The Use of Stereotactic Excisional Biopsy in the Management of Invasive Breast Cancer
Bibliographic record
Abstract
Stereotactic breast biopsy techniques minimize the surgical trauma associated with conventional wire-guided open breast biopsy for non-palpable breast lesions (NPBLs). Advanced breast biopsy instrumentation (ABBI) allows for a 2-cm core of breast tissue to be excised under stereotactic guidance in an outpatient setting. We report our initial experience with ABBI. Hospital charts from 89 ABBI procedures between 10/1996 and 07/2002 were retrospectively reviewed for patient characteristics, ABBI parameters, radiographic appearance, pathology, complications, and clinical follow-up. Data are presented as percentage/median (range). Median age was 59 years (range: 39-80 years), mammographic lesions were classified as calcifications 49% (44/89), soft tissue 39% (35/89), or mixed 11% (10/89). Median radiographic size was 7 mm (1-60 mm). Final pathology revealed ductal carcinoma in situ (DCIS) in 7% (6/89) and invasive cancer in 22% (20/89). Microscopically clear margins were obtained in 55% (11/20) of patients with invasive cancer. Of these, 82% (9/11) chose not to undergo further local surgical therapy. Eight patients remain disease free at 56 months (range: 41-95 months) follow-up. The ninth patient was deceased at 6 months from an unrelated cause. The overall complication rate was 3% (3/89). A definitive diagnosis was obtained in 100% of malignant and 87% of benign cases. Median waiting time was 19 days (range: 0-90 days). Our experience demonstrates that ABBI is an effective diagnostic tool for NPBLs. It is associated with minimal complications, and provides negative margins in over half of malignant cases. In selected patients with invasive cancer and negative margins, ABBI may obviate the need for further local surgical treatment. ABBI merits additional investigation as a therapeutic modality for early breast cancer.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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 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".