Development of an MRI/x-ray/ultrasound compatible marker for pre-operative breast tumour localization
Bibliographic record
Abstract
This paper describes an in vitro investigation into the composition, structure and development of an magnetic resonance imaging (MRI), ultrasound (US) and x-ray imaging compatible marker for breast tumour localization. The marker is composed of 0.4-0.6 mm glass and iron-containing aluminium microspheres suspended in a gelatin matrix. The final form of the marker is a cylindrical shape 7 mm long with 2.05 mm diameter to facilitate delivery through a 12 gauge biopsy needle. To get optimal reflectivity for the US contrast, the glass microsphere concentration was found to be 40% by weight. US contrast is independent of marker orientation and the cylindrical shape made its US signal appearance distinctive thus ensuring confident identification. To control the MRI contrast, iron content was varied to generate a clear and local susceptibility signal void to reflect the marker position. Optimal iron content was found to be 52 microg iron which produced a clear signal void in spoiled gradient recalled MR images. The appearance of the susceptibility artefact is determined by the marker's shape, orientation and echo time. The final marker produces a dark artefact in MRI while appears as a clear hyperintense structure with acoustic shadowing in US images. The x-ray image showed the marker as a radio-opaque structure. This in vitro study demonstrates that the marker forms an alternative to traditional wire localization currently used for breast surgical procedures and creates new opportunities for US guided surgical procedures.
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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 | 0.000 | 0.001 |
| 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 | 0.001 | 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 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".