literature. DIEEF might be useful as a biomarker for noninvasive neovascularization assessment by DCE-MRI.
在本文中,我们提出并研究血管内和血管外细胞外容积分数分布(DIEEF),作为通过动态对比增强磁共振成像(DCE-MRI)评估新生血管形成的一种非侵入性生物标志物。首先提出了一种广义双室交换模型(G2CXM),该模型统一包含Patlak模型、Tofts模型、扩展Tofts模型以及最近的双室交换模型作为特殊情况。基于G2CXM的曲线下总面积,提出了一种在不知道动脉输入函数的情况下估计DIEEF的方法。分析了在存在噪声和DCE-MRI数据不完整的情况下DIEEF估计的均方误差。模拟结果表明,在示踪剂注入和团注两种情况下,当信噪比仅为5 dB时,DIEEF估计是准确的,并且略有利于团注。在动脉粥样硬化兔模型上进行测试,主动脉斑块的DIEEF与组织学新生血管计数呈正相关,相关系数为0.940,P = 0.017,并且优于文献中的六个半定量参数。DIEEF可能作为一种通过DCE-MRI进行非侵入性新生血管形成评估的生物标志物。