Evidence map›Paper›PMID 36786202›Full record

ArticleMedical physics2023

Fraction optimization for hybrid proton-photon treatment planning.

Wangyao Li, Weijie Zhang, Yuting Lin, Ronald C Chen, Hao Gao

Abstract read
In one paragraph

Article in Medical physics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing 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

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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.

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3 · Its place in the literature

Who cites it

18 citing papers in PubMed.

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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

5 authors.

Wangyao LiDepartment of Radiation Oncology, Radiation Oncology, University of Kansas Medical Center, Kansas City, Kansas, USA.
Weijie ZhangDepartment of Radiation Oncology, Radiation Oncology, University of Kansas Medical Center, Kansas City, Kansas, USA.
Yuting LinDepartment of Radiation Oncology, Radiation Oncology, University of Kansas Medical Center, Kansas City, Kansas, USA.
Ronald C ChenDepartment of Radiation Oncology, Radiation Oncology, University of Kansas Medical Center, Kansas City, Kansas, USA.
Hao GaoDepartment of Radiation Oncology, Radiation Oncology, University of Kansas Medical Center, Kansas City, Kansas, USA.

Funding

Novel Optimization Methods and Treatment Planning System for Clinically-Deliverable Truly-Hybrid Proton-Photon RadiotherapyR37CA250921 · NCI · UT SOUTHWESTERN MEDICAL CENTER · PI Hao Gao · 2021 to 2026
$2.2M
Simultaneous dose and dose rate optimization for clinical FLASH proton radiotherapyR01CA261964 · NCI · UT SOUTHWESTERN MEDICAL CENTER · PI GAO, HAO · 2022 to 2025
$2.0M
NCI NIH HHS R01 CA261964NCI NIH HHS R37 CA250921NIH HHS R01CA261964NIH HHS R37CA250921
6 · The paper itself

Abstract

backgroundHybrid proton-photon radiotherapy (RT) can provide better plan quality than proton or photon only RT, in terms of robustness of target coverage and sparing of organs-at-risk (OAR). PURPOSE: This work develops a hybrid treatment planning method that can optimize the number of proton and photon fractions as well as proton and photon plan variables, so that the hybrid plans can be clinically delivered day-to-day using either proton or photon machine.

methodsIn the new hybrid treatment planning method, the total dose distribution (sum of proton dose and photon dose) is optimized for robust target coverage and optimal OAR sparing, by jointly optimizing proton spots and photon fluences, while the target dose uniformity is also enforced individually on both proton dose and photon dose, so that the hybrid plans can be separately and robustly delivered on proton or photon machine. To ensure the target dose uniformity for proton and photon plans, the number of proton and photon fractions is explicitly modeled and optimized, so that the target dose for proton and photon dose components is constrained to be a constant fraction of the total prescription dose while the plan quality based on total dose is optimized. The feasibility of hybrid planning using the proposed method is validated with representative clinical cases including abdomen, lung, head-and-neck (HN), and brain.

resultsFor all cases, hybrid plans provided better overall plan quality and OAR sparing than proton-only or photon-only plans, better target dose uniformity and robustness than proton-only plans, quantified by treatment planning objectives and dosimetric parameters. Moreover, for HN and brain cases, hybrid plans also had better target coverage than photon-only plans.

conclusionsWe have developed a new hybrid treatment planning method that optimizes number of proton and photon fractions as well as proton spots and photon fluences, for generating hybrid plans that can be separately and robustly delivered on proton or photon machines. Preliminary results have demonstrated that hybrid plans generated by the new method have better plan quality than proton-only or photon-only plans.

Indexed as

Proton TherapyRadiotherapy, Intensity-ModulatedOrgans at RiskPhotonsProtonsRadiotherapy DosageRadiotherapy Planning, Computer-AssistedProtonshybrid planningIMPTIMRTinverse planning

Identifiers

PMID36786202
PMCPMC10271913

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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.