Evidence map›Paper›PMID 36412092›Full record

ArticleJournal of applied clinical medical physics2023

Customizable landmark-based field aperture design for automated whole-brain radiotherapy treatment planning.

Yao Xiao, Carlos Cardenas, Dong Joo Rhee, Tucker Netherton, Lifei Zhang, Callistus Nguyen, Raphael Douglas, Raymond Mumme, Stephen Skett, Tina Patel and 5 more

Full text 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 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Automated treatment planning for brain and spinal metastases.Reports of practical oncology and radiotherapy : journal of Greatpoland Cancer Center in Poznan and Polish Society of Radiation Oncology · 2026
    Article
  3. Semi-automated hippocampal avoidance whole-brain radiotherapy planning.Journal of applied clinical medical physics · 2025
    Article
  4. Review
  5. Article
  6. Automated field-in-field whole brain radiotherapy planning.Journal of applied clinical medical physics · 2023
    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

15 authors.

Yao XiaoDepartment of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
Carlos CardenasDepartment of Radiation Oncology, The University of Alabama-Birmingham, Birmingham, Alabama, USA.
Dong Joo RheeDepartment of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
Tucker NethertonDepartment of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
Lifei ZhangDepartment of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
Callistus NguyenDepartment of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
Raphael DouglasDepartment of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
Raymond MummeDepartment of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
Stephen SkettDepartment of Medical Physics, Guy's & St Thomas NHS Foundation Trust, London, UK.
Tina PatelDepartment of Medical Physics, Guy's & St Thomas NHS Foundation Trust, London, UK.
Chris TrauernichtDivision of Medical Physics, Stellenbosch University and Tygerberg Academic Hospital, Stellenbosch, South Africa.
Caroline ChungDepartment of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
Hannah SimondsDivision of Radiation Oncology, Stellenbosch University and Tygerberg Academic Hospital, Stellenbosch, South Africa.
Ajay AggarwalDepartment of Medical Physics, Guy's & St Thomas NHS Foundation Trust, London, UK.
Laurence CourtDepartment of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.

Funding

Wellcome Trust
6 · The paper itself

Abstract

purposeTo develop and evaluate an automated whole-brain radiotherapy (WBRT) treatment planning pipeline with a deep learning-based auto-contouring and customizable landmark-based field aperture design.

methodsThe pipeline consisted of the following steps: (1) Auto-contour normal structures on computed tomography scans and digitally reconstructed radiographs using deep learning techniques, (2) locate the landmark structures using the beam's-eye-view, (3) generate field apertures based on eight different landmark rules addressing different clinical purposes and physician preferences. Two parallel approaches for generating field apertures were developed for quality control. The performance of the generated field shapes and dose distributions were compared with the original clinical plans. The clinical acceptability of the plans was assessed by five radiation oncologists from four hospitals.

resultsThe performance of the generated field apertures was evaluated by the Hausdorff distance (HD) and mean surface distance (MSD) from 182 patients' field apertures used in the clinic. The average HD and MSD for the generated field apertures were 16 ± 7 and 7 ± 3 mm for the first approach, respectively, and 17 ± 7 and 7 ± 3 mm, respectively, for the second approach. The differences regarding HD and MSD between the first and the second approaches were 1 ± 2 and 1 ± 3 mm, respectively. A clinical review of the field aperture design, conducted using 30 patients, achieved a 100% acceptance rate for both the first and second approaches, and the plan review achieved a 100% acceptance rate for the first approach and a 93% acceptance rate for the second approach. The average acceptance rate for meeting lens dosimetric recommendations was 80% (left lens) and 77% (right lens) for the first approach, and 70% (both left and right lenses) for the second approach, compared with 50% (left lens) and 53% (right lens) for the clinical plans.

conclusionThis study provided an automated pipeline with two field aperture generation approaches to automatically generate WBRT treatment plans. Both quantitative and qualitative evaluations demonstrated that our novel pipeline was comparable with the original clinical plans.

Indexed as

Radiotherapy, Intensity-ModulatedRadiotherapy Planning, Computer-AssistedBrainHumansRadiometryRadiotherapy DosageTomography, X-Ray Computedautomationcustomizable field aperturedeep learningwhole-brain radiotherapy

Identifiers

PMID36412092
PMCPMC10018662

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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.