Evidence map›Paper›PMID 36576418›Full record

ArticleJournal of applied clinical medical physics2023

Effectiveness of robust optimization against geometric uncertainties in TomoHelical planning for prostate cancer.

Takayuki Yagihashi, Kazumasa Inoue, Hironori Nagata, Masashi Yamanaka, Akihiro Yamano, Shunsuke Suzuki, Wataru Yamakabe, Naoki Sato, Motoko Omura, Tatsuya Inoue

Open access · goldAbstract read
In one paragraph

Article in Journal of applied clinical medical physics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
2.4field-weighted citation impact, top 12% 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

7 citing papers in PubMed, 10 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Review
  5. Article
  6. Article
  7. 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

10 authors at 4 institutions in 1 country.

Takayuki YagihashiDepartment of Medical Physics, Shonan Kamakura General Hospital, Kamakura City, Kanagawa, Japan.
Kazumasa InoueGraduate School of Human Health Sciences, Tokyo Metropolitan University, Arakawa-ku, Tokyo, Japan.
Hironori NagataDepartment of Medical Physics, Shonan Kamakura General Hospital, Kamakura City, Kanagawa, Japan.
Masashi YamanakaDepartment of Medical Physics, Shonan Kamakura General Hospital, Kamakura City, Kanagawa, Japan.
Akihiro YamanoDepartment of Medical Physics, Shonan Kamakura General Hospital, Kamakura City, Kanagawa, Japan.
Shunsuke SuzukiDepartment of Medical Physics, Shonan Kamakura General Hospital, Kamakura City, Kanagawa, Japan.
Wataru YamakabeDepartment of Medical Physics, Shonan Kamakura General Hospital, Kamakura City, Kanagawa, Japan.
Naoki SatoDepartment of Medical Physics, Shonan Kamakura General Hospital, Kamakura City, Kanagawa, Japan.
Motoko OmuraDepartment of Radiation Oncology, Shonan Kamakura General Hospital, Kamakura City, Kanagawa, Japan.
Tatsuya InoueDepartment of Medical Physics, Shonan Kamakura General Hospital, Kamakura City, Kanagawa, Japan.
Shonan Kamakura General Hospital · JPJuntendo University · JPOsaka University · JPTokyo Metropolitan University · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundGeometrical uncertainties in patients can severely affect the quality of radiotherapy. PURPOSE: We evaluated the dosimetric efficacy of robust optimization for helical intensity-modulated radiotherapy (IMRT) planning in the presence of patient setup uncertainty and anatomical changes.

methodsTwo helical IMRT plans for 10 patients with localized prostate cancer were created using either minimax robust optimization (robust plan) or a conventional planning target volume (PTV) margin approach (PTV plan). Plan robustness was evaluated by creating perturbed dose plans with setup uncertainty from isocenter shifts and anatomical changes due to organ variation. The magnitudes of the geometrical uncertainties were based on the patient setup uncertainty considered during robust optimization, which was identical to the PTV margin. The homogeneity index, and target coverage (TC, defined as the V100% of the clinical target volume), and organs at risk (OAR; rectum and bladder) doses were analyzed for all nominal and perturbed plans. A statistical t-test was performed to evaluate the differences between the robust and PTV plans.

resultsComparison of the nominal plans showed that the robust plans had lower OAR doses and a worse homogeneity index and TC than the PTV plans. The evaluations of robustness that considered setup errors more than the PTV margin demonstrated that the worst-case perturbed scenarios for robust plans had significantly higher TC while maintaining lower OAR doses. However, when anatomical changes were considered, improvement in TC from robust optimization was not observed in the worst-case perturbed plans.

conclusionsFor helical IMRT planning in localized prostate cancer, robust optimization provides benefits over PTV margin-based planning, including better OAR sparing, and increased robustness against systematic patient-setup errors.

Indexed as

Prostatic NeoplasmsRadiotherapy, Intensity-ModulatedHumansMaleOrgans at RiskRadiotherapy DosageRadiotherapy Planning, Computer-AssistedUncertaintyhelical tomotherapyintensity-modulated radiotherapylocalized prostate cancerminimax robust optimization

Identifiers

PMID36576418
PMCPMC10113685
OpenAlexW4312226658

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.