Evidence map›Paper›PMID 39640275›Full record

ArticleFrontiers in oncology2024

Dosimetric analysis of half-field-based VMAT with the deep inspiration breath-hold technique for left breast cancer patients following breast-conserving surgery.

Weiwei Wu, Hui Yin, Zhiwei Liu, Lipeng Liu, Chengjian Xiao, Ying Xiao, Jinquan Ding, Qungui Zhang, Hailiang Guo

Abstract read
In one paragraph

Article in Frontiers in oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

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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

2 citing papers in PubMed.

  1. 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

9 authors.

Weiwei Wu *Center of Radiation Oncology, Ganzhou Cancer Hospital, Ganzhou, Jiangxi, China.
Hui Yin *Medical Imaging Department, Ganzhou Cancer Hospital, Ganzhou, Jiangxi, China.
Zhiwei LiuCenter of Radiation Oncology, Ganzhou Cancer Hospital, Ganzhou, Jiangxi, China.
Lipeng LiuCenter of Radiation Oncology, Ganzhou Cancer Hospital, Ganzhou, Jiangxi, China.
Chengjian XiaoCenter of Radiation Oncology, Ganzhou Cancer Hospital, Ganzhou, Jiangxi, China.
Ying XiaoCenter of Radiation Oncology, Ganzhou Cancer Hospital, Ganzhou, Jiangxi, China.
Jinquan DingCenter of Radiation Oncology, Ganzhou Cancer Hospital, Ganzhou, Jiangxi, China.
Qungui ZhangCenter of Radiation Oncology, Ganzhou Cancer Hospital, Ganzhou, Jiangxi, China.
Hailiang GuoDepartment of Oncology, the First Affiliated Hospital of Gannan Medical University, Ganzhou, Jiangxi, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Compared the dosimetric characteristics of half-field-based VMAT and half-field-based IMRT for left breast cancer patients combined with deep inspiration breath-hold (DIBH) and free breathing (FB) techniques. Methods: Twenty-one left breast cancer patients were included. Each patient underwent DIBH and FB CT scans, IMRT and VMAT plans in half-field beam mode for both breathing techniques, resulting in four plans: FB-IMRT (F-IMRT), FB-VMAT (F-VMAT), DIBH-IMRT (D-IMRT) and DIBH-VMAT (D-VMAT). The conformity index (CI), homogeneity index (HI), and the doses received at the heart, left anterior descending (LAD), left lung, right breast, and right lung, were compared among plans.The correlation between the difference in the volume of lung_L (ΔLVL) and the difference in the mean dose (ΔDmean) of lung_L under the DIBH and FB plans, the correlation between the difference in the heart-chest distance (ΔHCD) and the ΔDmean of the heart,LAD under the DIBH and FB plans. Results: The D-VMAT plan lower lung_L V5 than both the F-IMRT and F-VMAT plans ( Conclusion: the D-VMAT plan offered enhanced protection for OARs. The integration of the DIBH technique with half-field and VMAT technology in the D-VMAT plan offers a superior dose distribution.

Indexed as

breast cancerdeep inspiration breath-holdingdosimetryhalf beamVMAT

Identifiers

PMID39640275
PMCPMC11617583

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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.