TU‐FF‐A2‐02: Dual‐Fields Rotational Total Skin Electron Irradiation/therapy
Bibliographic record
Abstract
Purpose: We have developed a new technique for rotational total skin electron therapy (RTSET). The technique combines the rotational method of McGill University with the Stanford University angled dual‐fields method. We report dosimetry characteristics and in‐vivo dosimetry. Method and Materials: Patients stand on a rotational (0.9 rpm) platform at an extended SSD (332cm) with field‐size 133‐cm by 133‐cm. The gantry is angled 70° and 110° so that beam points above patient's head and below patient's feet, respectively, in order to minimize contaminant x‐ray dose. A “high‐dose‐rate” mode (600 MU/min) on a Varian‐21EX delivers a 6 MeV‐electron beam. Daily treatments require only about 0.5 h, one‐half of which is used for patient set‐up. Shields are used for eyes, nails, and toes. Dosimetry measurements include static dose‐rate at extended SSD, rotational dose‐rate for a rotating patient/phantom, and a power law correction for SSD variation. In‐vivo dose measurements are performed using XV‐films and MOSFET. Films strips are attached firmly on patient's skin to avoid any air gaps. Results: We obtained MU = Dose/(0.0751*0.39 *(332/SSD) 2.25 ). Therefore, a prescription dose of 125cGy at 325cm SSD required 4068 MU or 7.5 revolutions. The dose distribution along the vertical direction was measured by a parallel‐plate ionization chamber in a phantom. For a patient prescribed 116cGy daily, the average measured surface dose with film was 110cGy, within 5% of prescribed dose. In‐vivo MOSFET on a patient prescribed 125cGy daily, measured doses were distributed from 99% to 102% from the prescribed dose of 125cGy. Conclusion: The dual‐field RTSET offers combined advantages of shorter beam‐on time, uniform dose distribution, larger treatment fields, and less x‐ray contamination than other techniques. Our in‐vivo measurements revealed that delivered dose matched prescribed dose to < 5% and dose uniformity was within 6% variation.
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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) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".