Evidence map›Paper›PMID 34021691›Full record

ArticleJournal of applied clinical medical physics2021

Assessment of the Sun Nuclear ArcCHECK to detect errors in 6MV FFF VMAT delivery of brain SABR using ROC analysis.

Sebastian Tattenberg, Derek Hyde, Marie-Pierre Milette, Katia Parodi, Cynthia Araujo, Marco Carlone

Open access · goldAbstract read
In one paragraph

Article in Journal of applied clinical medical physics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.4field-weighted citation impact, top 20% 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

8 citing papers in PubMed, 6 citations in OpenAlex.

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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 at 5 institutions in 2 countries.

Sebastian TattenbergDepartment of Medical Physics, Ludwig Maximilian University of Munich, Garching, Germany.
Derek HydeIrving K. Barber Faculty of Science, University of British Columbia, Okanagan Campus, Kelowna, BC, Canada.
Marie-Pierre MiletteIrving K. Barber Faculty of Science, University of British Columbia, Okanagan Campus, Kelowna, BC, Canada.
Katia ParodiDepartment of Medical Physics, Ludwig Maximilian University of Munich, Garching, Germany.
Cynthia AraujoIrving K. Barber Faculty of Science, University of British Columbia, Okanagan Campus, Kelowna, BC, Canada.
Marco CarloneIrving K. Barber Faculty of Science, University of British Columbia, Okanagan Campus, Kelowna, BC, Canada.
Interior Health · CABC Cancer Agency · CALudwig-Maximilians-Universität München · DEOkanagan University College · CAUniversity of British Columbia · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Institutions use a range of different detector systems for patient-specific quality assurance (QA) measurements conducted to assure that the dose delivered by a patient's radiotherapy treatment plan matches the calculated dose distribution. However, the ability of different detectors to detect errors from different sources is often unreported. This study contains a systematic evaluation of Sun Nuclear's ArcCHECK in terms of the detectability of potential machine-related treatment errors. The five investigated sources of error were multileaf collimator (MLC) leaf positions, gantry angle, collimator angle, jaw positions, and dose output. The study encompassed the clinical treatment plans of 29 brain cancer patients who received stereotactic ablative radiotherapy (SABR). Six error magnitudes were investigated per source of error. In addition, the Eclipse AAA beam model dosimetric leaf gap (DLG) parameter was varied with four error magnitudes. Error detectability was determined based on the area under the receiver operating characteristic (ROC) curve (AUC). Detectability of DLG errors was good or excellent (AUC >0.8) at an error magnitude of at least ±0.4 mm, while MLC leaf position and gantry angle errors reached good or excellent detectability at error magnitudes of at least 1.0 mm and 0.6°, respectively. Ideal thresholds, that is, gamma passing rates, to maximize sensitivity and specificity ranged from 79.1% to 98.7%. The detectability of collimator angle, jaw position, and dose output errors was poor for all investigated error magnitudes, with an AUC between 0.5 and 0.6. The ArcCHECK device's ability to detect errors from treatment machine-related sources was evaluated, and ideal gamma passing rate thresholds were determined for each source of error. The ArcCHECK was able to detect errors in DLG value, MLC leaf positions, and gantry angle. The ArcCHECK was unable to detect the studied errors in collimator angle, jaw positions, and dose output.

Indexed as

Radiotherapy, Intensity-ModulatedBrainHumansQuality Assurance, Health CareRadiometryRadiotherapy DosageRadiotherapy Planning, Computer-AssistedROC CurveArcCHECKPSQAQAROCSABRVMAT

Identifiers

PMID34021691
PMCPMC8200516
OpenAlexW3162607319

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.