SU‐E‐T‐424: Clinical Validation of a GammaBeam Tomotherapy System Using the Octavius Pre‐Treatment QA Device
Bibliographic record
Abstract
Purpose: Verify and validate the clinical viability of a GammaBeam Tomotherapy system Methods: A full commissioning of the GammaBeam Tomotherapy unit is performed. This novel radiotherapy system integrates the Co‐60 Equinox machine (Best Theratronics, Canada), MIMiC MLC, AutoCrane and nomoSTATM software (Best Nomos, PA). PDDs, output factors and profiles was acquired and entered into the Corvus GammaBeam treatment planning system. Patient treatment plans for H&N, Pelvis, Brain and Brain SRS were generated. Corresponding pre‐treatment QA plans were calculated and delivered on the Octavius QA phantom (PTW, NY). As acceptance criteria, we applied a gamma analysis with a DTA ranging from 3 mm to 5 mm and a dose difference from 1% to 4% (of local dose). Plan quality is also analyzed in terms of target coverage, organ at risk sparing, skin dose, hot spots, etc., in comparison to serial tomotherapy plans generated on the same CT sets using linac based photon beams. Results: for the H&N plan, acceptance criteria were set to 4%, 5 mm DTA to meet the minimum requirement of more than 90% of points passing. For the Pelvis, 91.6% of points pass the 3%, 3 mm DTA. For Brain and Brain SRS, a gamma analysis based on 2%, 2 mm DTA resulted in 98% and 90.9% of points passing. In the most complex case of H&N, constraints were met with 10% hot spot (within the target) and a skin dose ∼50% of the prescribed dose. Conclusions: investigation has demonstrated that the GammaBeam Tomotherapy system is clinically viable. At maximum source activity (∼15000 Ci), a 2 Gy fraction of the H&N plan took 20 minutes to deliver. Although this time is expected to slowly increase, due to source decay, to reach ∼30 minutes three years later, it remains comparable to linac based tomotherapy treatment times. Financial support for this work was obtained from Best Medical International.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
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 source (direct Gemma or distilled Codex), 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".