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

La radiologia medica volume 126, pages 795–803 (2021)Cite this article

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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Data availability

The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

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Acknowledgements

We thank Miho Kobayashi (Kurashiki Central Hospital) for her extensive proofreading.

Funding

This research received no specific grant from any funding agency in the public, commercial or not-for-profit sectors.

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Affiliations

  1. Department of Radiological Technology, Kurashiki Central Hospital, 1-1-1 Miwa, Kurashiki, Okayama, 710-8602, Japan

    Shota Ichikawa & Hiroyuki Yamamoto

  2. Department of Neurosurgery, Kurashiki Central Hospital, 1-1-1 Miwa, Kurashiki, Okayama, 710-8602, Japan

    Takumi Morita

Authors
  1. Shota Ichikawa
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  2. Hiroyuki Yamamoto
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  3. Takumi Morita
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Contributions

All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Shota Ichikawa, Hiroyuki Yamamoto and Takumi Morita. The first draft of the manuscript was written by Shota Ichikawa and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Shota Ichikawa.

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Conflicts of interest

The authors declare that there is no conflict of interest.

Ethics approval

This study was approved by the review board of Kurashiki Central Hospital and has been performed in accordance with the ethical standards as laid down in the 1964 Declaration of Helsinki and its later amendments or comparable ethical standards.

Consent to participate

The Hospital Ethics Committee granted permission to use pre-acquired anonymized patient data, and requirement for individual informed consent was waived.

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The Hospital Ethics Committee granted permission to use pre-acquired anonymized patient data, and requirement for individual informed consent was waived.

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Ichikawa, S., Yamamoto, H. & Morita, T. Comparison of a Bayesian estimation algorithm and singular value decomposition algorithms for 80-detector row CT perfusion in patients with acute ischemic stroke. Radiol med 126, 795–803 (2021). https://doi.org/10.1007/s11547-020-01316-6

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  • DOI: https://doi.org/10.1007/s11547-020-01316-6

Keywords

  • Computed tomography perfusion
  • Bayesian estimation algorithm
  • Singular value decomposition algorithm
  • Acute ischemic stroke
  • Infarction volume