Volumetric changes of the anterolateral thigh free flap following adjuvant radiotherapy in total parotidectomy reconstruction
Bibliographic record
Abstract
OBJECTIVES/HYPOTHESIS: The aim of this study was to prospectively evaluate volume change in anterolateral thigh free flaps pre- and postradiotherapy and to compare computed tomography (CT) volumetric analysis with intraoperative water displacement calculation. STUDY DESIGN: Matched pair cohort study. METHODS: Thirteen patients with advanced carcinoma of the parotid gland underwent anterolateral thigh free flap reconstruction following total parotidectomy resections and neck dissection. Before the initiation of external beam radiation, routine CT planning scans were done on all patients. A minimum of 6 months after surgery, a CT scan of the head and neck was carried out, and a detailed volumetric assessment was performed. RESULTS: The mean preradiotherapy flap volume was 94.3 mL, and the postradiotherapy volume was 84.8 mL. The mean volume reduction in all 13 patients was 8.12%. CONCLUSIONS: In this prospective study we observed an 8% volume loss in anterolateral thigh free flaps 6 months postradiotherapy. This loss of volume should be taken into account when reconstructing large defects of the face and lateral skull base. Intraoperative water displacement measurement is a useful adjunctive tool for shaping free tissue transfers that are to be used for volume replacement and soft-tissue fill-in.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".