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European Radiology

, Volume 28, Issue 10, pp 4379–4388 | Cite as

Assessment of an advanced virtual monoenergetic reconstruction technique in cerebral and cervical angiography with third-generation dual-source CT: Feasibility of using low-concentration contrast medium

  • Lu Zhao
  • Fengtan Li
  • Zewei Zhang
  • Zhang Zhang
  • Yingjian Jiang
  • Xinyu Wang
  • Jun Gu
  • Dong Li
Computed Tomography
First Online:
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Revised:
Accepted:
  • 120 Downloads

Abstract

Objectives

To investigate the feasibility of low-concentration contrast media (LC-CM) in cerebral and cervical dual-energy CT angiography (DE-CTA) using an advanced monoenergetic (Mono+) reconstruction technique.

Methods

Sixty-five consecutive patients prospectively selected to undergo cerebral and cervical DE-CTA were randomised into two groups: 32 patients (63.7 ± 9.7 years) in the high-concentration contrast medium (HC-CM) group with iopromide 370 and 33 patients (60.7 ± 10.8 years) in the low-concentration contrast medium (LC-CM) group with iodixanol 270. Traditional monoenergetic (Mono) and Mono+ images from 40 to 100 keV levels (at 10-keV intervals) and the standard mixed (Mixed, 120 kVp equivalent) images were reconstructed. Subjective image quality parameters included the contrast-to-noise ratio (CNR) and objective image quality parameters were evaluated and compared between the two groups.

Results

The 40-keV Mono+ images in the LC-CM group showed comparable objective CNR (common carotid arteries: 83.7 ± 24.5 vs. 78.1 ± 23.2; internal carotid arteries: 82.2 ± 26.8 vs. 76.8 ± 24.1; middle cerebral arteries: 72.5 ± 24.6 vs. 70.6 ± 19.2; all p > 0.05) and subjective image scores (3.95 ± 0.19 vs. 3.83 ± 0.35; p > 0.05) compared with Mixed images in the HC-CM group.

Conclusion

The Mono+ reconstruction technique could reduce the concentration of iodinated CM in the diagnosis of cerebral and cervical angiography.

Key Points

• Mono+ shows decreased noise and superior CNR compared with Mono.

• The 40-keV Mono+ images show the highest CNR in the LC-CM group.

• The Mono+ reconstruction technique could reduce the concentration of iodinated CM.

Keywords

Cerebral arteries Carotid arteries Computed tomography angiography Monoenergetic imaging Low-concentration contrast medium 

Abbreviations

AA

Ascending aorta

CCA

Common carotid arteries

CIN

Contrast-induced nephropathy

CM

Contrast medium

CNR

Contrast-to-noise ratio

CTA

Computed tomographic angiography

DE-CT

Dual-energy CT

DS-CT

Dual-source CT

HC-CM

High-concentration contrast medium

HU

Hounsfield units

ICA

Internal carotid arteries

LC-CM

Low-concentration contrast medium

MCA

Middle cerebral arteries

Mixed

Standard mixed

Mono

Traditional monoenergetic

Mono+

Advanced monoenergetic

ROI

Region of interest

SD

Standard deviation

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Notes

Funding

This study has received funding by the Tianjin Research Program of Application Foundation and Advanced Technology (grant 14JCZDJC57000) and National Natural Science Foundation of China (grant 81301217).

Compliance with ethical standards

Guarantor

The scientific guarantor of this publication is Dong Li.

Conflict of interest

The authors of this manuscript declare relationships with the following companies: Gu Jun is on the speakers' bureau of Siemens Healthineers, Computed Tomography division. The other authors of this manuscript declare no relationships with any companies whose products or services may be related to the subject matter of the article.

Statistics and biometry

No complex statistical methods were necessary for this paper.

Informed consent

Written informed consent was waived by the Institutional Review Board.

Ethical approval

Institutional Review Board approval was obtained.

Methodology

• prospective

• case-control study

• performed at one institution

Supplementary material

330_2018_5407_MOESM1_ESM.docx (137 kb)
ESM 1 (DOCX 136 kb)

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Copyright information

© European Society of Radiology 2018

Authors and Affiliations

  • Lu Zhao
    • 1
  • Fengtan Li
    • 1
  • Zewei Zhang
    • 1
  • Zhang Zhang
    • 1
  • Yingjian Jiang
    • 1
  • Xinyu Wang
    • 1
  • Jun Gu
    • 2
  • Dong Li
    • 1
  1. 1.Department of RadiologyTianjin Medical University General HospitalTianjinChina
  2. 2.Siemens HealthineersBeijingChina

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