Advanced Medical Research Center, Iwate Medical University, Uchimaru, Morioka, Japan.
J Cereb Blood Flow Metab. 2011 Mar;31(3):908-12. doi: 10.1038/jcbfm.2010.169. Epub 2010 Sep 22.
The time-to-maximum of the tissue residue function (T(max)) perfusion index has proven very predictive of infarct growth in large clinical trials, yet its dependency on simple tracer delays remains unknown. Here, we determine the dependency of computed tomography (CT) perfusion (CTP) T(max) estimates on tracer delay using a range of deconvolution techniques and digital phantoms. Digital phantom data sets simulating the tracer delay were created from CTP data of six healthy individuals, in which time frames of the left cerebral hemisphere were shifted forward and backward by up to ±5 seconds. These phantoms were postprocessed with three common singular value decomposition (SVD) deconvolution algorithms-standard SVD (sSVD), block-circulant SVD (bSVD), and delay-corrected SVD (dSVD)-with an arterial input function (AIF) obtained from the right middle cerebral artery (MCA). The T(max) values of the left hemisphere were compared among different tracer delays and algorithms by a region of interest-based analysis. The T(max) values by sSVD were positively correlated with 'positive shifts' but unchanged with 'negative shifts,' those by bSVD had an excellent positive linear correlation with both positive and negative shifts, and those by dSVD were relatively constant, although slightly increased with the positive shifts. The T(max) is a parameter highly dependent on tracer delays and deconvolution algorithm.
组织残基功能(T(max))的时间-最大值灌注指数已被证明在大型临床试验中对梗死灶的生长具有很好的预测性,但它对简单示踪剂延迟的依赖性仍不清楚。在这里,我们使用一系列解卷积技术和数字体模来确定 CT 灌注(CTP)T(max)估计值对示踪剂延迟的依赖性。数字体模数据模拟了示踪剂延迟,是从六名健康个体的 CTP 数据中创建的,其中左半球的时间框架向前和向后移动了最多±5 秒。这些体模用三种常用的奇异值分解(SVD)解卷积算法(标准 SVD(sSVD)、块循环 SVD(bSVD)和延迟校正 SVD(dSVD))进行后处理,动脉输入功能(AIF)来自右侧大脑中动脉(MCA)。通过感兴趣区域分析比较不同示踪剂延迟和算法的左半球 T(max)值。sSVD 的 T(max)值与“正向移位”呈正相关,但与“负向移位”不变,bSVD 的 T(max)值与正向和负向移位均呈极好的正线性相关,而 dSVD 的 T(max)值则相对恒定,尽管随着正向移位略有增加。T(max)是一个高度依赖于示踪剂延迟和解卷积算法的参数。