Evidence map›Paper›PMID 31152568›Full record

ArticleMedical physics2019

Independent recalculation outperforms traditional measurement-based IMRT QA methods in detecting unacceptable plans.

Stephen F Kry, Mallory C Glenn, Christine B Peterson, Daniela Branco, Hunter Mehrens, Angela Steinmann, David S Followill

Abstract read
In one paragraph

Article in Medical physics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
36citing papers in PubMed, 1 pooled it
–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

36 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Guideline
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  14. A virtual phantom for patient-specific QA On A 1.5T MR-linac.Journal of applied clinical medical physics · 2024
    Article
  15. Article
  16. Article
  17. Article
  18. IMRT QA result prediction via MLC transmission decomposition.Journal of applied clinical medical physics · 2023
    Article
  19. Characterizing the interplay of treatment parameters and complexity and their impact on performance on an IROC IMRT phantom using machine learning.Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology · 2023
    Article
  20. 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

7 authors.

Stephen F KryDepartment of Radiation Physics, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX, 7030, USA.
Mallory C GlennDepartment of Radiation Physics, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX, 7030, USA.
Christine B PetersonGraduate School of Biomedical Sciences, The University of Texas Houston Health Science Center, Houston, TX, USA.
Daniela BrancoDepartment of Radiation Physics, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX, 7030, USA.
Hunter MehrensDepartment of Radiation Physics, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX, 7030, USA.
Angela SteinmannDepartment of Radiation Physics, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX, 7030, USA.
David S FollowillDepartment of Radiation Physics, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX, 7030, USA.

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 CA180803NIH/NCI CA214526NIH/NCI CCSG P30CA016672Public Health Service grant CA180803
6 · The paper itself

Abstract

purposeTo evaluate the performance of an independent recalculation and compare it against current measurement-based patient specific intensity-modulated radiation therapy (IMRT) quality assurance (QA) in predicting unacceptable phantom results as measured by the Imaging and Radiation Oncology Core (IROC).

methodsWhen institutions irradiate the IROC head and neck IMRT phantom, they are also asked to submit their internal IMRT QA results. Separately from this, IROC has previously created reference beam models on the Mobius3D platform to independently recalculate phantom results based on the institution's DICOM plan data. The ability of the institutions' IMRT QA to predict the IROC phantom result was compared against the independent recalculation for 339 phantom results collected since 2012. This was done to determine the ability of these systems to detect failing phantom results (i.e., large errors) as well as poor phantom results (i.e., modest errors). Sensitivity and specificity were evaluated using common clinical thresholds, and receiver operator characteristic (ROC) curves were used to compare across different thresholds.

resultsOverall, based on common clinical criteria, the independent recalculation was 12 times more sensitive at detecting unacceptable (failing) IROC phantom results than clinical measurement-based IMRT QA. The recalculation was superior, in head-to-head comparison, to the EPID, ArcCheck, and MapCheck devices. The superiority of the recalculation vs these array-based measurements persisted under ROC analysis as the recalculation curve had a greater area under it and was always above that for these measurement devices. For detecting modest errors (poor phantom results rather than failing phantom results), neither the recalculation nor measurement-based IMRT QA performed well.

conclusionsA simple recalculation outperformed current measurement-based IMRT QA methods at detecting unacceptable plans. These findings highlight the value of an independent recalculation, and raise further questions about the current standard of measurement-based IMRT QA.

Indexed as

Radiotherapy, Intensity-ModulatedPhantoms, ImagingQuality ControlRadiotherapy DosageRadiotherapy Planning, Computer-AssistedIMRT QAMobiuspatient-specific QArecalculation

Identifiers

PMID31152568
PMCPMC6692191

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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.