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European Radiology

, Volume 25, Issue 12, pp 3415–3422 | Cite as

Effects of radiation dose reduction in Volume Perfusion CT imaging of acute ischemic stroke

  • Ahmed E. Othman
  • Carolin Brockmann
  • Zepa Yang
  • Changwon Kim
  • Saif Afat
  • Rastislav Pjontek
  • Omid Nikobashman
  • Marc A. Brockmann
  • Jong Hyo Kim
  • Martin Wiesmann
Neuro

Abstract

Purpose

To examine the influence of radiation dose reduction on image quality and sensitivity of Volume Perfusion CT (VPCT) maps regarding the detection of ischemic brain lesions.

Methods and materials

VPCT data of 20 patients with suspected ischemic stroke acquired at 80 kV and 180 mAs were included. Using realistic reduced-dose simulation, low-dose VPCT datasets with 144 mAs, 108 mAs, 72 mAs and 36 mAs (80 %, 60 %, 40 % and 20 % of the original levels) were generated, resulting in a total of 100 datasets. Perfusion maps were created and signal-to-noise-ratio (SNR) measurements were performed. Qualitative analyses were conducted by two blinded readers, who also assessed the presence/absence of ischemic lesions and scored CBV and CBF maps using a modified ASPECTS-score.

Results

SNR of all low-dose datasets were significantly lower than those of the original datasets (p < .05). All datasets down to 72 mAs (40 %) yielded sufficient image quality and high sensitivity with excellent inter-observer-agreements, whereas 36 mAs datasets (20 %) yielded poor image quality in 15 % of the cases with lower sensitivity and inter-observer-agreements.

Conclusion

Low-dose VPCT using decreased tube currents down to 72 mAs (40 % of original radiation dose) produces sufficient perfusion maps for the detection of ischemic brain lesions.

Key Points

Perfusion CT is highly accurate for the detection of ischemic brain lesions

Perfusion CT results in high radiation exposure, therefore low-dose protocols are required

Reduction of tube current down to 72 mAs produces sufficient perfusion maps

Keywords

Low dose perfusion CT, Perfusion CT, Perfusion imaging, Radiation dose Stroke 

Abbreviations

ACA

Anterior cerebral artery

CBF

Cerebral blood flow

CBV

Cerebral blood volume

LD VPCT

Low-dose volume perfusion CT

MCA

Middle cerebral artery

MTT

Mean transit time

NVT

Nonviable tissue

PCA

Posterior cerebral artery

ROI

Region of interest

SD

Standard deviation

SNR

Signal-to-noise-ratio

TAR

Tissue at risk

TTD

Time-to-drain

TTP

Time-to-peak

VPCT

Volume perfusion CT

Notes

Acknowledgments

The scientific guarantor of this publication is Professor Dr. Martin Wiesmann. 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. The authors state that this work has not received any funding. One of the authors (Ahmed Othman) has significant statistical expertise. Institutional Review Board approval was received and the Institutional Review Board waived the requirement for informed patient consent. Approval from the institutional animal care committee was not required because the study was conducted on Patient data. Methodology: retrospective, diagnostic or prognostic, multicenter study.

Supplementary material

330_2015_3763_Fig6_ESM.gif (17 kb)
Fig. S1

A schematic diagram provides an overview of realistic reduced-dose simulation technique used in this study. (GIF 16 kb)

330_2015_3763_MOESM1_ESM.tif (152 kb)
High Resolution Image (TIFF 152 kb)

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Copyright information

© European Society of Radiology 2015

Authors and Affiliations

  • Ahmed E. Othman
    • 1
    • 2
  • Carolin Brockmann
    • 1
  • Zepa Yang
    • 3
    • 4
  • Changwon Kim
    • 3
    • 4
  • Saif Afat
    • 1
  • Rastislav Pjontek
    • 1
  • Omid Nikobashman
    • 1
  • Marc A. Brockmann
    • 1
  • Jong Hyo Kim
    • 3
    • 4
    • 5
  • Martin Wiesmann
    • 1
  1. 1.Department of Diagnostic and Interventional NeuroradiologyRWTH Aachen UniversityAachenGermany
  2. 2.Department for Diagnostic and Interventional RadiologyEberhard Karls University Tuebingen, University Hospital TuebingenTübingenGermany
  3. 3.Department of Transdisciplinary Studies, Graduate School of Convergence Science and TechnologySeoul National UniversitySuwonSouth Korea
  4. 4.Department of RadiologySeoul National University College of MedicineSeoulSouth Korea
  5. 5.Center for Medical-IT Convergence Technology Research, Advanced Institute of Convergence TechnologySuwonSouth Korea

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