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Record W3213020083 · doi:10.1002/acm2.13415

Adaptive radiation therapy strategies in the treatment of prostate cancer patients using hypofractionated VMAT

2021· article· en· W3213020083 on OpenAlexaff
Pawel Siciarz, Boyd McCurdy, Nikesh Hanumanthappa, Eric Van Uytven

Bibliographic record

VenueJournal of Applied Clinical Medical Physics · 2021
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Radiotherapy Techniques
Canadian institutionsUniversity of ManitobaCancerCare Manitoba
Fundersnot available
KeywordsContouringMedicineRadiation treatment planningNuclear medicineRadiation therapyProstate cancerRectumProstateCone beam computed tomographyImage-guided radiation therapyTomotherapyMedical physicsRadiologyCancerComputed tomographySurgeryComputer scienceInternal medicine

Abstract

fetched live from OpenAlex

Abstract Purpose To perform a comprehensive evaluation of eight adaptive radiation therapy strategies in the treatment of prostate cancer patients who underwent hypofractionated volumetric modulated arc therapy (VMAT) treatment. Material and methods The retrospective study included 20 prostate cancer patients treated with 40 Gy total dose over five fractions (8 Gy/fraction) using VMAT. Daily cone beam computed tomography images were acquired before the delivery of every fraction and then, with the application of deformable image registration used for the estimation of daily dose, contouring and plan re‐optimization. Dosimetric benefits of the various ART strategies were quantified by the comparison of dose and dose‐volume metrics derived from treatment planning objectives for original treatment plan and adapted plans with the consideration of target volumes (PTV and CTV) as well as critical structures (bladder, rectum, left, and right femoral heads). Results Percentage difference (ΔD) between planning objectives and delivered dose in the D 99% > 4000cGy (CTV) metric was −3.9% for the non‐ART plan and 2.1% to 4.1% for ART plans. For D 99% > 3800cGy and D max < 4280cGy (PTV), ΔD was −11.2% and −6.5% for the non‐ART plan as well as −3.9% to −1.6% and −0.2% to 1.8% for ART plans, respectively. For D 15% < 3200 cGy and D 20% < 2800 cGy (bladder), ΔD was −62.4% and −68.8% for the non‐ART plan as well as −60.0% to −57.4% and −67.0% to −64.0% for ART plans. For D 15% < 3200 cGy and D 20% < 2800 cGy (rectum), ΔD was −11.4% and −8.15% for non‐ART plan as well as −14.9% to −9.0% and −11.8% to −5.1% for ART plans. Conclusions Daily on‐line adaptation approaches were the most advantageous, although strategies adapting every other fraction were also impactful while reducing relative workload as well. Offline treatment adaptations were shown to be less beneficial due to increased dose delivered to bladder and rectum compared toother ART strategies.

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)0.000
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 score0.945
Threshold uncertainty score0.313

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.041
GPT teacher head0.389
Teacher spread0.348 · 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

Citations4
Published2021
Admission routes1
Has abstractyes

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