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Record W4385363620 · doi:10.1016/j.ijrobp.2023.07.020

Consensus Delineation Guidelines for Pelvic Lymph Node Radiation Therapy of Prostate Cancer: On Behalf of the Francophone Group of Urological Radiation Therapy (GFRU)

2023· article· en· W4385363620 on OpenAlexaff
O. De Hertogh, Guillaume Le Bihan, Thomas Zilli, Samuel Palumbo, M. Jolicoeur, G. Créhange, T. Derashodian, Guilhem Roubaud, Carl Salembier, S. Supiot, O. Chapet, Vérane Achard, Paul Sargos

Bibliographic record

VenueInternational Journal of Radiation Oncology*Biology*Physics · 2023
Typearticle
Languageen
FieldMedicine
TopicProstate Cancer Diagnosis and Treatment
Canadian institutionsMcGill University Health CentreCentre intégré de santé et de services sociaux de Chaudière-AppalachesCentre Intégré de Santé et de Services Sociaux des LaurentidesHôpital Charles-Le Moyne
FundersCilagJanssen PharmaceuticalsSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungMerck KGaASanofiAccurayAstellas PharmaAstellas Pharma USNational Science Foundation
KeywordsMedicineContouringRadiation therapyProstate cancerLymph nodeMedical physicsNuclear medicineRadiologyCancerComputer scienceInternal medicine

Abstract

fetched live from OpenAlex

PURPOSE: Clinical target volume (CTV) delineation for pelvic lymph nodes in prostate cancer is currently based on 3 consensus guidelines with some inherent discrepancies. To improve the reproducibility in nodal delineation, the Francophone Group of Urological Radiotherapy (Groupe Francophone de Radiothérapie Urologique [GFRU]) worked toward proposing an easily applicable, reproducible, and practice-validated contouring guideline for pelvic nodal CTV. METHODS AND MATERIALS: The nodal CTV data sets of a high-risk node-negative prostate cancer clinical case contoured by 86 radiation oncologists participating in a GFRU contouring workshop were analyzed. CTV volumes were defined before and after a structured presentation of literature data on lymphatic drainage pathways and patterns of nodal involvement and relapse, illustrated using a reference contour (CRef) defined by 3 GFRU experts. The consistency between the participants' contours and CRef was assessed quantitively by means of the Simultaneous Truth and Performance Level Estimation (STAPLE) method, the Dice coefficient, and the Hausdorff distance and qualitatively using a count map. These results combined with the literature review were thoroughly discussed among GFRU experts to reach a consensus. RESULTS: From the 86 workshop participants, the volume of the STAPLE CTV was 591 cc compared with 502 cc for CRef. The Dice coefficient of the STAPLE CTV compared with the experts' CRef was 0.736 (±0.084) before and 0.823 (±0.070) after the workshop; the standard deviation decreased from 11.5% to 8.5% over the workshop. The Hausdorff distance of the STAPLE CTV compared with the CRef was 34.5 mm (±12.4) before the workshop and 21.8 mm (±9.3) after the workshop. Four areas of significant interobserver variability were identified, and a consensus was reached. CONCLUSIONS: Using a robust methodology, our cooperative group proposed an easily applicable, reproducible, and practice-validated guideline for the delineation of the pelvic CTV in prostate cancer, useful for implementation in daily practice and clinical trials.

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)0.061
metaresearch head score (Gemma)0.064
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.061
Threshold uncertainty score0.325

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0610.064
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0060.004
Science and technology studies0.0020.002
Scholarly communication0.0030.002
Open science0.0050.003
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0030.002

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 head0.053
GPT teacher head0.376
Teacher spread0.324 · 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 designNot applicable
Domainnot available
GenreMethods

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

Citations24
Published2023
Admission routes1
Has abstractyes

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