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Record W3015183842 · doi:10.1002/mp.14163

Dose‐rate considerations for the INTRABEAM electronic brachytherapy system: Report from the American Association of Physicists in Medicine task group no. 292

2020· article· en· W3015183842 on OpenAlexaff
Wesley S. Culberson, Stephen Davis, Grace Gwe‐Ya Kim, Jessica Lowenstein, Zoubir Ouhib, Marija Popović, Timothy J. Waldron, Habib Safigholi, Samantha J. Simiele, Mark J. Rivard

Bibliographic record

VenueMedical Physics · 2020
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Radiotherapy Techniques
Canadian institutionsCarleton UniversityMcGill University Health Centre
Fundersnot available
KeywordsDosimetryTask groupMedical physicistMedical physicsBrachytherapyNuclear medicineDose rateIonization chamberProtocol (science)MedicinePhysicsRadiation therapyEngineeringIonizationSurgery

Abstract

fetched live from OpenAlex

The purpose of this report is to provide detailed guidance on the dosimetry of the INTRABEAM® (Carl Zeiss Medical AG, Jena, Germany) electronic brachytherapy (eBT) system as it stands at the present time. This report has been developed by the members of American Association of Physicists in Medicine (AAPM) Task Group 292 and endorsed by the AAPM. Members of AAPM Task Group 292 on Electronic-Brachytherapy Dosimetry have reviewed pertinent publications and user manuals regarding the INTRABEAM system dosimetry and manufacturer-supplied dose calculation protocols. Formal written correspondence with Zeiss has also provided further clarification. Dose-rate calculations for the INTRABEAM system are highly dependent on choice of dosimetry protocol. Even with careful protocol selection, large uncertainties remain due to the incomplete characterization of the ionization chambers used for verification with respect to their energy dependence as well as manufacturing variations. There are two distinct sets of dose-rate data provided by Zeiss for the INTRABEAM system. One dataset (Calibration V4.0) is representative of the physical dose surrounding the source and the other dataset (TARGIT) has been adjusted to be consistent with a clinical trial named TARGIT (TARGeted Intraoperative RadioTherapy). The adjusted TARGIT doses are quite dissimilar to the physical doses, with differences ranging from 14% to 30% at the surface of a spherical applicator, depending on its diameter, and up to a factor of two at closer distances with the smaller needle applicators. In addition, ion chamber selection and associated manufacturing tolerances contribute to significant additional uncertainties. With these substantial differences in dose rates and their associated uncertainties, it is important for users to be aware of how each value is calculated and whether it is appropriate to be used for the intended treatment. If users intend to deliver doses that are the same as they were in 1998 at the onset of the TARGIT trial, then the TARGIT dose-rate tables should be used. The Calibration V4.0 dose rates may be more appropriate to use for applications other than TARGIT trial treatments, since they more closely represent the physical doses being delivered. Users should also be aware of the substantial uncertainties associated with the provided dose rates, which are due to beam hardening, chamber geometry, and selection of the point-of-measurement for a given ionization chamber. This report serves to describe the details and implications of the manufacturer-recommended dosimetry formalism for users of the INTRABEAM system.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.033
metaresearch head score (Gemma)0.023
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.033
Threshold uncertainty score0.175

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0330.023
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0030.004
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0040.002
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0040.004

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.012
GPT teacher head0.288
Teacher spread0.276 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreMethods

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations17
Published2020
Admission routes1
Has abstractyes

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