Evidence map›Paper›PMID 34869034›Full record

ArticleFrontiers in oncology2021

How Does the Gradient Measure of the Lung SBRT Treatment Plan Depend on the Tumor Volume and Shape?

Yanhua Duan, Yang Lin, Hao Wang, Bodong Kang, Aihui Feng, Kui Ma, Hua Chen, Ying Huang, Hengle Gu, Yan Shao and 3 more

Abstract read
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Article in Frontiers in oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

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

  1. 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

13 authors.

Yanhua DuanDepartment of Radiation Oncology, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, China.
Yang LinDepartment of Radiation Oncology, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, China.
Hao WangDepartment of Radiation Oncology, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, China.
Bodong KangPekoe Team, MIM Software Inc., Cleveland, OH, United States.
Aihui FengDepartment of Radiation Oncology, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, China.
Kui MaClinical Helpdesk, Varian Medical Systems, Beijing, China.
Hua ChenDepartment of Radiation Oncology, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, China.
Ying HuangDepartment of Radiation Oncology, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, China.
Hengle GuDepartment of Radiation Oncology, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, China.
Yan ShaoDepartment of Radiation Oncology, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, China.
Tao ZhouShandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China.
Qing KongInstitute of Modern Physics, Fudan University, Shanghai, China.
Zhiyong XuDepartment of Radiation Oncology, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeGradient measure (GM) is a critical index related to normal tissue sparing in radiosurgery. This study aims to describe the dependence of GM on target volume and target shape for lung stereotactic body radiation therapy (SBRT) treatment plans.

methodsA total of 307 peripheral and 119 central lung SBRT treatment plans were enrolled for this study. A least-squares regression was used for data analysis. First, the equations with different functional forms were established to determine the dependence of GM on a univariaty (V

resultsThe power equations had the highest coefficient of determination (R

conclusionsThe GM of the lung SBRT plan is shape-independent and volume-dependent. The dependence of GM on PTV volume for peripheral and central lung cancer can be described by two different power equations. The results of this study can be used as a potential tool to assist dosimetric quality control during the radiosurgery process.

Indexed as

gradient measurelung cancerradiotherapySBRTshapevolume

Identifiers

PMID34869034
PMCPMC8636139

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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.