ArticleJournal of applied clinical medical physics2025
Fast, automated optimization of virtual monoenergetic images with the dual-energy image synthesizer for cone-beam CT.
Article in Journal of applied clinical medical physics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 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
- Experimental characterization and mitigation of scatter induced spectral contamination in photon counting CBCT for radiotherapy.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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5 authors.
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Abstract
backgroundDual-energy cone-beam CT (DE-CBCT) has become subject of recent interest due to the ability to produce virtual monoenergetic images (VMIs) with improved soft-tissue contrast and reduced nonuniformity artifacts. However, efficient production and optimization of VMIs remains an under-explored part of DE-CBCT's application. PURPOSE: This work reports on the creation of DISC (dual-energy image synthesizer for CBCT), a newly developed, open-source user interface to efficiently produce and optimize VMIs with the eventual goal of clinical application.
methodsTwo sets of CBCT scans of a Catphan 604 phantom were acquired sequentially (80 and 140 kVp) using the on-board imager of a commercial linear accelerator. Material decomposition into aluminum (Al) and polymethyl-methylacrylate (PMMA) basis materials in the projection-domain and reconstruction with the Feldkamp-Davis-Kress (FDK) algorithm of basis material images were performed in the open-source Tomographic Iterative GPU-based REconstruction (TIGRE) Matlab toolkit. Using DISC, a series of VMIs were generated via linear combinations of the basis material images without reconstructing individual VMIs at different energies. Hounsfield units (HU) were computed using an energy-dependent fit over the range of 20-150 keV. VMI energies that maximized contrast-to-noise ratio (CNR) for various materials and minimized nonuniformity artifacts were determined with 1 keV precision.
resultsOptimal CNR values for all material inserts ranged from 55 to 62 keV, showing an average CNR enhancement of 25% over the polychromatic images. Optimal uniformity is observed at 65 keV. Computed HUs show good agreement with theoretical values, with root-mean-squared error of 16 HU across the range of energies and materials.
conclusionA spectrum of VMIs from DE-CBCT was efficiently produced with 1 keV precision using DISC. Optimal energies for both soft tissue contrast and nonuniformity reduction were quickly computed with high precision. Future work will expand DISC to generate other DE-derived image types and will explore the acquisition and optimization of DE patient images.
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