ArticlePhysics in medicine and biology2020
Fast-switching dual energy cone beam computed tomography using the on-board imager of a commercial linear accelerator.
Article in Physics in medicine and biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
12 citing papers in PubMed, 24 citations in OpenAlex.
- 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
- Characterization and Clinical Translation of a Novel Prototype Kilovoltage Dual-Layer Imager for Onboard Imaging.International journal of radiation oncology, biology, physics · 2026Article
- Multi-Material Decomposition Using Spectral Diffusion Posterior Sampling.IEEE transactions on bio-medical engineering · 2025Article
- Optimization-based image reconstruction regularized with inter-spectral structural similarity for limited-angle dual-energy cone-beam CT.Physics in medicine and biology · 2025Article
- Fast, automated optimization of virtual monoenergetic images with the dual-energy image synthesizer for cone-beam CT.Journal of applied clinical medical physics · 2025Article
- CT Material Decomposition using Spectral Diffusion Posterior Sampling.Conference proceedings. International Conference on Image Formation in X-Ray Computed Tomography · 2024Article
- Technical note: TIGRE-DE for the creation of virtual monoenergetic images from dual-energy cone-beam CT.Medical physics · 2024Article
- Feasibility of dual-energy CBCT material decomposition in the human torso with 2D anti-scatter grids and grid-based scatter sampling.Medical physics · 2024Article
- Simultaneous Image Reconstruction and Element Decomposition for Iodine Contrast Agent Visualization in Multienergy Element-Resolved Cone Beam CT.Frontiers in oncology · 2022Article
- Effect of computed tomography value error on dose calculation in adaptive radiotherapy with Elekta X-ray volume imaging cone beam computed tomography.Journal of applied clinical medical physics · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors at 4 institutions in 2 countries.
Funding
Abstract
To evaluate fast-kV switching (FS) dual energy (DE) cone beam computed tomography (CBCT) using the on-board imager (OBI) of a commercial linear accelerator to produce virtual monoenergetic (VM) and relative electron density (RED) images. Using an polynomial attenuation mapping model, CBCT phantom projections obtained at 80 and 140 kVp with FS imaging, were decomposed into equivalent thicknesses of aluminum (Al) and polymethyl methacrylate (PMMA). All projections were obtained with the titanium foil and bowtie filter in place. Basis material projections were then recombined to create VM images by using the linear attenuation coefficients at the specified energy for each material. Similarly, RED images were produced by replacing the linear attenuation values of Al and PMMA by their respective RED values in the projection space. VM and RED images were reconstructed using Feldkamp-Davis-Kress (FDK) and an iterative algorithm (iCBCT, Varian Medical Systems). Hounsfield units (HU), contrast-to-noise ratio (CNR) and RED values were compared against known values. The results after VM-CBCT production showed good material decomposition and consistent HU
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.