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Record W2466662696 · doi:10.1118/1.4956163

SU‐F‐T‐28: Evaluation of BEBIG HDR Co‐60 After‐Loading System for Skin Cancer Treatment Using Conical Surface Applicator

2016· article· en· W2466662696 on OpenAlexaff
Habib Safigholi, Ali S. Meigooni, Dan Han, A Soliman, W. Y. Song

Bibliographic record

VenueMedical Physics · 2016
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Radiotherapy Techniques
Canadian institutionsHealth Sciences CentreUniversity of TorontoSunnybrook Health Science Centre
Fundersnot available
KeywordsConical surfaceMaterials scienceBrachytherapyDosimetryOpticsMonte Carlo methodNuclear medicineBiomedical engineeringRadiation therapyPhysicsMathematicsMedicine

Abstract

fetched live from OpenAlex

Purpose: To evaluate the possibility of utilizing the BEBIG HDR 60Co remote after‐loading system for malignant skin surface treatment using Monte Carlo (MC) simulation technique. Methods: First TG‐43 parameters of BEBIG‐Co‐60 and Nucletron Ir‐192‐mHDR‐V2 brachytherapy sources were simulated using MCNP6 code to benchmark the sources against the literature. Second a conical tungsten‐alloy with 3‐cm diameter of Planning‐Target‐Volume (PTV) at surface for use with a single stepping HDR source is designed. The HDR source is modeled parallel to treatment plane at the center of the conical applicator with a source surface distance (SSD) of 1.5‐cm and a removable plastic end‐cap with a 1‐mm thickness. Third, MC calculated dose distributions from HDR Co‐60 for conical surface applicator were compared with the simulated data using HDR Ir‐192 source. The initial calculations were made with the same conical surface applicator (standard‐applicator) dimensions as the ones used with the Ir‐192 system. Fourth, the applicator wall‐thickness for the Co‐60 system was increased (doubled) to diminish leakage dose to levels received when using the Ir‐192 system. With this geometry, percentage depth dose (PDD), and relative 2D‐dose profiles in transverse/coronal planes were normalized at 3‐mm prescription‐depth evaluated along the central axis. Results: PDD for Ir‐192 and Co‐60 were similar with standard and thick‐walled applicator. 2D‐relative dose distribution of Co‐60, inside the standard‐conical‐applicator, generated higher penumbra (7.6%). For thick‐walled applicator, it created smaller penumbra (<4%) compared to Ir‐192 source in the standard‐conicalapplicator. Dose leakage outside of thick‐walled applicator with Co‐60 source was approximately equal (≤3%) with standard applicator using Ir‐192 source. Conclusion: Skin cancer treatment with equal quality can be performed with Co‐60 source and thick‐walled conical applicators instead of Ir‐192 with standard applicators. These conical surface applicator must be used with a protective plastic end‐cap to eliminate electron contamination and over‐dosage of the skin.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.036
GPT teacher head0.370
Teacher spread0.334 · 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 designBench or experimental
Domainnot available
GenreEmpirical

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

Citations0
Published2016
Admission routes1
Has abstractyes

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