Evidence map›Paper›PMID 42816122›Full record

ArticleJournal of applied clinical medical physics2026

A technology-specific risk analysis of surface guided radiation therapy.

Victoria Bry, Angelia Tran, Tamara Egan, Eric Ford, Juergen Meyer

Abstract read
In one paragraph

Article in Journal of applied clinical medical physics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

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

5 authors.

Victoria BryDepartment of Radiation Oncology, Samuel Oschin Cancer Center, Cedars Sinai Medical Center, Los Angeles, California, USA.ORCID https://orcid.org/0000-0002-8284-7453
Angelia TranDepartment of Radiation Oncology, Fred Hutchinson Cancer Center, University of Washington, Seattle, Washington, USA.
Tamara EganDepartment of Radiation Oncology, Fred Hutchinson Cancer Center, University of Washington, Seattle, Washington, USA.
Eric FordDepartment of Radiation Oncology, Fred Hutchinson Cancer Center, University of Washington, Seattle, Washington, USA.
Juergen MeyerDepartment of Radiation Oncology, Fred Hutchinson Cancer Center, University of Washington, Seattle, Washington, USA.ORCID https://orcid.org/0000-0003-4350-2222

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSurface Guided Radiation Therapy (SGRT) has become an increasingly important tool that complements x-ray imaging to improve patient safety for setup, respiratory tracking, and motion monitoring. As SGRT is integrated into clinical workflows, its complexity can introduce potential risk of process-related errors. These risks may depend on workflow design, system integration, equipment configuration, and technology specific features. As SGRT continues to expand across a wider range of treatment sites and clinical applications, comprehensive evaluation of institutional workflows is recommended to support safe and effective implementation. PURPOSE: This study aimed to identify and evaluate safety risks associated with the clinical use of SGRT using Failure Mode and Effects Analysis (FMEA). Emphasis was placed on workflow processes, system integration, and equipment-specific characteristics within a clinical environment to inform risk mitigation strategies and support safe implementation.

methodsA multidisciplinary team performed an FMEA of SGRT related procedures and workflows. A process map was developed to define the scope of clinical applications, including tattoo free setup, free-breathing and deep-inspiration breath-hold (DIBH) breast treatments, prone patient positioning and real-time motion monitoring for stereotactic body radiation therapy (SBRT) patients across body sites. For each process step, team members identified potential failure modes associated with the clinical workflow and environment, including the integration of a C-RAD SGRT system with Elekta linear accelerators. Scoring was performed according to AAPM TG-100 guidelines, using severity (S), occurrence (O), and detectability (D) to calculate the Risk Priority Number (RPN). Failure modes were then ranked by RPN, and those with scores greater than or equal to 100 were selected for further analysis and development of mitigation strategies.

resultsThirty-eight failure modes were identified, with nine having RPN scores greater than or equal to 100 (S = 5-8, O = 2-5, and D = 5-9). High risk failure modes were most associated with the DIBH workflow, particularly respiratory trace acquisition, respiratory trace configuration, and x-ray image verification. Additional high risk failure modes were identified in treatment preparation and system quality assurance processes, including manual data import, template selection, calibration, and daily QA procedures. These risks were primarily associated with workflow-dependent processes involving user interaction and coordination between integrated clinical systems.

conclusionsThis FMEA identified workflow, system integration and equipment related vulnerabilities associated with SGRT implementation. The findings emphasize the importance of risk assessments tailored to specific clinical workflows and treatment environments and support the development of targeted mitigation strategies for safe clinical use.

Indexed as

Breast NeoplasmsHealthcare Failure Mode and Effect AnalysisRadiosurgeryRadiotherapy, Image-GuidedRadiotherapy Planning, Computer-AssistedHumansPatient PositioningPatient SafetyRadiotherapy DosageRadiotherapy, Intensity-ModulatedRisk AssessmentWorkflowFMEAsafety and qualitySGRTsurface imaging

Identifiers

PMID42816122
PMCPMC13626861

What OpenQuestion holds

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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.