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Updated: Jul 2, 2025

Contrast Enhanced Vessel Imaging using MicroCT
Published on: January 27, 2011
Technical note: TIGRE-DE for the creation of virtual monoenergetic images from dual-energy cone-beam CT
Andrew Keeler1, Mathias Lehmann2, Jason Luce1
1Department of Radiation Oncology, Stritch School of Medicine, Cardinal Bernardin Cancer Center, Loyola University of Chicago, Maywood, Illinois, USA.
Background:
Dual-energy (DE)-CBCT represents a promising imaging modality that can produce virtual monoenergetic (VM) CBCT images. VM images, which provide enhanced contrast and reduced imaging artifacts, can be used to assist in soft-tissue visualization during image-guided radiotherapy.
Purpose:
This work reports the development of TIGRE-DE, a module in the open-source TIGRE toolkit for the performance of DE-CBCT and the production of VM CBCT images. This module is created to make DE-CBCT tools accessible in a wider range of clinical and research settings.
Methods:
We developed an add-on (TIGRE-DE) to the TIGRE toolkit that performs DE material decomposition. To verify its performance, sequential CBCT scans at 80 and 140 kV of a Catphan 604 phantom were decomposed into equivalent thicknesses of aluminum (Al) and polymethyl-methylacrylate (PMMA) basis materials. These basis material projections were used to synthesize VM projections for a range of x-ray energies, which were then reconstructed using the Feldkamp-Davis-Kress (FDK) algorithm. Image quality was assessed by computing Hounsfield units (HU) and contrast-to-noise ratios (CNR) for the material inserts of the phantom and comparing with the constituent 80 and 140 kV images.
Results:
All VM images generated using TIGRE-DE showed good general agreement with the theoretical HU values of the material inserts of the phantom. Apart from the highest-density inserts imaged at the extremes of the energy range, the measured HU values agree with theoretical HUs within the clinical tolerance of ±50 HU. CNR measurements for the various inserts showed that, of the energies selected, 60 keV provided the highest CNR values. Moreover, 60 keV VM images showed average CNR enhancements of 63% and 66% compared to the 80 and 140 kV full-fan protocols.
Conclusions:
TIGRE-DE successfully implements DE-CBCT material decomposition and VM image creation in an accessible, open-source platform.

