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Record W2064911381 · doi:10.1120/jacmp.v7i2.2210

PTV margin for dose‐escalated radiation therapy of prostate cancer with daily online realignment using internal fiducial markers: Monte Carlo approach and dose population histogram (DPH) analysis

2006· article· en· W2064911381 on OpenAlexaff
Miao Zhang, Vitali Moiseenko, Mitchell Liu

Bibliographic record

VenueJournal of Applied Clinical Medical Physics · 2006
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Radiotherapy Techniques
Canadian institutionsBC Cancer Agency
Fundersnot available
KeywordsFiducial markerNuclear medicineMedicineProstate cancerMargin (machine learning)Radiation therapyProstateRadiation treatment planningDose-volume histogramRectumIsocenterDosimetryRadiologyCancerSurgeryComputer scienceInternal medicine

Abstract

fetched live from OpenAlex

Using internal fiducial markers and electronic portal imaging (EPID) to realign patients has been shown to significantly reduce positioning uncertainties in prostate radiation treatment. This creates the possibility of decreasing the planning target volume (PTV) margin added on the clinical target volume (CTV), which in turn may allow for dose escalation. We compared the outcome of two plans: 70Gy/35fx, 10 mm PTV margin without patient realignment (Reference Plan) vs. 78Gy/39fx, 5 mm PTV margin with patient realignment (Escalated Plan). Four-field-oblique (gantry angles 35 degrees, 90 degrees, 270 degrees, 176 degrees, 325 degrees) beam arrangement was used. Monte Carlo code was used to simulate the daily organ motion. Dose to each organ was calculated. Tumour control probability (TCP) and the effective dose to critical organ (Deff) were calculated using the biologically normalized dose-volume histograms. By comparing the biological factors, we found that the prescription dose can be escalated to 78Gy/39fx with a 5 mm PTV margin when using internal fiducial markers and EPID. Based on the available dose-response data for intermediate risk prostate patients, this will result in a 20% increase of local control and significantly reduced rectal complications provided that less serial dose-volume behaviour of rectum is proven.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.776
Threshold uncertainty score0.673

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.346
Teacher spread0.325 · 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 designOther design
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

Citations11
Published2006
Admission routes1
Has abstractyes

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