Evidence map›Paper›PMID 41477289›Full record

ArticlePrecision radiation oncology2025

Evaluating the trade-off between plan complexity, dosimetric accuracy, and treatment efficiency: Role of aperture shape controller settings in HyperArc for intracranial oligometastases.

Huipeng Meng, Yanlong Zhang, Xinrui Wang, Pengfei Liu, Weihua Zhu, Shixiong Huang, Yining Yang

Abstract read
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 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

7 authors.

Huipeng MengDepartment of Radiation Oncology Tianjin First Central Hospital, School of Medicine, Nankai University Tianjin China.
Yanlong ZhangSchool of Medical Technology Tianjin Medical College Tianjin China.
Xinrui WangDepartment of Radiation Oncology Tianjin First Central Hospital, School of Medicine, Nankai University Tianjin China.
Pengfei LiuDepartment of Radiation Oncology Tianjin First Central Hospital, School of Medicine, Nankai University Tianjin China.
Weihua ZhuClinical Application Training Department Varian Medical Systems Inc. Beijing China.
Shixiong HuangDepartment of Radiation Oncology The Affiliated Cancer Hospital of Xiangya School of Medicine Central South University/Hunan Cancer Hospital Changsha China.
Yining YangDepartment of Radiation Oncology Tianjin First Central Hospital, School of Medicine, Nankai University Tianjin China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: To evaluate the impact of different aperture shape controller (ASC) stratification strategies on the dosimetric quality and treatment efficiency of HyperArc plans for intracranial oligometastases. Methods: This retrospective study analyzed 17 patients with 1-3 intracranial oligometastases. For each patient, the HyperArc plans were reoptimized using six ASC strength settings (off, very low, low, moderate, high, and very high). Evaluations encompassed planning target volume (PTV) and organ at risk (OAR) dosimetric parameters (Paddick Conformity Index [Paddick CI], Gradient Index [GI], D Results: No statistically significant differences were observed in the PTV and OAR dosimetric parameters or gamma passing rates among the ASC strategy groups ( Conclusions: ASC stratification strategies do not significantly compromise plan dosimetric quality in HyperArc treatment for intracranial oligometastases; however, these can markedly optimize treatment efficiency, particularly by reducing MUs. Considering both plan complexity and treatment efficiency, a moderate or high ASC strength is recommended to maintain high-quality radiotherapy while improving workflow efficiency.

Indexed as

Aperture shape controllerdosimetryHyperArcintracranial oligometastasesradiotherapytreatment efficiency

Identifiers

PMID41477289
PMCPMC12750308

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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.