Technical Note: Identification of an optimal electromagnetic sensor for <i>in vivo</i> electromagnetic‐tracked scintillation dosimeter for HDR brachytherapy
Bibliographic record
Abstract
Purpose Brachytherapy is a treatment modality which delivers large doses of radiation in a reduced number of visits. Since a small number of large dose‐per‐fraction is administered in high dose rate brachytherapy, ensuring the right dose is delivered is highly critical. In this work, a scintillation detector is coupled to an electromagnetic (EM) sensor (NDI, Waterloo, ON, Canada) having submillimeter positional accuracy for real‐time tracking of the dosimeter position. However, adding an EM sensor adds materials in the path to the scintillator and thus could potentially perturb the dose measurements. This study assesses four different sensors for a plastic scintillation detector–EM sensor coupled dosimeter. Methods To confirm the perturbation presence, different sensors were placed in front of the scintillator so the radiation does not arrive to it directly. Variation of the distance between the sensor and the scintillator was used to quantify the effect on the signal at and . To test the signal's angular dependence for each sensor, the signal measurement was taken from to with increment. Results The Aurora 5DOF‐610090 sensor showed an increased signal of almost 20% with increasing beam angle. Sensors Aurora 5DOF‐610099, Aurora 5DOF‐610157, and Aurora Micro 6DOF‐610059 showed no significant angle dependance. The Aurora Micro 6DOF‐610059 and Aurora 5DOF‐610157 sensors' cable signal revealed no extra signal attenuation. The latter gives a smaller overall attenuation. Therefore, the Aurora 5DOF‐610157 sensor is chosen to be part of the novel dosimeter construction. It has a jitter error (average standard deviation of each individual measurement) of ±0.06 mm and a reproducibility of ±0.008 mm. In the optimal operating range, the average positional uncertainty is less than 0.2 mm. Average angle errors are not higher than . Conclusion It is feasible to integrate an EM tracking sensor to a plastic scintillation dosimeter with minimal impact to the collected signal as well as sufficient positional accuracy to keep dose uncertainty below 5%.
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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".