Evaluation of a Ferromagnetic Marker Technology for Intraoperative Localization of Nonpalpable Breast Lesions
Bibliographic record
Abstract
OBJECTIVE: The purpose of this study was to evaluate the magnetic occult lesion localization instrument (MOLLI) system that involves implantation of a small, ferromagnetic marker to guide surgical excision of nonpalpable breast lesions. Characterization of the system was undertaken as part of what is, to our knowledge, the first study to assess the MOLLI system. MATERIALS AND METHODS: The MOLLI system consists of a handheld probe that can detect the position and distance of an implanted magnetic marker. The system presents the surgeon with an accurate assessment of lesion location and depth measurement for precise 3D localization. The marker is implanted under ultrasound or mammographic guidance at any time before the surgical procedure and requires no special precautions. Experimental analysis focused on characterization of the following aspects of the MOLLI system: visualization of the marker under imaging, 3D detection of the magnetic marker, spatial resolution of the probe to detect markers placed in close proximity, and the effect of signal interference on system performance. RESULTS: The MOLLI system can reliably detect mean (± SD) marker depths up to 53 ± 8.56 mm from the probe. Bracketing large lesions or localizing multiple lesions can be accomplished by placing markers as close as 10 mm apart, at depths of up to 42 mm. The biologically inert MOLLI marker is readily visible under ultrasound and mammographic guidance, and it is differentiable from radiologic clips. The effect of surgical instruments on MOLLI functioning is minimal and does not impact system accuracy or reliability. CONCLUSION: The MOLLI system offers an accurate and efficient alternative lesion localization method for nonpalpable breast lesions.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".