Evidence map›Paper›PMID 41164811›Full record

ArticlePrecision radiation oncology2025

Exploring the potential benefits of multi-field IMPT for stage I NSCLC SBRT: An in silico dosimetric comparison to IMRT and CyberKnife.

ZhangMing Chen, Xianrui Yan, Shu Xie, Pinjing Cheng, Dong Xiang, Cheng Tao, Qingtao Qiu, Tengxiang Li, Chengqiang Li, Huazhong Shu and 2 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Precision radiation oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

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

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. ALK-tyrosine kinase inhibitor resistance due to acquiredTranslational lung cancer research · 2026
    Article
  2. Microbiome-Driven Risk Stratification and Biotherapeutics in Radiation Enteritis.Computational and structural biotechnology journal · 2026
    Review
  3. Targeting gut microbiota and metabolites in cancer radiotherapy.Clinical and translational medicine · 2025
    Review
  4. Article
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

12 authors.

ZhangMing ChenSchool of Nuclear Science and Technology University of South China Hengyang Hunan Province China.ORCID https://orcid.org/0009-0008-0596-4411
Xianrui YanSchool of Nuclear Science and Technology University of South China Hengyang Hunan Province China.
Shu XieSchool of Nuclear Science and Technology University of South China Hengyang Hunan Province China.
Pinjing ChengSchool of Nuclear Science and Technology University of South China Hengyang Hunan Province China.
Dong XiangSchool of Nuclear Science and Technology University of South China Hengyang Hunan Province China.
Cheng TaoShandong Provincial Key Medical and Health Laboratory of Pediatric Cancer Precision Radiotherapy Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences Jinan Shandong Province China.
Qingtao QiuShandong Provincial Key Medical and Health Laboratory of Pediatric Cancer Precision Radiotherapy Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences Jinan Shandong Province China.ORCID https://orcid.org/0000-0002-8355-0125
Tengxiang LiSchool of Nuclear Science and Technology University of South China Hengyang Hunan Province China.ORCID https://orcid.org/0000-0003-4320-0363
Chengqiang LiShandong Provincial Key Medical and Health Laboratory of Pediatric Cancer Precision Radiotherapy Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences Jinan Shandong Province China.
Huazhong ShuCentre de Recherche en Information BioMdicale Sino- français Nanjing China.
Antoine SimonCentre de Recherche en Information BioMdicale Sino-français Rennes France.
Jian ZhuShandong Provincial Key Medical and Health Laboratory of Pediatric Cancer Precision Radiotherapy Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences Jinan Shandong Province China.ORCID https://orcid.org/0000-0003-2257-4593

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: Multi-field intensity-modulated proton therapy (IMPT) is a novel treatment protocol design method proposed to reduce range uncertainty. This study aimed to investigate whether multi-field IMPT has a dose distribution advantage over photon intensity-modulated radiation therapy (IMRT) and CyberKnife in stereotactic body radiotherapy (SBRT) for stage I non-small cell lung cancer (NSCLC). Methods: Twenty-nine patients who underwent photon SBRT from February 2021 to September 2022 at Shandong Cancer Hospital were included. Their Computed Tomography (CT) images were used to design CyberKnife and multi-field IMPT plans. For the photon plan (IMRT and CyberKnife), the planning target volume (PTV), which was extended from the internal gross target volume (IGTV), was prescribed at 50 Gy. For the proton plans, the planning beam-specific target volume (PBSTV) based on the IGTV was created to meet the same area as the photon PTV. Multi-field IMPT was simulated by adding additional beam angles to conventional IMPT. Dose distribution assessment factors included D Results: With each patient receiving 7-11 beams, multi-field IMPT had a better target GI than IMRT. For the lung, heart, spinal cord, chest wall, and ribs doses, the D Conclusion: Multi-field IMPT achieves favorable target coverage and OAR protection compared to IMRT and CyberKnife for SBRT of NSCLC.

Indexed as

Dosimetric studyMulti‐field intensity‐modulated proton therapyStage I non‐small cell lung cancerStereotactic body radiotherapy

Identifiers

PMID41164811
PMCPMC12559922

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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.