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Post-processing of computed tomography perfusion in patients with acute cerebral ischemia: variability of inter-reader, inter-region of interest, inter-input model, and inter-software

  • Computed Tomography
  • Published:
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Abstract

Objective

To determine the reproducibility of quantitative computed tomography perfusion (CTP) parameters generated using different post-processing methods and identify the relative impact of subjective factors on the robustness of CTP parameters in acute ischemic stroke (AIS).

Materials and methods

A total of 80 CTP datasets from patients with AIS or transient ischemic attack (TIA) were retrospectively post-processed by two observers using different regions of interest (ROI) types, input models, and software. The CTP parameters were derived for 10 parenchymal ROIs. The intra-class correlation coefficients (ICCs) were used to assess the reproducibility of the CTP parameters for various post-processing methods. The Spearman correlation test was used to detect potential relationships between software and input models.

Results

The ICCs with 95% confidence intervals (CIs) were 0.94 (0.93–0.96), 0.94 (0.92–0.96), 0.82 (0.79–0.86), and 0.87 (0.85–0.90) for inter-reader agreement by using elliptic ROI, irregular ROI, single-input model, and dual-input model, respectively. The ICCs with 95% CI were 0.98 (0.98–0.98), 0.46 (0.43–0.50), and 0.25 (0.20–0.30) for inter-ROI type, inter-input model, and inter-software agreement, respectively.

Conclusions

Although the CTP parameters were stable when measured using different readers with different ROI types, they varied for different input models and software. The standardization of CTP post-processing is essential to reduce variability of CTP values.

Key Points

• The CTP parameters derived by different readers with different ROI types have agreements that range from good to excellent.

• The CTP parameters derived from different input models and software programs have poor agreement but significant correlations.

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Abbreviations

AIF:

Arterial input function

AIS:

Acute ischemic stroke

CBF:

Cerebral blood flow

CBV:

Cerebral blood volume

CTP:

Computed tomography perfusion

CTT:

Computed tomography technologist

ICC:

Intra-class correlation coefficient

MCA:

Middle cerebral artery

MTT:

Mean transit time

ROI:

Region of interest

SVD:

Singular value decomposition

TIA:

Transient ischemic attack

TTP:

Time to peak

VOF:

Venous output function

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Acknowledgments

We are grateful to Miss Guo of CT Kinetics, GE Healthcare, China, for providing the CK software.

Funding

This study has received funding from the Jilin Province Special Scientific Research Project of Health, with additional funding support from the Health Special Project of Finance Department of Jilin Province and funding support from National Key Research and Development Program of China. (No.2018YFC0116400)]. The first author of this study (Zhong-ping Chen) is the key coinvestigator of this project.

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Authors and Affiliations

  1. Department of Radiology, The First Hospital of Jilin University, Changchun, 130021, Jilin, China

    Zhong-Ping Chen, Zhen-Zhen Shi, Yun-Geng Li & Dan Tong

  2. Life Sciences, GE Healthcare, Shenyang, 110000, China

    Yan Guo

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  1. Zhong-Ping Chen
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Correspondence to Dan Tong.

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Guarantor

The scientific guarantor of this publication is Dan Tong.

Conflict of interest

One of the authors of this manuscript (Yan Guo) is an employee of GE Healthcare. The remaining authors declare no relationships with any companies whose products or services may be related to the subject matter of the article.

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One of the authors has significant statistical expertise.

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Written informed consent was waived by the Institutional Review Board.

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• retrospective

• cross-sectional study

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Chen, ZP., Shi, ZZ., Li, YG. et al. Post-processing of computed tomography perfusion in patients with acute cerebral ischemia: variability of inter-reader, inter-region of interest, inter-input model, and inter-software. Eur Radiol 30, 6561–6569 (2020). https://doi.org/10.1007/s00330-020-07000-7

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  • DOI: https://doi.org/10.1007/s00330-020-07000-7

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