Complete frozen section margins for cancer of the tongue: part 1: animal experience.
Bibliographic record
Abstract
OBJECTIVE: Positive margins for squamous cell carcinoma of the oral tongue on final pathology are a poor prognostic factor associated with a higher likelihood of local recurrence. Obtaining margin status in a relatively short time by using complete frozen sections, such as Mohs margins for skin cancer, would lower the recurrence rate. The goal of this study was to compare, on pig tongue, the efficacy of different techniques used to obtain complete frozen sections on histologic glass slides of optimal quality. STUDY DESIGN: We compared the quality of frozen section glass slides on fresh pig tongues. The partial glossectomy was executed with either a sharp instrument (scalpel and scissors), electrocautery in the cutting mode, or electrocautery at the coagulation mode. For each of the three methods, we also compared the frozen section, obtained on the line of resection and for a thickness of 1 to 1.3 mm, using either the cryostat or isopentane for the freezing phase. The percentage and quality of epithelium and muscle present on histologic glass slides were assessed by a pathologist independently. RESULTS: Complete frozen margins of high quality were obtained in a relatively short time for all techniques (28-38 minutes). Sharp dissection showed better results: a shorter processing time for the specimens and better quality for the histologic glass slides. Using cryostat or isopentane for the freezing phase did not show any significant difference. CONCLUSION AND SIGNIFICANCE: Complete frozen margins (Mohs margins) of high quality are feasible. Histologic glass slides of very good quality are obtained when using a sharp dissection technique. For the freezing period, both isopentane and cryostat offer very good results. This approach is appropriate on animals and needs further study in clinical situations. The human experience will be presented in the next article which is: Complete frozen section margins (with measurable 1 or 5 mm thick free margin) for cancer of the oral tongue (Clinical experience Part 2 [CSO2008]).
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".