Evidence map›Paper›PMID 32452657›Full record

ArticleJournal of applied clinical medical physics2020

Automation of Monte Carlo-based treatment plan verification for proton therapy.

Maduka Kaluarachchi, Vadim Moskvin, Fakhriddin Pirlepesov, Lydia J Wilson, Fang Xie, Austin M Faught

Abstract read
In one paragraph

Article in Journal of applied clinical medical physics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Three-dimensional dose and LETMedical physics · 2022
    Article
  3. Article
  4. 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

6 authors.

Maduka KaluarachchiDepartment of Radiation Oncology, St. Jude Children's Research Hospital, Memphis, TN, USA.
Vadim MoskvinDepartment of Radiation Oncology, St. Jude Children's Research Hospital, Memphis, TN, USA.
Fakhriddin PirlepesovDepartment of Radiation Oncology, St. Jude Children's Research Hospital, Memphis, TN, USA.
Lydia J WilsonDepartment of Radiation Oncology, St. Jude Children's Research Hospital, Memphis, TN, USA.
Fang XieDepartment of Radiation Oncology, St. Jude Children's Research Hospital, Memphis, TN, USA.
Austin M FaughtDepartment of Radiation Oncology, St. Jude Children's Research Hospital, Memphis, TN, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeIndependent calculations of proton therapy plans are an important quality control procedure in treatment planning. When using custom Monte Carlo (MC) models of the beamline, deploying the calculations can be laborious, time consuming, and require in-depth knowledge of the computational environment. We developed an automated framework to remove these barriers and integrate our MC model into the clinical workflow. MATERIALS AND

methodsThe Eclipse Scripting Application Programming Interface was used to initiate the automation process. A series of MATLAB scripts were then used for preprocessing of input data and postprocessing of results. Additional scripts were used to monitor the calculation process and appropriately deploy calculations to an institutional high-performance computing facility. The automated framework and beamline models were validated against 160 patient specific QA measurements from an ionization chamber array and using a ±3%/3 mm gamma criteria.

resultsThe automation reduced the human-hours required to initiate and run a calculation to 1-2 min without leaving the treatment planning system environment. Validation comparisons had an average passing rate of 99.4% and were performed at depths ranging from 1 to 15 cm.

conclusionAn automated framework for running MC calculations was developed which enables the calculation of dose and linear energy transfer within a clinically relevant workflow and timeline. The models and framework were validated against patient specific QA measurements and exhibited excellent agreement. Before this implementation, execution was prohibitively complex for an untrained individual and its use restricted to a research environment.

Indexed as

Proton TherapyRadiotherapy, Intensity-ModulatedAlgorithmsAutomationHumansMonte Carlo MethodPhantoms, ImagingRadiotherapy DosageRadiotherapy Planning, Computer-AssistedautomationMonte Carloproton therapy

Identifiers

PMID32452657
PMCPMC7484839

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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.