Techniques for overcoming a missing clip during pre-operative needle localization for lumpectomy: case report
Bibliographic record
Abstract
Breast conservation therapy (BCT) has become the standard of care for treating low-stage breast lesions. The principle of this therapy is to conserve as much normal breast tissue as allowable while still achieving a proper oncologic resection. These breast-sparing dissections would be difficult if not impossible without any intra-operative guidance. For this reason a wire is typically placed near the lesion pre-operatively to serve in directing the surgeon. To accurately place a wire, a lesion must be identifiable on imaging. This creates a potential dilemma as candidates for breast-conserving therapy typically have low-stage lesions which can be illusive at times. Thus, fiduciary markers such as clips have become integral in the treatment of low-stage breast lesions as they can serve as a reference point for identifying non-palpable breast lesions. In fact, cases in which a clip serves as the only identifiable landmark for an occult breast lesion are not uncommon. While undoubtedly useful, the heavy reliance we place on these markers creates a potential for significant dilemma when they cannot be visualized. We present a case that demonstrates one of the potential pitfalls that can occur when relying on a fiduciary marker, specifically, the inability to perform pre-operative wire-guided localization (WGL) for lumpectomy due to a lack of clip visualization. We discuss the potential causes for lost markers such as clip migration as well as several techniques available for attempting a “blind” lumpectomy with particular focus on intra-operative fluoroscopy. By utilizing this technique we were able to successfully complete an unexpected blind lumpectomy without any sacrifice in regards to oncologic margins or cosmesis.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.010 | 0.008 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".