SU‐G‐JeP4‐13: Continuous Intra‐Fractional Monitoring of the Prostate Using Dynamic KV Collimation and Tube Current Modulation
Bibliographic record
Abstract
Purpose: The focus of this work is to improve the available kV image quality for continuous intra‐fraction monitoring of the prostate. This is investigated using a novel blade collimation system enabling modulated volume‐of‐interest (VOI) imaging of prostate fiducial markers. Methods: A four‐blade dynamic kV collimator was used to track a VOI during gantry rotation. Planar image quality was investigated as a function of collimator dimension, while maintaining the same dose to isocenter, for a 22.2 cm diameter cylindrical water phantom with a 9 mm diameter bone insert. A sample prostate anatomy was defined in the planning system, including three fiducial markers within the CTV. The VOI margin around each marker was set to be 2σ of the population covariance matrix characterizing prostate motion. DRRs were used to calculate the kV attenuation for each VOI as a function of angle. The optimal marker and tube current were determined using kV attenuation. Monte Carlo simulations were used to calculate the imaging dose to the phantom and MV scatter dose to the imaging panel. Results: Preliminary measurements show an increase in CNR by a factor of 1.3 with the VOI method, when decreasing from an 6×6 to 2×2 cm2 field. Attenuation calculations show a change in kV fluence at the detector by a factor of 21.6 with fiducial optimization; resultant tube current modulation increases maximum dose by a factor of 1.4 compared to no modulation. MV scatter contribution to the kV detector changes by approximately a factor of two over a complete gantry rotation. Conclusion: The dynamic collimation system allows single fiducial marker tracking at a very low dose, with reduction of scatter and improvement of image quality, compared to imaging the entire prostate. The approach is compatible with tube current modulation, which enables consistent image quality throughout the range of gantry rotation. This project was funded by Varian Medical Systems.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".