SU‐E‐J‐161: In Vivo Dose Measurement During IGRT with KV Cone Beam CT
Bibliographic record
Abstract
Purpose: The purpose of this study is to perform in vivo dose measurements during image guidance kV CBCT using MOSFET dosimeter. Methods: Dose measurements were performed on a Clinac 2100 C/D unit with the integrated kV CBCT.for patient positioning. CBCT imaging of head and neck is usually performed with full cone beam and half gantry rotation and that of breast and pelvis with half cone beam and full gantry rotation. In this study we used mobile MOSFET dosimeters along with dose verification system supplied by the BEST Medicals Canada. The MOSFETs used in this study are of high sensitivity, i.e 9 mV/cGy for standard and 30 mV/cGy for high bias setting. The mobile MOSFETs were calibrated against parallel plate ion chamber, with air kerma calibration factor (Nk) traceable to the primary standard. Radiation dose measurements during kV CBCT were performed for patients undergoing IGRT treatments for head & Neck, breast and pelvis. The kV CBCT doses to ipsi‐lateral and contralateral eyes were measured by placing the MOSFET on the eye lid for 15 patients. Similarly doses to ipsi‐lateral and contra‐lateral breasts for kV CBCT of breast patients and on the surface of the pelvis for prostate patients were measured. Results: The maximum doses to the contra‐lateral and ipsi‐lateral eyes were 4.0 mGy and 5.7 mGy respectively with an average of 2.0 and 3.0 mGy. Breast dose measurements performed on five patients showed maximum dose of 11 mGy and 9.1 mGy to the ipsi‐lateral and contra‐lateral breasts with an average of 10.7 mGy and 6.6 mGy respectively. The average dose to the surface of the pelvis was 31 mGy. Conclusion: The dose measurements performed in this study closely agrees with those of published values. Dose reduction strategies should be employed to reduce dose during IGRT. Funded by the Board of Research in Nuclear Sciences, Department of Atomic Energy, Govt. of India
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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 | 0.000 | 0.001 |
| 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) | 0.001 | 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 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".