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Biased visualization of hypoperfused tissue by computed tomography due to short imaging duration: improved classification by image down-sampling and vascular models

Abstract

Objectives

Lesion detection in acute stroke by computed-tomography perfusion (CTP) can be affected by incomplete bolus coverage in veins and hypoperfused tissue, so-called bolus truncation (BT), and low contrast-to-noise ratio (CNR). We examined the BT-frequency and hypothesized that image down-sampling and a vascular model (VM) for perfusion calculation would improve normo- and hypoperfused tissue classification.

Methods

CTP datasets from 40 acute stroke patients were retrospectively analysed for BT. In 16 patients with hypoperfused tissue but no BT, repeated 2-by-2 image down-sampling and uniform filtering was performed, comparing CNR to perfusion-MRI levels and tissue classification to that of unprocessed data. By simulating reduced scan duration, the minimum scan-duration at which estimated lesion volumes came within 10 % of their true volume was compared for VM and state-of-the-art algorithms.

Results

BT in veins and hypoperfused tissue was observed in 9/40 (22.5 %) and 17/40 patients (42.5 %), respectively. Down-sampling to 128 × 128 resolution yielded CNR comparable to MR data and improved tissue classification (p = 0.0069). VM reduced minimum scan duration, providing reliable maps of cerebral blood flow and mean transit time: 5 s (p = 0.03) and 7 s (p < 0.0001), respectively).

Conclusions

BT is not uncommon in stroke CTP with 40-s scan duration. Applying image down-sampling and VM improve tissue classification.

Key points:

Too-short imaging duration is common in clinical acute stroke CTP imaging.

The consequence is impaired identification of hypoperfused tissue in acute stroke patients.

The vascular model is less sensitive than current algorithms to imaging duration.

Noise reduction by image down-sampling improves identification of hypoperfused tissue by CTP.

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Abbreviations

VM:

Vascular model

sSVD:

Standard singular value decomposition

oSVD:

Circular singular-value decomposition with oscillation index

CNR:

Contrast-to-noise ratio

CTC:

Concentration-time curve

AIF:

Arterial input function

propLD:

Proportion of lesion detected

TP:

True-positive

FP:

False-positive

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Acknowledgments

The scientific guarantor of this publication is Professor Leif Østergaard. The authors of this manuscript declare no relationships with any companies whose products or services may be related to the subject matter of the article. This study has received funding from the Danish Agency for Science, Technology and Innovation, grant 09-065250. One of the authors (Kim Mouridsen) has significant statistical expertise. Institutional Review Board approval was obtained. Written informed consent was waived by the Institutional Review Board. Thirty-two of the included subjects were previously investigated as part of an unrelated study investigating the fate of non-core-non-penumbral tissue. Lesion volumes on follow-up images for these patients were hence reported in Brain. 2011 Jun;134(Pt 6):1765-76. Methodology: retrospective, diagnostic or prognostic multi-centre study.

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Correspondence to Irene Klærke Mikkelsen.

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Mikkelsen, I.K., Jones, P.S., Ribe, L.R. et al. Biased visualization of hypoperfused tissue by computed tomography due to short imaging duration: improved classification by image down-sampling and vascular models. Eur Radiol 25, 2080–2088 (2015). https://doi.org/10.1007/s00330-015-3602-x

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  • DOI: https://doi.org/10.1007/s00330-015-3602-x

Keywords

  • CTP
  • Bolus truncation
  • Deconvolution
  • Acute stroke
  • Noise reduction