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Record W2150154609 · doi:10.1259/bjr/16416346

Normalized data for the estimation of fetal radiation dose from radiotherapy of the breast

2006· article· en· W2150154609 on OpenAlexaff
B Bradley, Andre Fleck, Ernest Osei

Bibliographic record

VenueBritish Journal of Radiology · 2006
Typearticle
Languageen
FieldMedicine
TopicCancer Risks and Factors
Canadian institutionsRegional Municipality of WaterlooUniversity of Waterloo
Fundersnot available
KeywordsMedicineEstimationRadiation therapyRadiation doseOncologyNuclear medicineRadiology

Abstract

fetched live from OpenAlex

There can be several reasons why a pregnant patient may receive a radiological examination. It could have been a planned exposure, or the exposure might have resulted from an emergency when a thorough evaluation of pregnancy was impractical. Sometimes the pregnancy was unsuspected at the time of the examination and, with younger women being diagnosed with breast cancer, the likelihood of this will increase in radiotherapy departments. Whatever the reason, when presented with a pregnant patient who has received a radiological examination involving ionizing radiation, the dose to the fetus should be assessed based on the patient's treatment plan. However, a major source of uncertainty in the estimation of fetal absorbed dose is the influence of fetal size and position as these change with gestational age. Consequently, dose to the fetus is related to gestational age. Various studies of fetal dose during pregnancy have appeared in the literature. Whilst these papers contain many useful data for estimating fetal dose, they usually contain limited data regarding the depth and size of the fetus within the maternal uterus. We have investigated doses to the fetus from radiation therapy of the breast of a pregnant patient using an anthropomorphic phantom. Normalized data for estimating fetal doses that takes into account the fetal size (gestational age: 8-20 weeks post-conception) and depth within the maternal abdomen (4-16 cm) for different treatment techniques have been provided. The data indicate that fetal dose is dependent on both depth within the maternal abdomen and gestational age, and hence these factors should always be considered when estimating fetal dose. The data show that fetal dose can be underestimated up to about 10% or overestimated up to about 30% if the dose to the uterus is assumed instead of the actual fetal dose. It can also be underestimated up to about 23% or overestimated up to about 12% if a mean depth of 9 cm is assumed, instead of using the actual depth of the fetus within the maternal abdomen. Multi-segments sMLC technique showed consistently lower fetal doses compared with all the wedged plans employed.

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)0.003
metaresearch head score (Gemma)0.013
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 score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.013
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.015
GPT teacher head0.286
Teacher spread0.271 · 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

Citations15
Published2006
Admission routes1
Has abstractyes

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