ArticleMedical physics2024
Technical note: TIGRE-DE for the creation of virtual monoenergetic images from dual-energy cone-beam CT.
Article in Medical physics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Refining imaging parameters for dual-energy cone-beam computed tomography in image-guided radiation therapy.Journal of applied clinical medical physics · 2026Article
- Impact of dose allocation between high- and low-kV scans on virtual monoenergetic image quality in developmental dual-energy cone-beam CT for image-guided radiotherapy.Journal of applied clinical medical physics · 2026Article
- Fast, automated optimization of virtual monoenergetic images with the dual-energy image synthesizer for cone-beam CT.Journal of applied clinical medical physics · 2025Article
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6 authors.
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Abstract
backgroundDual-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.
methodsWe 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.
resultsAll 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.
conclusionsTIGRE-DE successfully implements DE-CBCT material decomposition and VM image creation in an accessible, open-source platform.
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