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Record W1969169127 · doi:10.4103/0971-6203.26689

Intra-operative dosimetry of trans-rectal ultrasound guided <sup>125</sup>I prostate implants using C-arm fluoroscopic images

2006· article· en· W1969169127 on OpenAlexaff
PaulB Ravindran, C. Lewis, Jacob Van Dyk, David D’Souza

Bibliographic record

VenueJournal of Medical Physics · 2006
Typearticle
Languageen
FieldMedicine
TopicProstate Cancer Diagnosis and Treatment
Canadian institutionsLondon Health Sciences CentreWestern University
Fundersnot available
KeywordsDosimetryMedicineNuclear medicineFluoroscopyUltrasoundProstateRadiologyInternal medicine

Abstract

fetched live from OpenAlex

Permanent implantation of radioactive seeds is a viable and effective therapeutic option widely used today for early-stage prostate cancer. The implant technique has improved considerably during the recent years due to the use of image guidance; however, real-time dose distributions would allow potential cold spots to be assessed and additional seeds added. In this study, we investigate the use of a conventional C-arm fluoroscopy unit for image acquisition and evaluation of dose distribution immediately after the implant. The phantom study indicates that it is possible to obtain seed positions within ±2 mm. A pilot study carried out with three patients indicated that it is possible to obtain seed positions and calculate the dose distribution with C-arm fluoroscopy and about 95% of the seeds were reconstructed within ±2 mm. The results could be further improved with better digital imaging.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.019
GPT teacher head0.323
Teacher spread0.304 · 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 designObservational
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

Citations4
Published2006
Admission routes1
Has abstractyes

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