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European Radiology

, Volume 29, Issue 12, pp 6762–6771 | Cite as

Virtual versus true non-contrast dual-energy CT imaging for the diagnosis of aortic intramural hematoma

  • Salim Si-MohamedEmail author
  • Nicolas Dupuis
  • Valérie Tatard-Leitman
  • David Rotzinger
  • Sara Boccalini
  • Matthias Dion
  • Alain Vlassenbroek
  • Philippe Coulon
  • Yoad Yagil
  • Nadav Shapira
  • Philippe Douek
  • Loic Boussel
Emergency Radiology

Abstract

Purpose

To assess whether virtual non-contrast (VNC) images derived from contrast dual-layer dual-energy computed tomography (DL-DECT) images could replace true non-contrast (TNC) images for aortic intramural hematoma (IMH) diagnosis in acute aortic syndrome (AAS) imaging protocols by performing quantitative as well as qualitative phantom and clinical studies.

Materials and methods

Patients with confirmed IMH were included retrospectively in two centers. For in vitro imaging, a custom-made phantom of IMH was placed in a semi-anthropomorphic thorax phantom (QRM GmbH) and imaged on a DL-DECT at 120 kVp under various conditions of patient size, radiation exposure, and reconstruction modes. For in vivo imaging, 21 patients (70 ± 13 years) who underwent AAS imaging protocols at 120 kVp were included. In both studies, contrast-to-noise ratio (CNR) between hematoma and lumen was compared using a paired t test. Diagnostic confidence (1 = non-diagnostic, 4 = exemplary) for VNC and TNC images was rated by two radiologists and compared. Effective radiation doses for each acquisition were calculated.

Results

In both the phantom and clinical studies, we observed that the CNRs were similar between the VNC and TNC images. Moreover, both methods allowed differentiating the hyper-attenuation within the hematoma from the blood. Finally, we obtained equivalent high diagnostic confidence with both VNC and TNC images (VNC = 3.2 ± 0.7, TNC = 3.1 ± 0.7; p = 0.3). Finally, by suppressing TNC acquisition and using VNC, the mean effective dose reduction would be 40%.

Conclusion

DL-DECT offers similar performances with VNC and TNC images for IMH diagnosis without compromise in diagnostic image quality.

Key Points

• Dual-layer dual-energy CT enables virtual non-contrast imaging from a contrast-enhanced acquisition.

• Virtual non-contrast imaging with dual-layer dual-energy CT reduces the number of acquisitions and radiation exposure in acute aortic syndrome imaging protocol.

• Dual-layer dual-energy CT has the potential to become a suitable imaging tool for acute aortic syndrome.

Keywords

Tomography, x-ray computed Humans In vitro Acute disease Aorta 

Abbreviations

AAS

Acute aortic syndrome

CNR

Contrast-to-noise ratio

CTA

CT angiography

CTDIvol

Volume CT dose index

DL-DECT

Dual-layer dual-energy computed tomography

DLP

Dose-length product

DS-DECT

Dual-source dual-energy computed tomography

IMH

Intramural hematoma

ROI

Regions of interest

SD

Standard deviations

TNC

True non-contrast

VNC

virtual non-contrast

WED

Water-equivalent diameter

Notes

Acknowledgments

We thank Pr. Emmanuel Coche, Dr. Begum Demirler, and Dr.Matteo Pozzi for helping with the clinical study.

Funding

This work has not received any funding.

Compliance with ethical standards

Guarantor

The scientific guarantor of this publication is Professor Loic Boussel.

Conflict of interest

Philippe Coulon, Yoad Yagil, and Nadav Shapira are employees of Philips Healthcare, the manufacturer of the scanner.

Statistics and biometry

Prof. Loic Boussel provided statistical advice for this manuscript.

Informed consent

Written informed consent was waived by the Institutional Review Board.

Ethical approval

Institutional Review Board approval was not required.

Methodology

• Retrospective

• Observational

• Multicenter study

Supplementary material

330_2019_6322_MOESM1_ESM.docx (488 kb)
ESM 1 (DOCX 488 kb)

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Copyright information

© European Society of Radiology 2019

Authors and Affiliations

  • Salim Si-Mohamed
    • 1
    • 2
    Email author
  • Nicolas Dupuis
    • 1
    • 2
    • 3
  • Valérie Tatard-Leitman
    • 1
  • David Rotzinger
    • 4
  • Sara Boccalini
    • 2
  • Matthias Dion
    • 1
    • 2
    • 3
  • Alain Vlassenbroek
    • 5
  • Philippe Coulon
    • 6
  • Yoad Yagil
    • 7
  • Nadav Shapira
    • 7
  • Philippe Douek
    • 1
    • 2
  • Loic Boussel
    • 1
    • 2
  1. 1.Univ Lyon, INSA-LyonUniversité Claude Bernard Lyon 1LyonFrance
  2. 2.Radiology DepartmentHospices Civils de Lyon, CHU Louis PradelBronFrance
  3. 3.Anatomy Lab, Rockefeller FacultyLyon EstLyonFrance
  4. 4.Department of Diagnostic and Interventional RadiologyLausanne University Hospital LausanneSwitzerland
  5. 5.CT Clinical ScienceBestNetherlands
  6. 6.CT Clinical SciencePhilipsSuresnesFrance
  7. 7.Global Advanced Technologies, CT, PhilipsHaifaIsrael

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