A Review of Objective Measurement of Flap Volume in Reconstructive Surgery
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: The utility and efficacy of 3-dimensional representation have been proven in bony reconstruction; however, its role in soft-tissue reconstruction remains limited. There is currently no reliable gold standard to objectively measure flap volume. This systematic review aims to summarize the available techniques used to objectively measure flap volume in reconstructive surgery. METHODS: A systematic literature search was performed to identify all relevant articles describing objective techniques to quantify flap volume. The search included published articles in 3 electronic databases-Ovid MEDLINE, EMBASE, and PubMed. RESULTS: A total of 16 studies were included. Flap volume was calculated using the following techniques: magnetic resonance imaging, computed tomography, 3-dimensional imaging and modeling, material templates, ultrasound, and weighing scales. Techniques and results of the included studies are summarized. CONCLUSIONS: This systematic review provides a summary of various published techniques for objective pre- or intraoperative quantification of flap volume in reconstructive surgery. The preliminary results from this review are promising, and we believe that 3-dimensional representation and objective quantification is the future of reconstructive flap surgery. More studies are needed to study the clinical relevancy and impact of the various imaging modalities reviewed and to develop automated volumetric measurement technology with improved accuracy, efficacy, and reproducibility.
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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 | 0.007 | 0.013 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.004 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 it