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Record W2170970130 · doi:10.1017/s1460396909990355

Hippocampus avoidance with fan beam and volumetric arc radiotherapy for base of skull tumours

2010· article· en· W2170970130 on OpenAlexaff
Ericka Wiebe, Luca Cozzi, Slav Yartsev, Antonella Fogliata, Alessandro Clivio, Eugenio Vanetti, Giorgia Nicolini, Jeff Chen, Andrew Leung, Glenn Bauman

Bibliographic record

VenueJournal of Radiotherapy in Practice · 2010
Typearticle
Languageen
FieldMedicine
TopicGlioma Diagnosis and Treatment
Canadian institutionsLondon Health Sciences CentreWestern UniversityCancer Care Ontario
Fundersnot available
KeywordsTomotherapyArc (geometry)Margin (machine learning)Radiation therapyNuclear medicineMedicineRadiologyComputer scienceMathematics

Abstract

fetched live from OpenAlex

Abstract Radiosensitive neurogenic stem cells reside in the hippocampi, suggesting that avoidance of the hippocampi may be an important strategy to reduce potential radiation-related cognitive effects. Six patients treated for base of skull tumours were re-planned using co-planar helical fan beam arc therapy (tomotherapy) and co-planar and non-coplanar volumetric arc techniques (RapidArc). The hippocampi were contoured as avoidance structures with the specific goal of minimising the dose. Two gross target volume (GTV) to planning target volume (PTV) expansions (10 and 2 mm) were considered to evaluate the impact of margin selection on organ at risk (OAR) sparing. The dose prescription was 50 Gy to >95% of the PTV. Comparison of the hippocampus avoidance plans demonstrated the importance of non-coplanar delivery when the 10 mm margin was used. With the 2 mm margin, both co-planar and non-coplanar delivery provided similar degrees of sparing. A mean dose of 3–4 Gy and a V 6Gy <5% to the hippocampi was realised with the hippocampus sparing techniques. Our comparisons suggest interventions to minimise GTV to PTV margins will have a more profound influence on multiple OAR sparing than the choice of intensity modulated arc delivery technique.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.174
Threshold uncertainty score0.564

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
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 head0.009
GPT teacher head0.293
Teacher spread0.284 · 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 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

Citations1
Published2010
Admission routes1
Has abstractyes

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