Evidence map›Paper›PMID 42026428›Full record

ArticleJournal of applied clinical medical physics2026

Refining imaging parameters for dual-energy cone-beam computed tomography in image-guided radiation therapy.

Hyejoo Kang, Andrew Keeler, Matthew Georgesen, Jason Luce, Ha Nguyen, Mathias Lehmann, Sebastien Gros, John C Roeske

Abstract read
In one paragraph

Article in Journal of applied clinical medical physics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Hyejoo KangDepartment of Radiation Oncology, Stritch School of Medicine, Cardinal Bernardin Cancer Center, Loyola University of Chicago, Maywood, Illinois, USA.ORCID https://orcid.org/0000-0002-4433-0939
Andrew KeelerDepartment of Radiation Oncology, Stritch School of Medicine, Cardinal Bernardin Cancer Center, Loyola University of Chicago, Maywood, Illinois, USA.
Matthew GeorgesenDepartment of Medical Physics, Creighton University, Omaha, Nebraska, USA.
Jason LuceDepartment of Radiation Oncology, Stritch School of Medicine, Cardinal Bernardin Cancer Center, Loyola University of Chicago, Maywood, Illinois, USA.
Ha NguyenDepartment of Radiation Oncology, Stritch School of Medicine, Cardinal Bernardin Cancer Center, Loyola University of Chicago, Maywood, Illinois, USA.
Mathias LehmannVarian Imaging Laboratory, Baden, Switzerland.
Sebastien GrosDepartment of Radiation Oncology, Stritch School of Medicine, Cardinal Bernardin Cancer Center, Loyola University of Chicago, Maywood, Illinois, USA.ORCID https://orcid.org/0000-0002-6497-5152
John C RoeskeDepartment of Radiation Oncology, Stritch School of Medicine, Cardinal Bernardin Cancer Center, Loyola University of Chicago, Maywood, Illinois, USA.

Funding

Markerless Motion Tracking of Lung Tumors Using Dual Energy ImagingR01CA207483 · NCI · LOYOLA UNIVERSITY CHICAGO · PI LEHMANN, MATHIAS, ROESKE, JOHN · 2017 to 2025
$2.2M
NCI NIH HHS R01 CA207483NIH HHS R01-CA207483
6 · The paper itself

Abstract

purposeTo develop a dose estimation method for virtual monoenergetic images (VMIs) derived from sequential dual-energy (DE) cone-beam computed tomography (CBCT), enhancing image quality while reducing imaging dose. The goal is to generate VMIs with lower imaging dose than standard CBCT for future clinical applications. MATERIALS AND

methodsNormalized air kerma (K

resultsThe average difference between estimated and measured K

conclusionThis pilot study demonstrates that VMIs can improve CNR and HU uniformity while reducing imaging dose by up to 40%, relative to the PLP, without compromising HU accuracy. Our approach offers potential for optimizing VMIs by balancing image quality enhancement and dose reduction. Future work will focus on the application of advanced reconstruction algorithms to further improve VMIs quality.

Indexed as

AlgorithmsCone-Beam Computed TomographyImage Processing, Computer-AssistedPhantoms, ImagingRadiography, Dual-Energy Scanned ProjectionRadiotherapy, Image-GuidedRadiotherapy Planning, Computer-AssistedHumansRadiotherapy DosageRadiotherapy, Intensity-Modulateddual energylow imaging dosevirtual monoenergetic images

Identifiers

PMID42026428
PMCPMC13106026

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.