Evidence map›Paper›PMID 37384416›Full record

ReviewMedical physics2023

AAPM Task Group Report 307: Use of EPIDs for Patient-Specific IMRT and VMAT QA.

Nesrin Dogan, Ben J Mijnheer, Kyle Padgett, Adrian Nalichowski, Chuan Wu, Matthew J Nyflot, Arthur J Olch, Niko Papanikolaou, Jie Shi, Shannon M Holmes and 2 more

Abstract readReview
In one paragraph

Review in Medical physics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 51 papers.

0numbers the graph read from it
0cells of the map it votes in
51citing 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

51 citing papers in PubMed.

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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

12 authors.

Nesrin DoganDepartment of Radiation Oncology, University of Miami Miller School of Medicine, Miami, Florida, USA.
Ben J MijnheerDepartment of Radiation Oncology, Netherlands Cancer Institute, Amsterdam, Netherlands.
Kyle PadgettDepartment of Radiation Oncology, University of Miami Miller School of Medicine, Miami, Florida, USA.
Adrian NalichowskiDepartment of Radiation Oncology, Karmanos Cancer Institute, Detroit, Michigan, USA.
Chuan WuDepartment of Radiation Oncology, Sutter Medical Foundation, Roseville, California, USA.
Matthew J NyflotDepartment of Radiation Oncology, University of Washington, Seattle, Washington, USA.
Arthur J OlchDepartment of Radiation Oncology, University of Southern California, and Children's Hospital Los Angeles, Los Angeles, California, USA.
Niko PapanikolaouDivision of Medical Physics, UT Health-MD Anderson, San Antonio, Texas, USA.
Jie ShiSun Nuclear Corporation - A Mirion Medical Company, Melbourne, Florida, USA.
Shannon M HolmesStandard Imaging, Inc., Middleton, Wisconsin, USA.
Jean MoranDepartment of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York, USA.
Peter B GreerDepartment of Radiation Oncology, Calvary Mater Newcastle Hospital, Newcastle, NSW, Australia.

Funding

X-RAY CRYSTALLOGRAPHYP30CA008748 · NCI · SLOAN-KETTERING INSTITUTE FOR CANCER RES · PI Nicholas D Socci · 1985 to 2026
$347.4M
NCI NIH HHS P30 CA008748
6 · The paper itself

Abstract

purposeElectronic portal imaging devices (EPIDs) have been widely utilized for patient-specific quality assurance (PSQA) and their use for transit dosimetry applications is emerging. Yet there are no specific guidelines on the potential uses, limitations, and correct utilization of EPIDs for these purposes. The American Association of Physicists in Medicine (AAPM) Task Group 307 (TG-307) provides a comprehensive review of the physics, modeling, algorithms and clinical experience with EPID-based pre-treatment and transit dosimetry techniques. This review also includes the limitations and challenges in the clinical implementation of EPIDs, including recommendations for commissioning, calibration and validation, routine QA, tolerance levels for gamma analysis and risk-based analysis.

methodsCharacteristics of the currently available EPID systems and EPID-based PSQA techniques are reviewed. The details of the physics, modeling, and algorithms for both pre-treatment and transit dosimetry methods are discussed, including clinical experience with different EPID dosimetry systems. Commissioning, calibration, and validation, tolerance levels and recommended tests, are reviewed, and analyzed. Risk-based analysis for EPID dosimetry is also addressed.

resultsClinical experience, commissioning methods and tolerances for EPID-based PSQA system are described for pre-treatment and transit dosimetry applications. The sensitivity, specificity, and clinical results for EPID dosimetry techniques are presented as well as examples of patient-related and machine-related error detection by these dosimetry solutions. Limitations and challenges in clinical implementation of EPIDs for dosimetric purposes are discussed and acceptance and rejection criteria are outlined. Potential causes of and evaluations of pre-treatment and transit dosimetry failures are discussed. Guidelines and recommendations developed in this report are based on the extensive published data on EPID QA along with the clinical experience of the TG-307 members.

conclusionTG-307 focused on the commercially available EPID-based dosimetric tools and provides guidance for medical physicists in the clinical implementation of EPID-based patient-specific pre-treatment and transit dosimetry QA solutions including intensity modulated radiation therapy (IMRT) and volumetric modulated arc therapy (VMAT) treatments.

Indexed as

RadiometryRadiotherapy, Intensity-ModulatedAlgorithmsCalibrationElectrical Equipment and SuppliesHumansPrecision MedicineQuality Assurance, Health CareResearch Reportelectronic portal imaging deviceEPIDEPID QAIMRT/VMAT QApatient-specific EPID QA

Identifiers

PMID37384416
PMCPMC11230298

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.