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European Radiology

, Volume 25, Issue 6, pp 1655–1664 | Cite as

Noise-optimized virtual monoenergetic images and iodine maps for the detection of venous thrombosis in second-generation dual-energy CT (DECT): an ex vivo phantom study

  • Malte N. Bongers
  • Christoph SchabelEmail author
  • Bernhard Krauss
  • Ilias Tsiflikas
  • Dominik Ketelsen
  • Stefanie Mangold
  • Claus D. Claussen
  • Konstantin Nikolaou
  • Christoph Thomas
Computed Tomography

Abstract

Aims and objectives

Deep venous thrombosis (DVT) can be difficult to detect using CT due to poor and heterogeneous contrast. Dual-energy CT (DECT) allows iodine contrast optimization using noise-optimized monoenergetic extrapolations (MEIs) and iodine maps (IMs). Our aim was to assess whether MEI and IM could improve the delineation of thrombotic material within iodine-enhanced blood compared to single-energy CT (SECT).

Materials and methods

Six vessel phantoms, including human thrombus and contrast media-enhanced blood and one phantom without contrast, were placed in an attenuation phantom and scanned with DECT 100/140 kV and SECT 120 kV. IM, virtual non-contrast images (VNC), mixed images, and MEI were calculated. Attenuation of thrombi and blood were measured. Contrast and contrast-to-noise-ratios (CNRs) were calculated and compared among IM, VNC, mixed images, MEI, and SECT using paired t tests.

Results

MEI40keV and IM showed significantly higher contrast and CNR than SE120kV from high to intermediate iodine concentrations (contrast:pMEI40keV < 0.002,pIM < 0.005;CNR:pMEI40keV < 0.002,pIM < 0.004). At low iodine concentrations, MEI190keV and VNC images showed significantly higher contrast and CNR than SE120kV with inverted contrasts (contrast:pMEI190keV < 0.008,pVNC < 0.002;CNR:pMEI190keV < 0.003,pVNC < 0.002).

Conclusions

Noise-optimized MEI and IM provide significantly higher contrast and CNR in the delineation of thrombosis compared to SECT, which may facilitate the detection of DVT in difficult cases.

Key points

Poor contrast makes it difficult to detect thrombosis in CT.

Dual-energy-CT allows contrast optimization using monoenergetic extrapolations (MEI) and iodine maps (IM).

Noise-optimized-MEI and IM are significantly superior to single-energy-CT in delineation of thrombosis.

Noise-optimized-MEI and IM may facilitate the detection of deep vein thrombosis.

Keywords

Thrombosis Dual-energy computed tomography Monoenergetic images Iodine maps Single energy computed tomography 

Abbreviations

DVT

deep vein thrombosis

PE

pulmonary embolism

CM

contrast media

DECT

dual-energy computed tomography

MEI

virtual monoenergetic images

IM

iodine maps

VNC

virtual non-contrast images

SECT

single-energy computed tomography

ROI

region of interest

CNR

contrast-to-noise-ratio

Notes

Acknowledgments

The scientific guarantor of this publication is PD Dr. med. Christoph Thomas. The authors of this manuscript declare relationships with the following companies: co-author Bernhard Krauss is an employee of Siemens. He was not involved in data acquisition or data analysis. The authors state that this work has not received any funding. No complex statistical methods were necessary for this paper. Institutional Review Board approval was not required because no human subjects were studied. Methodology: prospective, experimental, performed at one institution.

Supplementary material

330_2014_3544_MOESM1_ESM.jpg (395 kb)
3D model of a custom-built phantom, including seven aspiration syringes, each including a human thrombus 3 cm3 in size at approximately 80 HU and CM-enhanced Citrat buffered blood with attenuation levels between 53 and 127 HU. (JPEG 395 kb)

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Copyright information

© European Society of Radiology 2014

Authors and Affiliations

  • Malte N. Bongers
    • 1
  • Christoph Schabel
    • 1
    Email author
  • Bernhard Krauss
    • 2
  • Ilias Tsiflikas
    • 1
  • Dominik Ketelsen
    • 1
  • Stefanie Mangold
    • 1
  • Claus D. Claussen
    • 1
  • Konstantin Nikolaou
    • 1
  • Christoph Thomas
    • 1
  1. 1.Department of Diagnostic and Interventional RadiologyUniversity Hospital of TübingenTübingenGermany
  2. 2.Siemens AG, Healthcare SectorForchheimGermany

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