Technical note: TIGRE-DE for the creation of virtual monoenergetic images from dual-energy cone-beam CT

Abstract

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.

Keywords: cone beam CT; dual‐energy; spectral imaging.

Figure 1:

Diagram of the DE workflow as implemented in TIGRE, with preexisting functions shaded in orange and newly-developed functionality shaded in blue. The block diagram shows the general construction of the new MaterialDecomposition.m data loader function, which loads the pair of high- and low-energy datasets and outputs a single set of VM projections at the energy specified. From there, the rest of the workflow follows the reconstruction and post-processing procedures described in past works using TIGRE.^, Note that the two projection sets require calling the VarianDataLoader.m function twice.

Figure 2:

Reconstructions of full-fan protocol images of Catphan 604 sensitometry module at 80 and 140 kV and several VM energies. A conventional CT image at 120 kV is included for reference. Beginning from the 12 o’clock position and continuing clockwise, the material inserts used are air, Teflon, Delrin at the 3 o’clock position, 20% bone, acrylic, another air insert at the 6 o’clock position, polystyrene, a background ROI at the 8 o’clock position, LDPE, 50% bone, and PMP. The apparent ring around the edge of the phantom is an artifact likely caused by an incomplete scatter correction of the bowtie filter, leading to additional estimated thickness of Al and reduced thickness of PMMA in the basis materials.^, Window/Level: 2200/100

Figure 3:

HU consistency plot for the Catphan 604 material inserts measured with a full-fan protocol. The clinical tolerance of the TrueBeam system is ±50 HU. Other studies that use iTools Reconstruction clip HU values below −1000, which is not done here, with the result that the air HU values show residuals that may not be present in other works.

Figure 4:

Full-fan CNR values: a) CNR of each insert as a function of VM energy, indicating that, of the energies used, 60 keV provides the highest CNR for all material inserts; b) Comparison between the CNR values for the 60 keV image and the constituent 80 kV and 140 kV images. Of note, the 60 keV image results in higher CNR values for all inserts than both polychromatic images.