A scintillation dosimeter with real‐time positional tracking information for in vivo dosimetry error detection in HDR brachytherapy
Bibliographic record
Abstract
Abstract Purpose To evaluate the performance of an electromagnetic (EM)‐tracked scintillation dosimeter in detecting source positional errors of IVD in HDR brachytherapy treatment. Materials and Methods Two different scintillator dosimeter prototypes were coupled to 5 degrees‐of‐freedom (DOF) EM sensors read by an Aurora V3 system. The scintillators used were a 0.3 × 0.4 × 0.4 mm 3 ZnSe:O and a BCF‐60 plastic scintillator of 0.5 mm diameter and 2.0 mm in length (Saint‐Gobain Crystals). The sensors were placed at the dosimeter's tip at 20.0 mm from the scintillator. The EM sampling rate was 40/s while the scintillator signal was sampled at 100 000/s using two photomultiplier tubes from Hamamatsu (series H10722) connected to a data acquisition board. A high‐pass filter and a low‐pass filter were used to separate the light signal into two different channels. All measurements were performed with an afterloader unit (Flexitron‐Elekta AB, Sweden) in full‐scattered (TG43) conditions. EM tracking was further used to provide distance/angle‐dependent energy correction for the ZnSe:O inorganic scintillator. For the error detection part, lateral shifts of 0.5 to 3 mm were induced by moving the source away from its planned position. Indexer length (longitudinal) errors between 0.5 to 10 mm were also introduced. The measured dose rate difference was converted to a shift distance, with and without using the positional information from the EM sensor. Results The inorganic scintillator had both a signal‐to‐noise‐ratio (SNR) and signal‐to‐background‐ratio (SBR) close to 70 times higher than those of the plastic scintillator. The mean absolute difference from the dose measurement to the dose calculated with TG‐43U1 was 1.5% ±0.7%. The mean absolute error for BCF‐60 detector was 1.7% when compared to TG‐43 calculations formalism. With the inorganic scintillator and EM tracking, a maximum area under the curve (AUC) gain of 24.0% was obtained for a 0.5‐mm lateral shift when using the EMT data with the ZnSe:O. Lower AUC gains were obtained for a 3‐mm lateral shifts with both scintillators. For the plastic scintillator, the highest gain from using EM tracking information occurred for a 0.5‐mm lateral shift at 20 mm from the source. The maximal gain (17.4%) for longitudinal errors was found at the smallest shifts (0.5 mm). Conclusions This work demonstrates that integrating EM tracking to in vivo scintillation dosimeters enables the detection of smaller shifts, by decreasing the dosimeter positioning uncertainty. It also serves to perform position‐dependent energy correction for the inorganic scintillator,providing better SNR and SBR, allowing detection of errors at greater distances from the source.
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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 | 0.001 | 0.000 |
| 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 | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".