Evidence map›Paper›PMID 26725727›Full record

ArticleInternational journal of radiation oncology, biology, physics2016

Exploratory Study of 4D versus 3D Robust Optimization in Intensity Modulated Proton Therapy for Lung Cancer.

Wei Liu, Steven E Schild, Joe Y Chang, Zhongxing Liao, Yu-Hui Chang, Zhifei Wen, Jiajian Shen, Joshua B Stoker, Xiaoning Ding, Yanle Hu and 6 more

Open access · greenAbstract readComparative Study
In one paragraph

Article in International journal of radiation oncology, biology, physics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 64 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
64citing papers in PubMed, 1 pooled it
12.4field-weighted citation impact, top 1% of its field
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

64 citing papers in PubMed, 1 synthesis or guideline pooled it, 130 citations in OpenAlex.

  1. Technical Considerations on Proton Therapy in NRG's Multi-Institutional Clinical Trials.International journal of radiation oncology, biology, physics · 2026
    Guideline
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  14. Medical physics · 2024
    Article
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  20. Emerging technologies for cancer therapy using accelerated particles.Progress in particle and nuclear physics · 2023
    Article

4 more citing papers are in PubMed but not listed here.

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

16 authors at 5 institutions in 1 country.

Wei LiuDepartment of Radiation Oncology, Mayo Clinic Arizona, Phoenix, Arizona. Electronic address: Liu.Wei@mayo.edu.
Steven E SchildDepartment of Radiation Oncology, Mayo Clinic Arizona, Phoenix, Arizona.
Joe Y ChangDepartment of Radiation Oncology, the University of Texas MD Anderson Cancer Center, Houston, Texas.
Zhongxing LiaoDepartment of Radiation Oncology, the University of Texas MD Anderson Cancer Center, Houston, Texas.
Yu-Hui ChangDivision of Health Sciences Research, Mayo Clinic Arizona, Phoenix, Arizona.
Zhifei WenDepartment of Radiation Physics, the University of Texas MD Anderson Cancer Center, Houston, Texas.
Jiajian ShenDepartment of Radiation Oncology, Mayo Clinic Arizona, Phoenix, Arizona.
Joshua B StokerDepartment of Radiation Oncology, Mayo Clinic Arizona, Phoenix, Arizona.
Xiaoning DingDepartment of Radiation Oncology, Mayo Clinic Arizona, Phoenix, Arizona.
Yanle HuDepartment of Radiation Oncology, Mayo Clinic Arizona, Phoenix, Arizona.
Narayan SahooDepartment of Radiation Physics, the University of Texas MD Anderson Cancer Center, Houston, Texas.
Michael G HermanDepartment of Radiation Oncology, Mayo Clinic Rochester, Rochester, Minnesota.
Carlos VargasDepartment of Radiation Oncology, Mayo Clinic Arizona, Phoenix, Arizona.
Sameer KeoleDepartment of Radiation Oncology, Mayo Clinic Arizona, Phoenix, Arizona.
William WongDepartment of Radiation Oncology, Mayo Clinic Arizona, Phoenix, Arizona.
Martin BuesDepartment of Radiation Oncology, Mayo Clinic Arizona, Phoenix, Arizona.
Mayo Clinic in Florida · USThe University of Texas MD Anderson Cancer Center · USMayo Clinic · USMayo Clinic Hospital · USMayo Clinic in Arizona · US

Funding

4D Robust Optimization in Intensity-Modulated Proton TherapyK25CA168984 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI LIU, WEI · 2012 to 2015
$450k
NCI NIH HHS K25 CA168984
6 · The paper itself

Abstract

purposeThe purpose of this study was to compare the impact of uncertainties and interplay on 3-dimensional (3D) and 4D robustly optimized intensity modulated proton therapy (IMPT) plans for lung cancer in an exploratory methodology study. METHODS AND MATERIALS: IMPT plans were created for 11 nonrandomly selected non-small cell lung cancer (NSCLC) cases: 3D robustly optimized plans on average CTs with internal gross tumor volume density overridden to irradiate internal target volume, and 4D robustly optimized plans on 4D computed tomography (CT) to irradiate clinical target volume (CTV). Regular fractionation (66 Gy [relative biological effectiveness; RBE] in 33 fractions) was considered. In 4D optimization, the CTV of individual phases received nonuniform doses to achieve a uniform cumulative dose. The root-mean-square dose-volume histograms (RVH) measured the sensitivity of the dose to uncertainties, and the areas under the RVH curve (AUCs) were used to evaluate plan robustness. Dose evaluation software modeled time-dependent spot delivery to incorporate interplay effect with randomized starting phases of each field per fraction. Dose-volume histogram (DVH) indices comparing CTV coverage, homogeneity, and normal tissue sparing were evaluated using Wilcoxon signed rank test.

results4D robust optimization plans led to smaller AUC for CTV (14.26 vs 18.61, respectively; P=.001), better CTV coverage (Gy [RBE]) (D95% CTV: 60.6 vs 55.2, respectively; P=.001), and better CTV homogeneity (D5%-D95% CTV: 10.3 vs 17.7, respectively; P=.002) in the face of uncertainties. With interplay effect considered, 4D robust optimization produced plans with better target coverage (D95% CTV: 64.5 vs 63.8, respectively; P=.0068), comparable target homogeneity, and comparable normal tissue protection. The benefits from 4D robust optimization were most obvious for the 2 typical stage III lung cancer patients.

conclusionsOur exploratory methodology study showed that, compared to 3D robust optimization, 4D robust optimization produced significantly more robust and interplay-effect-resistant plans for targets with comparable dose distributions for normal tissues. A further study with a larger and more realistic patient population is warranted to generalize the conclusions.

Indexed as

Area Under CurveCarcinoma, Non-Small-Cell LungDose Fractionation, RadiationFour-Dimensional Computed TomographyHumansImaging, Three-DimensionalLung NeoplasmsMovementOrgans at RiskProton TherapyRadiotherapy, Intensity-ModulatedRadiotherapy Planning, Computer-AssistedRelative Biological EffectivenessRespirationRetrospective StudiesTumor Burden

Identifiers

PMID26725727
PMCPMC4834263
OpenAlexW2163329967

What OpenQuestion holds

Textmetadata
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Registered trials

None linked

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.