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Record W2621128913 · doi:10.1016/s0167-8140(15)32857-7

OC-0551: Deformable dose reconstruction of liver SBRT to investigate margin reduction with dose-probability PTV

2013· article· en· W2621128913 on OpenAlexaff
Michael Velec, L. Dawson, Kyle Brock

Bibliographic record

VenueRadiotherapy and Oncology · 2013
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Radiotherapy Techniques
Canadian institutionsPrincess Margaret Cancer Centre
Fundersnot available
KeywordsMargin (machine learning)Reduction (mathematics)MedicineNuclear medicineMathematicsComputer scienceMachine learningGeometry

Abstract

fetched live from OpenAlex

Purpose/Objective: SBRT at the mean respiratory position coupled with a dose-probability PTV spares more normal tissue than the internal target volume (ITV) method.For liver cancer, a potential challenge with PTV reduction is the poor tumor contrast on respiratory correlated (4D) cone-beam CT (CBCT).Deformable image registration resolved the mean position on 4D CBCT and accumulated dose in order to investigate PTV reduction on both the planned and delivered liver SBRT doses.Materials and Methods: 21 tumors in 13 patients planned on exhale 4D CT for 27-49.8Gy/6 fractions with an ITV-based PTV (CT exh ), and treated in free-breathing with CBCT liver guidance, were retrospectively evaluated.Re-planning was done on the midventilation CT (CT mid ) using individualized dose-allocation (iso-NTCP ≤5%) and dose-probability margins accounting for: residual population inter-fraction tumor errors after liver guidance, intra-fraction motion, deformable registration accuracy, and patient-specific 4D CT tumor motion.The delivered dose was accumulated using biomechanical deformable registration of each 4D CBCT to model breathing changes, deformation and setup errors.This was done for the clinical CT exh plan, and for the CT mid plan after aligning the mean liver position between 4D CBCT and CT mid .Results: Relative to CT exh plans with ITV, PTVs on CT mid were smaller by a mean±SD of 35±13%, enabling a dose escalation to the PTV 95% volume of 5.0±4.7 Gy (maximum 19.5 Gy).The delivered minimum tumor doses (0.5cc) for the CT mid plans were 4.2±3.7 Gy (maximum 14.8Gy) higher than the doses delivered for the clinical CT exh plans.For the CT mid plans, only 1 patient (8%) had a decrease more than 0.5 Gy in the delivered minimum tumor dose, which was 4.8 Gy less than the dose planned to the PTV 95% volume on CT mid .This patient had 8 mm larger breathing amplitude on 4D CBCT versus 4D CT, and liver deformation causing a residual 4 mm systematic tumor error relative to the mean liver position on 4D CBCT.For the normal gastrointestinal tissues, the delivered maximum dose (0.5cc) for the CT exh plan exceeded the planning constraint by 1.7 Gy (5.4%) in one only patient's esophagus due to the effect of breathing motion.However, for the CT mid plans no delivered normal tissue doses exceeded the planning constraints by more than 0.2 Gy despite the dose-escalation.Conclusions: Liver SBRT planning and delivery at the mean respiratory liver with dose-probability margins enables a mean escalation of 5 Gy/6 fractions to the minimum tumor dose, potentially improving local control.Despite margin reduction, more than 90% of patients received the planned tumor dose without over irradiating the adjacent dose-limiting tissues.

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)0.001
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0080.001

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 head0.013
GPT teacher head0.262
Teacher spread0.249 · 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 designSimulation or modeling
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".

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Citations0
Published2013
Admission routes1
Has abstractno

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