Rapid palliative radiotherapy: comparing IG-IMRT with more conventional approaches
Bibliographic record
Abstract
Abstract Purpose: To assess the efficiency of an integrated imaging, planning, and treatment delivery system to provide image-guided intensity-modulated radiotherapy (IG-IMRT) for patients requiring palliative radiotherapy (PRT). Methods: Between December 2006 and May 2008, 28 patients requiring urgent PRT were selected to undergo single-session megavoltage computed tomography (MV-CT) simulation, IMRT treatment planning, position verification and delivery of the first faction of radiotherapy on a helical Tomotherapy ® unit. The time required to complete each step was recorded and compared to our standard approach of using either fluoroscopic or CT-based simulation, simplified treatment planning and delivery on a megavoltage unit. Results: Twenty-eight patients were treated with our integrated IG-IMRT protocol. The median age was 72 years, with 61% men and 39% women. The indications for PRT were: painful bone and soft tissue metastasis (75%); bleeding lesions (14%); and other reasons (11%). The areas treated included the following: hip and/or pelvis (42%); spine (36%); and other areas (21%). The most commonly used dose prescription was 20 Gy in five fractions. Average times for the integrated IG-IMRT processes were as follows: image acquisition, 15 minutes; target delineation, 16 minutes; IMRT treatment planning, 9 minutes; treatment position verification, 10 minutes; and treatment delivery, 12 minutes. The average total time was 62 minutes compared to 66 minutes and 81 minutes for fluoroscopic and CT-simulation-based approaches, respectively. The IMRT dose distributions were also superior to simpler plans. Conclusions: PRT with an integrated IG-IMRT approach is efficient and convenient for patients, and has potential for future applications such as single-fraction radiotherapy.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".