Large-Volume Fat Grafting to the Breast With External Expansion Assist
Bibliographic record
Abstract
BACKGROUND: Large-volume autologous fat transfer (AFT) to the breast with external expansion has emerged as an alternative to alloplastic augmentation or reconstruction in appropriate patients. OBJECTIVES: Report the authors' technique for this procedure and experience with 49 consecutive patients of a single surgeon's practice from 2013 to 2021. METHODS: The authors performed a retrospective analysis of consecutive patients undergoing fat grafting to the breast with preexpansion. Patients were included if they had a clinical problem amenable to correction with large-volume fat injection and adequate donor sites, and were willing to undergo preexpansion. Data was collected through chart review and deidentified. Demographics, diagnosis, radiation status, volume grafted, complications, and adjunct procedures were recorded. RESULTS: Forty-nine patients underwent external expansion with AFT by a single surgeon. Twenty-three patients (47%) had hypoplastic indications, including tuberous breast deformity (n = 9) and Poland syndrome (n = 1). Seventeen patients (35%) had indications for secondary breast revision of previously placed implants. Nine patients (18%) utilized the procedure for primary oncologic breast reconstruction. A total of 71 procedures were performed, with an average of 1.45 procedures per patient. The average volume of fat grafted per breast was 372 mL for hypoplasia, 240 mL for secondary breast revision, and 429 mL for oncologic reconstruction. Concurrent procedures included implant exchange, implant removal, mastopexy, and breast reduction. Follow-up ranged from 1 to 84 (average = 20) months. CONCLUSIONS: The authors' experience shows promising results with external expansion and large-volume fat grafting to the breast.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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 teacher head, 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".