Evidence map›Paper›PMID 30621744›Full record

ArticleRadiation oncology (London, England)2019

Simulation of dosimetry impact of 4DCT uncertainty in 4D dose calculation for lung SBRT.

Gang Liu, Fala Hu, Xuanfeng Ding, Xiaoqiang Li, Qihong Shao, Yuenan Wang, Jing Yang, Hong Quan

Abstract read
In one paragraph

Article in Radiation oncology (London, England), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
19citing 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

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

  1. DEGRO practical guideline for central nervous system radiation necrosis part 1: classification and a multistep approach for diagnosis.Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al] · 2022
    Guideline
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  12. 4DCT is long overdue for improvement.Journal of applied clinical medical physics · 2023
    Article
  13. Harmonization of dose prescription for lung stereotactic radiotherapy.Physics and imaging in radiation oncology · 2022
    Article
  14. Adoption of respiratory motion management in radiation therapy.Physics and imaging in radiation oncology · 2022
    Article
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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.

Gang LiuKey Laboratory of Artificial Micro- and Nano- structures of Ministry of Education and Center for Electronic Microscopy, School of Physics and Technology, Wuhan University, Wuhan, 430072, China.
Fala HuSchool of Mathematics and Statistics, Wuhan University, Wuhan, 430072, China.
Xuanfeng DingProton Therapy Center Beaumont Health, Royal Oak, MI, 48074, USA.
Xiaoqiang LiProton Therapy Center Beaumont Health, Royal Oak, MI, 48074, USA.
Qihong ShaoWuhan Zhongyuan Electronics Group Co. LTD, Wuhan, 430205, China.
Yuenan WangCancer Hospital Chinese Academy of Medical Sciences, Shenzhen Center, Shenzhen, 518000, China.
Jing YangCancer Center, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China.
Hong QuanKey Laboratory of Artificial Micro- and Nano- structures of Ministry of Education and Center for Electronic Microscopy, School of Physics and Technology, Wuhan University, Wuhan, 430072, China. csp6606@sina.com.

Funding

National Natural Science Foundation of China No. 10875092National Natural Science Foundation of China No.31271511Natural Science Foundation of Hubei Province of China No.2012KB04449the Natural Science Foundation of Union Hospital, Tongji Medical College, Huazhong University of Science and Technology No.02.03.2017-289
6 · The paper itself

Abstract

backgroundDue to the heterogeneity of patient's individual respiratory motion pattern in lung stereotactic body radiotherapy (SBRT), treatment planning dose assessment using a traditional four-dimensional computed tomography (4DCT_traditional) images based on a uniform breathing curve may not represent the true treatment dose delivered to the patient. The purpose of this study was to evaluate the accumulated dose discrepancy between based on the 4DCT_traditional and true 4DCT (4DCT_true) that incorporated with the patient's real entire breathing motion. The study also explored a novel 4D robust planning strategy to compensate for such heterogeneity respiratory motion uncertainties.

methodsSimulated and measured patient specific breathing curves were used to generate 4D targets motion CT images. Volumetric-modulated arc therapy (VMAT) was planned using two arcs. Accumulated dose was obtained by recalculating the plan dose on each individual phase image and then deformed the dose from each phase image to the reference image. The "4 D dose" (D

resultsWith increasing breathing amplitude from 5 to 20 mm, target [Formula: see text], [Formula: see text] increased from 1.59,1.39 to 10.15%,8.66% respectively. When the standard deviation of breathing amplitude increased from 15 to 35% of the mean amplitude, [Formula: see text], [Formula: see text] increased from 4.06,3.48 to 10.25%,6.63% respectively. The 4D Ro-VMAT plan significantly improve the target dose compared to VMAT plan.

conclusionWhen the breathing curve amplitude is more than 10 mm and standard deviation of amplitude is higher than 25% of mean amplitude, special care is needed to choose an appropriated dose accumulation approach to evaluate lung SBRT plan target coverage robustness. The proposed 4D Ro_VMAT strategy based on the pdf of patient specific breathing curve could effectively compensate such uncertainties.

Indexed as

Phantoms, ImagingComputer SimulationFour-Dimensional Computed TomographyHumansImage Interpretation, Computer-AssistedLung NeoplasmsMovementRadiosurgeryRadiotherapy DosageRadiotherapy, Intensity-ModulatedRadiotherapy Planning, Computer-AssistedRespirationRespiratory-Gated Imaging Techniques

Identifiers

PMID30621744
PMCPMC6323842

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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.