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Record W1995120127 · doi:10.1118/1.4740110

Poster - Thur Eve - 03: LDR to HDR: RADPOS applications in brachytherapy

2012· article· en· W1995120127 on OpenAlexaff
Amanda Cherpak, Joanna Cygler, Gustavo Kertzscher, C. E, George Perry

Bibliographic record

VenueMedical Physics · 2012
Typearticle
Languageen
FieldEngineering
TopicCalibration and Measurement Techniques
Canadian institutionsCarleton UniversityOttawa Hospital
Fundersnot available
KeywordsBrachytherapyMedical physicsMedical imagingNuclear medicineMedicineRadiation therapyRadiology

Abstract

fetched live from OpenAlex

The RADPOS in vivo dosimetry system combines an electromagnetic positioning sensor and either one or five MOSFET dosimeters. The feasibility of using the system for quality control has been explored for a range of radiotherapy treatment techniques including most recently transperineal interstitial permanent prostate brachytherapy and high dose rate (HDR) treatments. Dose and position information was collected by a RADPOS array detector inside a Foley catheter within patients' urethra during permanent seed implantation. Ten patients were studied, and average displacement during implantation was Δr = (1.4-5.1) mm, with movements up to 9.7 mm due to the removal of the transrectal ultrasound probe. Maximum integral dose in the prostatic urethra ranged from 110-195 Gy, and it was found that the dose can change up to 63 cGy (62.0%) depending on whether the rectal probe is in place. For HDR, a RADPOS detector was first calibrated with an Ir-192 source. A treatment was then simulated using a total of 50 dwell positions in 5 catheters in an acrylic phantom. Dwell positions ranged from 1 to 10 cm away from the RADPOS detector and dose was measured for each source position. An average calibration coefficient of 0.74±0.11 cGy/mV was calculated for the detector and the average absolute difference between measured values and expected dose was 0.7±5.4 cGy (5±20%). The demonstrated accuracy of RADPOS dose measurements along with its ability to simultaneously measure displacement makes it a powerful tool for brachytherapy treatments, where high dose gradients can present unique in vivo dosimetry challenges.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.735
Threshold uncertainty score0.317

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.021
GPT teacher head0.268
Teacher spread0.248 · 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 teacher head, not a consensus.

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

Citations1
Published2012
Admission routes1
Has abstractyes

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