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Assessment of tracer delay effect in whole-brain computed tomography perfusion: Results for selected regions of interest in middle cerebral artery acute ischemic strokes

机译:全脑计算机断层扫描灌注中示踪剂延迟效应的评估:大脑中动脉急性缺血性脑卒中选定目标区域的结果

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OBJECTIVE: The objective of this study was to compare the variability of computed tomography perfusion (CTP) results in identical data sets of middle cerebral artery (MCA) acute ischemic stroke (AIS) generated by standard singular value decomposition (sSVD) deconvolution and tracer delay-insensitive singular value decomposition (SVD+) algorithm analyses. METHODS: Whole-brain 320-detector-row CTP data sets from 9 unilateral MCA AIS cases and 9 controls were retrospectively analyzed. Computed tomography perfusion values for the combined core/penumbra, contralateral hemispheres and arterial territories were measured and compared with literature values. Simple linear regression models are provided to predict corresponding SVD+ value and sSVD CTP values. RESULTS: In the core/penumbra, sSVD generated lower cerebral blood flow (CBF) values, higher mean transit time (MTT) values, and a broader range of CBF and MTT values as compared with SVD+. Mean transit time value differences between the core/penumbra and contralateral hemispheres were statistically significant using sSVD, whereas those of SVD+ were not. Goodness of fit between algorithms for the core/penumbra was lower for CBF (0.483) and MTT (0.494), as compared with time to peak (0.891) and cerebral blood volume (0.997). CONCLUSIONS: In this study using identical source data for patients with MCA AIS, use of either sSVD or SVD+ analyses created statistically significant differences in the CTP value results. Tracer delay-sensitive and -insensitive algorithms impact CTP results in AIS and controls, highlighting the need to pursue additional studies that assess the variability, accuracy, and clinical implications of CTP results generated when using heterogeneous deconvolution algorithms.
机译:目的:本研究的目的是比较通过标准奇异值分解(sSVD)解卷积和示踪剂延迟产生的相同大脑中动脉(MCA)急性缺血性卒中(AIS)数据集的计算机断层扫描(CTP)结果的变异性不敏感奇异值分解(SVD +)算法分析。方法:回顾性分析了9例单侧MCA AIS病例和9例对照的全脑320排CTP数据集。测量组合的核心/半影,对侧半球和动脉区域的计算机断层扫描灌注值,并将其与文献值进行比较。提供了简单的线性回归模型来预测相应的SVD +值和sSVD CTP值。结果:与SVD +相比,sSVD在核心/半影中产生了较低的脑血流量(CBF)值,较高的平均通过时间(MTT)值以及较大的CBF和MTT值范围。使用sSVD,核心/半影和对侧半球之间的平均穿越时间值差异具有统计学意义,而SVD +则没有。与峰值时间(0.891)和脑血容量(0.997)相比,CBF(0.483)和MTT(0.494)的核心/半影算法之间的拟合优度较低。结论:在本研究中,对于MCA AIS患者使用相同的源数据,使用sSVD或SVD +分析创建的CTP值结果存在统计学上的显着差异。示踪剂延迟敏感和不敏感算法会对AIS和控件中的CTP结果产生影响,这突出表明有必要继续进行其他研究,以评估使用异构反卷积算法生成的CTP结果的变异性,准确性和临床意义。

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