Post–Vacuum-Assisted Stereotactic Core Biopsy Clip Displacement: A Comparison between Commercially Available Clips and Surgical Clip
Bibliographic record
Abstract
PURPOSE: The placement of localization clips following percutaneous biopsy is a standard practice for a variety of situations. Subsequent clip displacement creates challenges for imaging surveillance and surgical planning, and may cause confusion amongst radiologists and between surgeons and radiologists. Many causes have been attributed for this phenomenon including the commonly accepted "accordion effect." Herein, we investigate the performance of a low cost surgical clip system against 4 commercially available clips. METHODS: We retrospectively reviewed 2112 patients who underwent stereotactic vacuum-assisted core biopsy followed by clip placement between January 2013 and June 2016. The primary performance parameter compared was displacement >10 mm following vacuum-assisted stereotactic core biopsy. Within the group of clips that had displaced, the magnitude of displacement was compared. RESULTS: There was a significant difference in displacement among the clip types (P < .0001) with significant pairwise comparisons between pediatric surgical clips and SecureMark (38% vs 28%; P = .001) and SenoMark (38% vs 27%; P = .0001) in the proportion displaced. The surgical clips showed a significant magnitude of displacement of approximately 25% greater average distance displaced. CONCLUSIONS: As a whole, the commercial clips performed better than the surgical clip after stereotactic vacuum-assisted core biopsy suggesting the surrounding outer component acts to anchor the central clip and minimizes clip displacement. The same should apply to tomosynthesis-guided biopsy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 |
| 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) | 0.001 | 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".