Comparison of a Bayesian estimation algorithm and singular value decomposition algorithms for 80-detector row CT perfusion in patients with acute ischemic stroke

被引:14
作者
Ichikawa, Shota [1 ]
Yamamoto, Hiroyuki [1 ]
Morita, Takumi [2 ]
机构
[1] Kurashiki Cent Hosp, Dept Radiol Technol, 1-1-1 Miwa, Kurashiki, Okayama 7108602, Japan
[2] Kurashiki Cent Hosp, Dept Neurosurg, 1-1-1 Miwa, Kurashiki, Okayama 7108602, Japan
来源
RADIOLOGIA MEDICA | 2021年 / 126卷 / 06期
关键词
Computed tomography perfusion; Bayesian estimation algorithm; Singular value decomposition algorithm; Acute ischemic stroke; Infarction volume;
D O I
10.1007/s11547-020-01316-6
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
Purpose A variety of postprocessing algorithms for CT perfusion are available, with substantial differences in terms of quantitative maps. Although potential advantages of a Bayesian estimation algorithm are suggested, direct comparison with other algorithms in clinical settings remains scarce. We aimed to compare performance of a Bayesian estimation algorithm and singular value decomposition (SVD) algorithms for the assessment of acute ischemic stroke using an 80-detector row CT perfusion. Methods CT perfusion data of 36 patients with acute ischemic stroke were analyzed using the Vitrea implemented a standard SVD algorithm, a reformulated SVD algorithm and a Bayesian estimation algorithm. Correlations and statistical differences between affected and contralateral sides of quantitative parameters (cerebral blood volume [CBV], cerebral blood flow [CBF], mean transit time [MTT], time to peak [TTP] and delay) were analyzed. Agreement of the CT perfusion-estimated and the follow-up diffusion-weighted imaging-derived infarct volume were evaluated by nonparametric Passing-Bablok regression analysis. Results CBF and MTT of the Bayesian estimation algorithm were substantially different and showed a better correlation with the standard SVD algorithm (rho = 0.78 and 0.80, p < 0.001) than with the reformulated SVD algorithm (rho = 0.59 and 0.39, p < 0.001). There is no significant difference in MTT only when using the reformulated SVD algorithm (p = 0.217). Regarding the regression lines, the slope and intercept were nearly ideal with the Bayesian estimation algorithm (y = 2.42 x-6.51; rho = 0.60, p < 0.001) in comparison with the SVD algorithms. Conclusions The Bayesian estimation algorithm can lead to a better performance compared with the SVD algorithms in the assessment of acute ischemic stroke because of better delineation of abnormal perfusion areas and accurate estimation of infarct volume.
引用
收藏
页码:795 / 803
页数:9
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