Construction and Characterization of a Novel Single Pixel Beta Detector for Intraoperative Guidance in Breast-Conserving Surgery
Bibliographic record
Abstract
Breast-conserving surgery is imprecise requiring re-excision in up to 40% of cases. One potential method of improving breast-conserving surgery accuracy is to use a beta particle detector to evaluate the surface of the excised tissue for any cancerous deposits, intraoperatively. Patients could be injected with a radiopharmaceutical that emits beta particles and preferentially accumulates within cancer cells. Cancer cells found on the surface of the excised tissue indicate that the surgery is incomplete. The purpose of this paper is to develop and analyze a novel single pixel beta sensitive detector. The detector is made up of a calcium fluoride europium doped [CaF <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> (Eu)] scintillation crystal, which is coupled to a silicon photomultiplier. A computational model of the detector response was derived from an empirically generated, 2-D, detector sensitivity map. This study determined that a CaF <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> (Eu) scintillator of 0.5-mm thickness provided superior beta to gamma detection ratio. According to the detector response, it is expected that with an acquisition time of 30 s, the tumor-to-background ratio of 5 or higher, and a normal breast tissue activity of 1.69 kBq/ml, less than 1 mm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> tumor detection is achievable. The result of this paper indicates that the radio-guided surgery with a CaF <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> (Eu) scintillation detector could be feasible to intraoperatively assess tumor margin involvement.
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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) | 0.000 | 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) | 0.000 | 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".