Evidence map›Paper›PMID 39189817›Full record

ArticleJournal of applied clinical medical physics2024

Comprehensive clinical implementation, workflow, and FMEA of bespoke silicone bolus cast from 3D printed molds using open-source resources.

Dean Hobbis, Michael D Armstrong, Samir H Patel, Riley C Tegtmeier, Brady S Laughlin, Shadi Chitsazzadeh, Edward L Clouser, Jennifer L Smetanick, Justin Pettit, Justin D Gagneur and 3 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 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Trial
  2. Article
  3. 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

13 authors.

Dean HobbisDepartment of Radiation Oncology, Mayo Clinic Arizona, Phoenix, Arizona, USA.ORCID https://orcid.org/0000-0001-8932-2097
Michael D ArmstrongDepartment of Radiation Oncology, Mayo Clinic Arizona, Phoenix, Arizona, USA.
Samir H PatelDepartment of Radiation Oncology, Mayo Clinic Arizona, Phoenix, Arizona, USA.
Riley C TegtmeierDepartment of Radiation Oncology, Mayo Clinic Arizona, Phoenix, Arizona, USA.
Brady S LaughlinDepartment of Radiation Oncology, Mayo Clinic Arizona, Phoenix, Arizona, USA.
Shadi ChitsazzadehDepartment of Radiation Oncology, Mayo Clinic Arizona, Phoenix, Arizona, USA.
Edward L ClouserDepartment of Radiation Oncology, Mayo Clinic Arizona, Phoenix, Arizona, USA.
Jennifer L SmetanickDepartment of Radiation Oncology, Mayo Clinic Arizona, Phoenix, Arizona, USA.
Justin PettitDepartment of Radiation Oncology, Mayo Clinic Arizona, Phoenix, Arizona, USA.
Justin D GagneurDepartment of Radiation Oncology, Mayo Clinic Arizona, Phoenix, Arizona, USA.
Joshua B StokerDepartment of Radiation Oncology, Mayo Clinic Arizona, Phoenix, Arizona, USA.
Yi RongDepartment of Radiation Oncology, Mayo Clinic Arizona, Phoenix, Arizona, USA.ORCID https://orcid.org/0000-0002-2620-1893
Courtney R BuckeyDepartment of Radiation Oncology, Mayo Clinic Arizona, Phoenix, Arizona, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundBolus materials have been used for decades in radiotherapy. Most frequently, these materials are utilized to bring dose closer to the skin surface to cover superficial targets optimally. While cavity filling, such as nasal cavities, is desirable, traditional commercial bolus is lacking, requiring other solutions. Recently, investigators have worked on utilizing 3D printing technology, including commercially available solutions, which can overcome some challenges with traditional bolus. PURPOSE: To utilize failure modes and effects analysis (FMEA) to successfully implement a comprehensive 3D printed bolus solution to replace commercial bolus in our clinic using a series of open-source (or free) software products.

methods3D printed molds for bespoke bolus were created by exporting the DICOM structures of the bolus designed in the treatment planning system and manipulated to create a multipart mold for 3D printing. A silicone (Ecoflex 00-30) mixture is poured into the mold and cured to form the bolus. Molds for sheet bolus of five thicknesses were also created. A comprehensive FMEA was performed to guide workflow adjustments and QA steps.

resultsThe process map identified 39 and 30 distinct steps for the bespoke and flat sheet bolus workflows, respectively. The corresponding FMEA highlighted 119 and 86 failure modes, with 69 shared between the processes. Misunderstanding of plan intent was a potential cause for most of the highest-scoring failure modes, indicating that physics and dosimetry involvement early in the process is paramount.

conclusionFMEA informed the design and implementation of QA steps to guarantee a safe and high-quality comprehensive implementation of silicone bolus from 3D printed molds. This approach allows for greater adaptability not afforded by traditional bolus, as well as potential dissemination to other clinics due to the open-source nature of the workflow.

Indexed as

Printing, Three-DimensionalRadiotherapy DosageRadiotherapy Planning, Computer-AssistedSiliconesSoftwareWorkflowHumansRadiotherapy, Intensity-ModulatedSiliconeselectronsexternal beamprocess mapquality assurancerisk analysis

Identifiers

PMID39189817
PMCPMC11539970

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.