Comparison of a Bayesian Estimation Algorithm and Singular Value Decomposition Algorithms for 80-detector Row CT Perfusion in Patients with Acute Ischemic Stroke

Overview

Journal Radiol Med

Specialty Radiology

Date 2021 Jan 20

PMID 33469818

Citations 7

Authors

Shota Ichikawa

Hiroyuki Yamamoto

Takumi Morita

Affiliations

Soon will be listed here.

Abstract

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 (ρ = 0.78 and 0.80, p < 0.001) than with the reformulated SVD algorithm (ρ = 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; ρ = 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.

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