A multi‐institutional feasibility lead‐in trial of lymphatic mapping with <scp>SPECT</scp>–<scp>CT</scp> for evaluating contralateral disease in lateralized oropharynx cancer using 99m‐technetium sulfur colloid
Bibliographic record
Abstract
BACKGROUND: Lymphatic mapping with SPECT-CT has been demonstrated to accurately define lymphatic drainage patterns in oropharyngeal cancer but there has yet to be a study demonstrating its feasibility across multiple institutions. METHODS: Twelve adult patients with lateralized oropharyngeal carcinoma (T1-T3) who were planned for definitive or adjuvant radiotherapy without contralateral nodal disease underwent injection of 99-m technetium sulfur colloid followed by static planar lymphoscintigraphy to verify tracer migration, and SPECT-CT acquired at 30 ± 15 min (optional) and 3 h (±1 h) (mandatory time-point). RESULTS: All 12 patients completed the study with 7/12 patients having the injections performed under local anesthetic and 5 patients requiring general anesthetic. There were no tracer migration failures and there were no serious adverse events or complications encountered. Four out of 12 patients (33%) showed contralateral drainage patterns. CONCLUSIONS: Lymphatic mapping with SPECT-CT of lateralized oropharyngeal squamous cell carcinoma can be performed safely across multiple institutions.
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| 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".