Evidence map›Paper›PMID 36841341›Full record

ArticleRadiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology2023

Characterizing the interplay of treatment parameters and complexity and their impact on performance on an IROC IMRT phantom using machine learning.

Hunter Mehrens, Andrea Molineu, Nadia Hernandez, Laurence Court, Rebecca Howell, David Jaffray, Christine B Peterson, Julianne Pollard-Larkin, Stephen F Kry

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In one paragraph

Article in Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

9 authors.

Hunter MehrensIROC Houston Quality Assurance Center, The University of Texas MD Anderson Cancer Center, Houston, TX, USA; Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA; The University of Texas MD Anderson Cancer Center UT Health Houston Graduate School of Biomedical Sciences, Houston, TX, USA.
Andrea MolineuIROC Houston Quality Assurance Center, The University of Texas MD Anderson Cancer Center, Houston, TX, USA; Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Nadia HernandezIROC Houston Quality Assurance Center, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Laurence CourtDepartment of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA; The University of Texas MD Anderson Cancer Center UT Health Houston Graduate School of Biomedical Sciences, Houston, TX, USA.
Rebecca HowellDepartment of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA; The University of Texas MD Anderson Cancer Center UT Health Houston Graduate School of Biomedical Sciences, Houston, TX, USA.
David JaffrayDepartment of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Christine B PetersonDepartment of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA; The University of Texas MD Anderson Cancer Center UT Health Houston Graduate School of Biomedical Sciences, Houston, TX, USA.
Julianne Pollard-LarkinDepartment of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA; The University of Texas MD Anderson Cancer Center UT Health Houston Graduate School of Biomedical Sciences, Houston, TX, USA.
Stephen F KryDepartment of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA; The University of Texas MD Anderson Cancer Center UT Health Houston Graduate School of Biomedical Sciences, Houston, TX, USA. Electronic address: sfkry@mdanderson.org.

Funding

Tumor Evolution and Metastasis ProgramP30CA016672 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI Scott Kopetz · 1985 to 2026
$290.8M
IROC: Enhancing local enrolling site radiological data capture capabilities for NCTN trialsU24CA180803 · NCI · AMERICAN COLLEGE OF RADIOLOGY · PI Thomas J. FitzGerald, MICHAEL V KNOPP · 2014 to 2026
$116.2M
Correcting Dose Calculation Errors in Radiation OncologyR01CA214526 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI KRY, STEPHEN F · 2017 to 2020
$594k
NCI NIH HHS P30 CA016672NCI NIH HHS R01 CA214526NCI NIH HHS U24 CA180803
6 · The paper itself

Abstract

aim of the studyTo elucidate the important factors and their interplay that drive performance on IMRT phantoms from the Imaging and Radiation Oncology Core (IROC).

methodsIROC's IMRT head and neck phantom contains two targets and an organ at risk. Point and 2D dose are measured by TLDs and film, respectively. 1,542 irradiations between 2012-2020 were retrospectively analyzed based on output parameters, complexity metrics, and treatment parameters. Univariate analysis compared parameters based on pass/fail, and random forest modeling was used to predict output parameters and determine the underlying importance of the variables.

resultsThe average phantom pass rate was 92% and has not significantly improved over time. The step-and-shoot irradiation technique had significantly lower pass rates that significantly affected other treatment parameters' pass rates. The complexity of plans has significantly increased with time, and all aperture-based complexity metrics (except MCS) were associated with the probability of failure. Random forest-based prediction of failure had an accuracy of 98% on held-out test data not used in model training. While complexity metrics were the most important contributors, the specific metric depended on the set of treatment parameters used during the irradiation.

conclusionWith the prevalence of errors in radiotherapy, understanding which parameters affect treatment delivery is vital to improve patient treatment. Complexity metrics were strongly predictive of irradiation failure; however, they are dependent on the specific treatment parameters. In addition, the use of one complexity metric is insufficient to monitor all aspects of the treatment plan.

Indexed as

Radiation OncologyRadiotherapy, Intensity-ModulatedHumansMachine LearningPhantoms, ImagingRadiotherapy DosageRadiotherapy Planning, Computer-AssistedRetrospective StudiesIROCMachine learningPhantomsPlan Complexity

Identifiers

PMID36841341
PMCPMC10121814

What OpenQuestion holds

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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.