Evidence map›Paper›PMID 41485024›Full record

ArticleBMC medical imaging2026

ART workflow based on CBCT and end-to-end clinical dynamic phantom validation.

Zhenkai Li, Lingke Kong, Xiaoyuan Zhang, Peijun Yin, Chentong Ma, Yong Yin, Zhenjiang Li

Abstract readValidation Study
In one paragraph

Article in BMC medical imaging, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

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3 · Its place in the literature

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0 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Zhenkai LiDepartment of Radiation Oncology Physics and Technology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China.
Lingke KongManteia Technologies Co., Ltd., Xiamen, China.
Xiaoyuan ZhangDepartment of Radiation Oncology Physics and Technology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China.
Peijun YinDepartment of Radiation Oncology Physics and Technology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China.
Chentong MaDepartment of Radiation Oncology Physics and Technology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China.
Yong YinDepartment of Radiation Oncology Physics and Technology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China. yinyongsd@126.com.
Zhenjiang LiDepartment of Radiation Oncology Physics and Technology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China. zhenjli1987@163.com.

Funding

National Key Research and Development Program of China 2016YFC0105106National Natural Science Foundation of China 82102173/12275162/82072094
6 · The paper itself

Abstract

backgroundIn image-guided radiotherapy (IGRT), cone beam CT (CBCT) is usually used as a positional calibration for patients before treatment, but artifacts and inaccurate Hounsfield unit (HU) values prevent its use for clinical treatment dose calculation. In order to enable CBCT to be used for online (adaptive radiotherapy) ART treatment, it is crucial to obtain high-quality CBCT images. PURPOSE: To validate the feasibility and accuracy of the conventional accelerator’s online Adaptive Radiation Therapy (ART) workflow, providing valuable references for clinical treatment.

methodsFirstly, utilize the RegGAN model to generate synthetic CT (sCT). The quality of the sCT was evaluated using the mean absolute error (MAE), peak signal-to-noise ratio (PSNR), and structural similarity index measure (SSIM). sCT images were used for plan production and dose validation. The simulated clinical treatment process included model processing, rigid and deformable registration, delineation replication and plan replication. Dose verification was performed using CIRS Dynamic Thorax phantom and radiographic films to validate the sCT image accuracy.

resultsThe MAE in the images decreased from 52.85 ± 16.84 to 25.91 ± 3.62 (P < 0.05), the PSNR increased from 29.95 ± 2.88 to 31.61 ± 1.29 (P < 0.05), and the SSIM increased from 0.90 ± 0.02 to 0.96 ± 0.01 (P < 0.05). The Hounsfield unit (HU) distribution of the sCT images highly overlapped with that of the planning CT (pCT) images, with minimal dose calculation differences. Dynamic Motion sCT planning quality assurance achieved a pass rate of 100% at the 3%/2 mm gamma criterion. sCT Film verification using a 4 mm/3% gamma criterion yielded pass rates of 88.35% and 100% for the sCT planning system and pCT planning films, respectively.

conclusionsThe proposed ART workflow demonstrates high dosimetric accuracy in the evaluated phantom and patient cohort. The workflow serves as a proof-of-concept for conducting online adaptive radiotherapy on conventional accelerators.

Indexed as

Cone-Beam Computed TomographyPhantoms, ImagingRadiotherapy, Image-GuidedRadiotherapy Planning, Computer-AssistedWorkflowFeasibility StudiesHumansRadiotherapy DosageAdaptive radiation therapyCBCTDose verificationMotion phantomSynthetic CT

Identifiers

PMID41485024
PMCPMC12866423

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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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.