Smith M R, Lu H, Trochet S, Frayne R
Electrical and Computer Engineering, University of Calgary, Calgary, Alberta, Canada.
Magn Reson Med. 2004 Mar;51(3):631-4. doi: 10.1002/mrm.20006.
Quantitative cerebral blood flow (CBF) values can be obtained from dynamic susceptibility contrast (DSC) MR perfusion studies using the standard singular value decomposition (sSVD) deconvolution algorithm. Reports in the literature from simulation and in vivo studies suggest that CBF estimates obtained using sSVD deconvolution depend on the arterial-tissue delay (ATD). By contrast, Fourier transform (FT) deconvolution produces CBF estimates that are independent of ATD. The diagnostic reliability of quantitative CBF measurements to define areas of normal tissue flow and tissue at risk is brought into doubt by such gross sensitivity to the specifics of the deconvolution approach. This variation of CBF values with ATD is shown to be an artifact associated with the current implementation of the sSVD deconvolution algorithm. A reformulated version of the SVD deconvolution algorithm (rSVD) is presented and compared to the standard SVD algorithm through simulation and patient case studies.
使用标准奇异值分解(sSVD)反卷积算法,可从动态磁敏感对比(DSC)磁共振灌注研究中获得定量脑血流量(CBF)值。文献中来自模拟和体内研究的报告表明,使用sSVD反卷积获得的CBF估计值取决于动脉-组织延迟(ATD)。相比之下,傅里叶变换(FT)反卷积产生的CBF估计值与ATD无关。定量CBF测量用于定义正常组织血流区域和有风险组织的诊断可靠性,因对反卷积方法细节如此高度敏感而受到质疑。CBF值随ATD的这种变化被证明是与sSVD反卷积算法当前实现相关的伪影。本文提出了奇异值分解反卷积算法的重新公式化版本(rSVD),并通过模拟和患者病例研究将其与标准奇异值分解算法进行比较。