奇异值分解法用于MR灌注成像脑血流量估计的仿真研究  

A Simulation Study on Singular Value Decomposition to Estimate the Cerebral Blood Flow in MR Perfusion Imaging

作　　者：马栋敏[1] 李颖[1] 彭川[2] 郭延庆[3] 郭磊[1] 何任杰 饶利芸 

机构地区：[1]河北工业大学河北省电磁场与电器可靠性省部共建重点实验室,天津300130 [2]天津市第四中心医院,天津300140 [3]军械工程学院,石家庄050003 [4]University of Texas Medical School at Houston,Houston,TX 77030,USA [5]The Methodist Hospital Research Institute,Houston,TX 77030,USA

出　　处：《中国生物医学工程学报》2011年第6期813-819,共7页Chinese Journal of Biomedical Engineering

基　　金：河北省自然科学基金(E2009000085);河北省科学技术研究与发展计划(10213571)

摘　　要：MR脑灌注成像是MR方法中提供代谢能力度量的唯一途径,对于疾病诊断和治疗效果评估有重要意义。MR灌注成像灌注参数的确定本质上是一个逆问题的求解过程,对一种求逆估计方法—奇异值分解法的逆问题性质进行了研究。在对奇异值分解法进行理论推导后,设计仿真方案,分别针对不同的信噪比进行仿真实验,并对动脉输入函数的延迟与失真进行分析。结果表明,在信噪比分别为150和10时,奇异值分解法都可以有效地估计脑血流量。该方法对动脉输入函数的失真不敏感,但是发生动脉输入函数延迟时,高脑血流量会被低估20%～30%。针对这一情况,对动脉输入函数的延迟效应进行了修正,修正后低估程度减小到±5%,得以明显改善。仿真结果表明,奇异值分解法是一种有效的估计MR灌注成像脑血流量的方法。MR perfusion imaging provides the unique approach to measure the metabolic capacity of brain, which is important in diagnosing the disease as well as assessing the treatment. The retrieve of perfusion parameters from MR perfusion imaging of brain is typically a process of inverse problem. In this paper, singular value decomposition （SVD） is advocated as a solver for the inverse problem, and the SVD technique for estimating the cerebral blood flow （CBF） is elaborated in short. Simulation schemes are designed towards revealing the properties of the inverse problem, namely the effects of signal-noise ratio, arterial input function （AIF） delay and distortion. Our simulation experiments show that the SVD technique is able to precisely reproduce flows when SNR equals to 150 or 10 respectively. The solution of SVD technique is found to be stable in the presence of the AIF distortion. However, the SVD technique is sensitive to the effect of AIF delay, where the high CBFs are underestimated about 20% - 30%. Hence therefore a delay correction method is developed and the simulation results show that the corrected CBFs are less suffered from the underestimation which isreduced to a value between _＋ 5%. The simulation results show that SVD method is an effective method to estimate the cerebral blood flow in MR perfusion imaging.

关 键 词：MR脑灌注成像 奇异值分解 脑血流量估计 

分 类 号：R318[医药卫生—生物医学工程]