Total body irradiation: A transition from a Co‐60 treatment unit to an IMRT lateral‐field extended‐SAD technique
Bibliographic record
Abstract
PURPOSE: The purpose of this work was to detail our center's experience in transitioning from a Co-60 treatment technique to an intensity modulated radiation therapy (IMRT) based lateral-field extended source-to-axis distance (e-SAD) technique for total body irradiation (TBI). MATERIALS AND METHODS: An existing beam model in RayStation v.10A was validated for the use of e-SAD TBI treatments. Data were acquired with an Elekta Synergy linear accelerator (LINAC) at an extended source-to-surface distance of 365 cm with an 18 MV beam. Beam model validation measurements included percentage depth dose (PDD), profile data, surface dose, build-up region and transmission measurements. End-to-end testing was carried out using an anthropomorphic phantom. Treatments were performed in a supine position in a whole-body Vac-Lok at an e-SAD of 400 cm with a beam spoiler 10 cm from the couch. Planning was achieved using IMRT, where multi-leaf collimators were used to modulate the beam and shield the organs at risk. Beam's eye view projection images were used for in-room patient positioning and in-vivo dosimetry was performed for every treatment. RESULTS: The percent difference between the measured and calculated PDD and profiles was less than 2% at all locations. Surface dose was 83.8% of the maximum dose with the beam spoiler at a 10 cm distance from the phantom. The largest percent difference between the treatment planning system (TPS) and measured data within the anthropomorphic phantom was approximately 2%. In-vivo dosimetry measurements yielded results within the 5% institutional threshold. CONCLUSION: In 2022, 17 patients were successfully treated using the new IMRT-based lateral-field e-SAD TBI technique. The resulting clinical plans respected the institutional standard. The commissioning process, as well as the treatment planning and delivery aspects were described in this work with the intention of supporting other clinics in implementing this treatment method.
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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 | 0.000 | 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 | 0.000 |
| 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".