Contribution of Breast Density to the Volume of the Augmented Breast: A Preliminary Study
Bibliographic record
Abstract
BACKGROUND: Prediction of soft tissue contribution to the shape, volume and texture of the augmented breast proves to be an ever-challenging, uncontrollable variable. Similarly, the understanding of the contribution of breast density in breast augmentation has been elusive and, generally, not well studied. OBJECTIVE: With the aid of three-dimensional photographic analysis, the present preliminary study examined the contribution of differing breast densities to the overall volume of the augmented breast. METHODS: All patients undergoing primary augmentation over a six-month period were included in the study. To standardize technique and implant type, all patients received saline-filled moderate-profile implants, which were placed partially underneath the pectoralis muscle through a lower pole approach. Photographic analysis of the breast volume was completed preoperatively and, subsequently, at a minimum of six months postoperatively. Preoperatively, each breast was also assigned to one of four classes of increasing mammographic density, as judged by the mammographic radiologist (fatty, moderately dense, heterogeneously dense and extremely dense). Postoperative breast volumes were, subsequently, correlated to mammographic densities. RESULTS: Thirty-eight augmented breasts in 21 patients were examined. The average volume gain based on the implant size used was 92.7%. Heterogeneously dense breasts comprised 68% of the total breasts and showed an average volume gain of 100.67%, extremely dense breasts comprised 26% of the total breasts and showed an average volume gain of 97.3%, and moderately dense breasts comprised 5% of the total breasts with an average gain of 100.04%. There was no significant difference between the augmented breast volumes and the respective expected volumes (combined preaugmented breast volumes and implant volumes; P=0.3483). Additionally, no statistical difference was found between the density classes and the expected augmented volumes. CONCLUSION: No statistical difference was found between expected and actual augmented breast volumes among or between four different breast density classes. Thus, one would expect that the soft tissue compression or the response of the impression of the implant on the parenchyma, would not be statistically different among classes. Additionally, compressive atrophy, as seen with atrophy of the breasts over time, would be expected to be multifactorial and not uniquely independent to breast density. However, longitudinal analysis is needed to study the durability of breast shape relative to breast density.
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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 | 0.002 |
| 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".