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Record W4394770467 · doi:10.1016/j.ijrobp.2024.03.005

Diagnostic CT-Enabled Planning (DART): Results of a Randomized Trial in Palliative Radiation Therapy

2024· article· en· W4394770467 on OpenAlexafffund
Melissa O’Neil, Joanna Laba, Timothy K. Nguyen, Michael Lock, Christopher D. Goodman, Elizabeth Huynh, Jonatan Snir, Vikki Munro, Jenna Alce, Lidia Schrijver, Sylvia Lemay, Tara K. MacDonald, Andrew Warner, David A. Palma

Bibliographic record

VenueInternational Journal of Radiation Oncology*Biology*Physics · 2024
Typearticle
Languageen
FieldMedicine
TopicManagement of metastatic bone disease
Canadian institutionsWestern UniversityLondon Health Sciences Centre
FundersOntario Institute for Cancer Research
KeywordsMedicineInterquartile rangeRandomized controlled trialClinical endpointRadiation treatment planningRadiation therapyRadiologyNuclear medicineSurgery

Abstract

fetched live from OpenAlex

PurposeUsing diagnostic computed tomography (dCT) scans instead of CT simulation (CTsim) scans can increase departmental efficiency and reduce patient burden. The goal of the DART trial was to assess the efficacy and acceptability of dCT-based planning workflows with a focus on patient experiences, plan deliverability and adequacy of target coverage, and workflows.Methods and MaterialsPatients undergoing same-day CTsim and treatment for palliative radiation therapy to thoracic, abdominopelvic, or proximal limb targets with a recent dCT (within 28 days) in a reproducible position were eligible. After stratifying by target type (bone or soft tissue vs. visceral), participants were randomized (1:2 ratio) between CTsim-based (CTsim arm) vs. dCT-based planning (dCT arm). The primary endpoint was time in center (TIC), defined as total time spent in the cancer center on first day of treatment, from first radiation department appointment to first fraction completion. Secondary endpoints included plan deliverability, adequacy of target coverage, and stakeholder acceptability.ResultsThirty-three patients (42 treatment sites) were enrolled between June 2022 and April 2023. The median age was 72 (interquartile range [IQR]: 67-78), 73% were male, and the most common primary cancers were lung (33%), prostate (24%), and breast (12%). The most common dose and fractionations were 8 Gy in 1 and 20 Gy in 5 fractions (50% and 43% of plans, respectively). TIC was 4.7 ± 1.1 hours (mean ± SD) in the CTsim arm vs. 0.41 ± 0.14 hours in the dCT arm (P < .001). All dCT plans were deliverable. All plans in both arms were rated as “acceptable” (80% CTsim; 81% dCT) or “acceptable with minor deviation” (20% CTsim; 19% dCT). Patient perception of acceptability was similar in both arms with the exception of time burden, which was rated as “acceptable” by 50% in the CTsim arm vs. 90% in the dCT arm (P = .025).ConclusiondCT-based radiation planning substantially reduced TIC without detriment in plan deliverability or quality and had a tangible impact on patient experience with reduced patient-reported time burden. Using diagnostic computed tomography (dCT) scans instead of CT simulation (CTsim) scans can increase departmental efficiency and reduce patient burden. The goal of the DART trial was to assess the efficacy and acceptability of dCT-based planning workflows with a focus on patient experiences, plan deliverability and adequacy of target coverage, and workflows. Patients undergoing same-day CTsim and treatment for palliative radiation therapy to thoracic, abdominopelvic, or proximal limb targets with a recent dCT (within 28 days) in a reproducible position were eligible. After stratifying by target type (bone or soft tissue vs. visceral), participants were randomized (1:2 ratio) between CTsim-based (CTsim arm) vs. dCT-based planning (dCT arm). The primary endpoint was time in center (TIC), defined as total time spent in the cancer center on first day of treatment, from first radiation department appointment to first fraction completion. Secondary endpoints included plan deliverability, adequacy of target coverage, and stakeholder acceptability. Thirty-three patients (42 treatment sites) were enrolled between June 2022 and April 2023. The median age was 72 (interquartile range [IQR]: 67-78), 73% were male, and the most common primary cancers were lung (33%), prostate (24%), and breast (12%). The most common dose and fractionations were 8 Gy in 1 and 20 Gy in 5 fractions (50% and 43% of plans, respectively). TIC was 4.7 ± 1.1 hours (mean ± SD) in the CTsim arm vs. 0.41 ± 0.14 hours in the dCT arm (P < .001). All dCT plans were deliverable. All plans in both arms were rated as “acceptable” (80% CTsim; 81% dCT) or “acceptable with minor deviation” (20% CTsim; 19% dCT). Patient perception of acceptability was similar in both arms with the exception of time burden, which was rated as “acceptable” by 50% in the CTsim arm vs. 90% in the dCT arm (P = .025). dCT-based radiation planning substantially reduced TIC without detriment in plan deliverability or quality and had a tangible impact on patient experience with reduced patient-reported time burden.

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)0.003
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.204
Threshold uncertainty score0.730

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.006
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 head0.034
GPT teacher head0.375
Teacher spread0.342 · 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 designRandomized trial
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

Citations23
Published2024
Admission routes2
Has abstractyes

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