Evidence map›Paper›PMID 38742819›Full record

ArticleJournal of applied clinical medical physics2024

Optimization of treatment workflow for 0.35T MR-Linac system.

Mojtaba Behzadipour, Jatinder Palta, Tianjun Ma, Lulin Yuan, Siyong Kim, Suzanne Kirby, Laurel Torkelson, James Baker, Tammy Koenig, Mateb Al Khalifa and 5 more

Abstract read
In one paragraph

Article in Journal of applied clinical medical physics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

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

  1. Pooled it
  2. Optimization of treatment workflow for 0.35T MR-Linac system.Journal of applied clinical medical physics · 2024
    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

15 authors.

Mojtaba BehzadipourDepartment of Radiation Oncology, Virginia Commonwealth University, Richmond, Virginia, USA.ORCID https://orcid.org/0000-0002-3855-5373
Jatinder PaltaDepartment of Radiation Oncology, Virginia Commonwealth University, Richmond, Virginia, USA.
Tianjun MaDepartment of Radiation Oncology, Virginia Commonwealth University, Richmond, Virginia, USA.
Lulin YuanDepartment of Radiation Oncology, Virginia Commonwealth University, Richmond, Virginia, USA.
Siyong KimDepartment of Radiation Oncology, Virginia Commonwealth University, Richmond, Virginia, USA.ORCID https://orcid.org/0000-0002-9173-7141
Suzanne KirbyDepartment of Radiation Oncology, Virginia Commonwealth University, Richmond, Virginia, USA.
Laurel TorkelsonDepartment of Radiation Oncology, Virginia Commonwealth University, Richmond, Virginia, USA.
James BakerDepartment of Radiation Oncology, Virginia Commonwealth University, Richmond, Virginia, USA.
Tammy KoenigDepartment of Radiation Oncology, Virginia Commonwealth University, Richmond, Virginia, USA.
Mateb Al KhalifaDepartment of Radiation Oncology, Virginia Commonwealth University, Richmond, Virginia, USA.
Robert HawrankoDepartment of Radiation Oncology, Virginia Commonwealth University, Richmond, Virginia, USA.
Dylan RichesonDepartment of Radiation Oncology, Virginia Commonwealth University, Richmond, Virginia, USA.
Emma FieldsDepartment of Radiation Oncology, Virginia Commonwealth University, Richmond, Virginia, USA.ORCID https://orcid.org/0000-0002-2871-078X
Elisabeth WeissDepartment of Radiation Oncology, Virginia Commonwealth University, Richmond, Virginia, USA.
William Y SongDepartment of Radiation Oncology, Virginia Commonwealth University, Richmond, Virginia, USA.ORCID https://orcid.org/0009-0003-3196-2368

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeThis study presents a novel and comprehensive framework for evaluating magnetic resonance guided radiotherapy (MRgRT) workflow by integrating the Failure Modes and Effects Analysis (FMEA) approach with Time-Driven Activity-Based Costing (TDABC). We assess the workflow for safety, quality, and economic implications, providing a holistic understanding of the MRgRT implementation. The aim is to offer valuable insights to healthcare practitioners and administrators, facilitating informed decision-making regarding the 0.35T MRIdian MR-Linac system's clinical workflow.

methodsFor FMEA, a multidisciplinary team followed the TG-100 methodology to assess the MRgRT workflow's potential failure modes. Following the mitigation of primary failure modes and workflow optimization, a treatment process was established for TDABC analysis. The TDABC was applied to both MRgRT and computed tomography guided RT (CTgRT) for typical five-fraction stereotactic body RT (SBRT) treatments, assessing total workflow and costs associated between the two treatment workflows.

resultsA total of 279 failure modes were identified, with 31 categorized as high-risk, 55 as medium-risk, and the rest as low-risk. The top 20% risk priority numbers (RPN) were determined for each radiation oncology care team member. Total MRgRT and CTgRT costs were assessed. Implementing technological advancements, such as real-time multi leaf collimator (MLC) tracking with volumetric modulated arc therapy (VMAT), auto-segmentation, and increasing the Linac dose rate, led to significant cost savings for MRgRT.

conclusionIn this study, we integrated FMEA with TDABC to comprehensively evaluate the workflow and the associated costs of MRgRT compared to conventional CTgRT for five-fraction SBRT treatments. FMEA analysis identified critical failure modes, offering insights to enhance patient safety. TDABC analysis revealed that while MRgRT provides unique advantages, it may involve higher costs. Our findings underscore the importance of exploring cost-effective strategies and key technological advancements to ensure the widespread adoption and financial sustainability of MRgRT in clinical practice.

Indexed as

Magnetic Resonance ImagingParticle AcceleratorsRadiosurgeryRadiotherapy DosageRadiotherapy, Image-GuidedRadiotherapy, Intensity-ModulatedRadiotherapy Planning, Computer-AssistedWorkflowHealthcare Failure Mode and Effect AnalysisHumansNeoplasmsOrgans at RiskTomography, X-Ray ComputedCTgRTFMEAMRgRTMR‐LinacTDABC

Identifiers

PMID38742819
PMCPMC11302807

What OpenQuestion holds

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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.