Characterization of a Single Pixel Beta Detector for Guidance in Breast-Conserving Surgery
Bibliographic record
Abstract
Breast-conserving surgery (BCS) is a challenging surgical procedure due to the lack of intraoperative image guidance available to surgeons. One potential method of intra-operative guidance would be radio-guided surgery with adiopharmaceutical emitting beta particles. In this thesis, a single pixel beta sensitive detector was constructed and characterized for intra-operative guidance during BCS. The thickness of the scintillation element of the detector was optimized to obtain a superior beta to gamma detection ratio. A computer model of the detector response was derived from an empirically measured, two-dimensional (2D) detector response. An in silico study evaluated whether the novel single pixel beta detector could detect less than 1 mm² deposits of cancer at the cut edge of the surgically excised cancerous tissue, with a sensitivity and specificity of 95%. A thickness of 0.5 mm for a CaF₂(Eu) scintillator was found to be optimal for a beta to gamma detection ratio. Additionally, according to an in silico study it is expected that with an acquisition time of 30 seconds, a tumour-to-background ratio of 5 or higher, and a normal breast tissue activity of 1.69 kBq/ml, detection of cancerous deposits of less than 1 mm² is possible. The result of this thesis demonstrate that radio-guided BCS, with a CaF₂(Eu) scintillation beta particle detector, can intra-operatively assess the tumour margin involvement, which would help surgeons in determining resection margins.
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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) | 0.001 | 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".