Evaluation of percutaneous vacuum assisted intact specimen breast biopsy device for ultrasound visualized breast lesions: Upstage rates and long term follow-up for high risk lesions and DCIS
Bibliographic record
Abstract
Objective Percutaneous core biopsy of ultrasound visualized breast lesions is standard for diagnosis. Large gauge vacuum-assisted core needles have improved accuracy; but a significant underestimation of malignancy remains. The Intact R device was assessed for upstaging and subsequent malignancy at the biopsy site. Methods 469 consecutive ultrasound visualized breast lesions, < 2.0 cm in size, BIRADS 4 or 5, biopsied with Intact R Breast Lesion Excision System, between July 2007 and August 2014, were reviewed. All non-concordant lesions (0.8%), DCIS (1.7%) and invasive cancers (9.8%) were surgically excised. Excision was recommended for all high risk lesions (13.0%). The upstage rate to DCIS or invasive cancer was determined. All patients were followed for a median of 66 months (24–96 months) with serial imaging and exams to determine the incidence of re-biopsy, or malignancy at the original biopsy site. Results 23 of 61 high risk lesions (37.5%) were not excised, but observed for a median of 66 months. None required re-biopsy. One atypical lesion was upstaged to DCIS on excision. No patient was diagnosed with malignancy at or near the original biopsy site during follow-up. Overall upstage rate was 1.2%. Conclusions Percutaneous biopsy of ultrasound visualized lesions was performed accurately using Intact R . Upstaging was much lower with Intact R than with large-gauge core needles. High risk lesions, diagnosed with Intact R , have a very low upstage rate at surgical excision. It may be possible to observe these lesions without surgery when they present as ultrasound findings and undergo Intact R biopsy.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".