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本文引用的文献

1
The physiological significance of the time-to-maximum (Tmax) parameter in perfusion MRI.灌注 MRI 中达峰时间(Tmax)参数的生理学意义。
Stroke. 2010 Jun;41(6):1169-74. doi: 10.1161/STROKEAHA.110.580670. Epub 2010 Apr 22.
2
Difference in tracer delay-induced effect among deconvolution algorithms in CT perfusion analysis: quantitative evaluation with digital phantoms.CT灌注分析中去卷积算法之间示踪剂延迟诱导效应的差异:使用数字体模的定量评估
Radiology. 2009 Apr;251(1):241-9. doi: 10.1148/radiol.2511080983. Epub 2009 Feb 3.
3
Acute stroke imaging research roadmap.急性卒中成像研究路线图。
AJNR Am J Neuroradiol. 2008 May;29(5):e23-30. doi: 10.1161/STROKEAHA.107.512319.
4
Acute stroke imaging research roadmap.急性中风成像研究路线图。
Stroke. 2008 May;39(5):1621-8. doi: 10.1161/STROKEAHA.107.512319. Epub 2008 Apr 10.
5
Effects of alteplase beyond 3 h after stroke in the Echoplanar Imaging Thrombolytic Evaluation Trial (EPITHET): a placebo-controlled randomised trial.依平面成像溶栓评估试验(EPITHET)中卒中后3小时以上使用阿替普酶的效果:一项安慰剂对照随机试验。
Lancet Neurol. 2008 Apr;7(4):299-309. doi: 10.1016/S1474-4422(08)70044-9. Epub 2008 Feb 28.
6
How reliable is perfusion MR in acute stroke? Validation and determination of the penumbra threshold against quantitative PET.灌注磁共振成像在急性卒中中的可靠性如何?与定量正电子发射断层扫描对比进行半暗带阈值的验证与测定。
Stroke. 2008 Mar;39(3):870-7. doi: 10.1161/STROKEAHA.107.500090. Epub 2008 Feb 7.
7
Impact of collateral flow on tissue fate in acute ischaemic stroke.侧支血流对急性缺血性卒中组织转归的影响
J Neurol Neurosurg Psychiatry. 2008 Jun;79(6):625-9. doi: 10.1136/jnnp.2007.132100. Epub 2007 Dec 12.
8
Magnetic resonance imaging profiles predict clinical response to early reperfusion: the diffusion and perfusion imaging evaluation for understanding stroke evolution (DEFUSE) study.磁共振成像特征可预测早期再灌注的临床反应:扩散与灌注成像评估以理解卒中演变(DEFUSE)研究
Ann Neurol. 2006 Nov;60(5):508-517. doi: 10.1002/ana.20976.
9
Clinical-diffusion mismatch predicts the putative penumbra with high specificity.临床扩散不匹配以高特异性预测假定的半暗带。
Stroke. 2005 Aug;36(8):1700-4. doi: 10.1161/01.STR.0000173407.40773.17. Epub 2005 Jul 14.
10
Automated method for generating the arterial input function on perfusion-weighted MR imaging: validation in patients with stroke.灌注加权磁共振成像中动脉输入函数的自动生成方法:在中风患者中的验证
AJNR Am J Neuroradiol. 2005 Jun-Jul;26(6):1479-86.

Tmax 对灌注分析示踪剂延迟的敏感性:使用数字体模对各种去卷积算法的定量评估。

Susceptibility of Tmax to tracer delay on perfusion analysis: quantitative evaluation of various deconvolution algorithms using digital phantoms.

机构信息

Advanced Medical Research Center, Iwate Medical University, Uchimaru, Morioka, Japan.

出版信息

J Cereb Blood Flow Metab. 2011 Mar;31(3):908-12. doi: 10.1038/jcbfm.2010.169. Epub 2010 Sep 22.

DOI:10.1038/jcbfm.2010.169
PMID:20859294
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3063623/
Abstract

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.

摘要

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。