Evidence map›Paper›PMID 38576183›Full record

ArticleJournal of applied clinical medical physics2024

Image quality characterization of an ultra-high-speed kilovoltage cone-beam computed tomography imaging system on an O-ring linear accelerator.

Euidam Kim, Yang Kyun Park, Tianyu Zhao, Eric Laugeman, Xiaodong Neo Zhao, Yao Hao, Yoonsun Chung, Hugh Lee

Abstract read
In one paragraph

Article in Journal of applied clinical medical physics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
39citing papers in PubMed, 1 pooled it
–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

39 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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.

Euidam KimDepartment of Radiation Oncology, Washington University in St Louis School of Medicine, St Louis, Missouri, USA.ORCID https://orcid.org/0000-0002-0538-8345
Yang Kyun ParkDepartment of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, Texas, USA.ORCID https://orcid.org/0000-0002-3784-2653
Tianyu ZhaoDepartment of Radiation Oncology, Washington University in St Louis School of Medicine, St Louis, Missouri, USA.
Eric LaugemanDepartment of Radiation Oncology, Washington University in St Louis School of Medicine, St Louis, Missouri, USA.
Xiaodong Neo ZhaoDepartment of Radiation Oncology, Washington University in St Louis School of Medicine, St Louis, Missouri, USA.ORCID https://orcid.org/0000-0003-1984-5372
Yao HaoDepartment of Radiation Oncology, Washington University in St Louis School of Medicine, St Louis, Missouri, USA.ORCID https://orcid.org/0000-0002-5277-7271
Yoonsun ChungDepartment of Nuclear Engineering, Hanyang University College of Engineering, Seoul, South Korea.
Hugh LeeDepartment of Radiation Oncology, Washington University in St Louis School of Medicine, St Louis, Missouri, USA.ORCID https://orcid.org/0000-0003-1325-1530

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeThe quality of on-board imaging systems, including cone-beam computed tomography (CBCT), plays a vital role in image-guided radiation therapy (IGRT) and adaptive radiotherapy. Recently, there has been an upgrade of the CBCT systems fused in the O-ring linear accelerators called HyperSight, featuring a high imaging performance. As the characterization of a new imaging system is essential, we evaluated the image quality of the HyperSight system by comparing it with Halcyon 3.0 CBCT and providing benchmark data for routine imaging quality assurance.

methodsThe HyperSight features ultra-fast scan time, a larger kilovoltage (kV) detector, a more substantial kV tube, and an advanced reconstruction algorithm. Imaging protocols in the two modes of operation, treatment mode with IGRT and the CBCT for planning (CBCTp) mode were evaluated and compared with Halcyon 3.0 CBCT. Image quality metrics, including spatial resolution, contrast resolution, uniformity, noise, computed tomography (CT) number linearity, and calibration error, were assessed using a Catphan and an electron density phantom and analyzed with TotalQA software.

resultsHyperSight demonstrated substantial improvements in contrast-to-noise ratio and noise in both IGRT and CBCTp modes compared to Halcyon 3.0 CBCT. CT number calibration error of HyperSight CBCTp mode (1.06%) closely matches that of a full CT scanner (0.72%), making it suitable for adaptive planning. In addition, the advanced hardware of HyperSight, such as ultra-fast scan time (5.9 s) or 2.5 times larger heat unit capacity, enhanced the clinical efficiency in our experience.

conclusionsHyperSight represented a significant advancement in CBCT imaging. With its image quality, CT number accuracy, and ultra-fast scans, HyperSight has a potential to transform patient care and treatment outcomes. The enhanced scan speed and image quality of HyperSight are expected to significantly improve the quality and efficiency of treatment, particularly benefiting patients.

Indexed as

AlgorithmsCone-Beam Computed TomographyImage Processing, Computer-AssistedParticle AcceleratorsPhantoms, ImagingRadiotherapy DosageRadiotherapy, Image-GuidedRadiotherapy Planning, Computer-AssistedHumansQuality Assurance, Health CareRadiographic Image Interpretation, Computer-AssistedRadiotherapy, Intensity-Modulatedcone‐beam computational tomography (CBCT)image characterizationimage qualityimaging quality assurance (QA)

Identifiers

PMID38576183
PMCPMC11087174

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LicenceCC BY
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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.