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Record W4400737414 · doi:10.1002/hed.27871

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

2024· article· en· W4400737414 on OpenAlexaff
Leba M. Sarkis, Christopher M. K. L. Yao, Aaron Hendler, Ravi Mohan, Michael Au, Han Zhang, Antoine Eskander, Kevin Higgins, Danielle MacNeil, Sharon Tzelnick, David P. Goldstein, Ali Hosni, John R. de Almeida

Bibliographic record

VenueHead & Neck · 2024
Typearticle
Languageen
FieldMedicine
TopicHead and Neck Cancer Studies
Canadian institutionsWestern UniversityHealth Sciences CentreSunnybrook Health Science CentrePrincess Margaret Cancer CentreMcMaster UniversityUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsLymphatic systemMedicineTechnetium-99mNuclear medicineTechnetiumRadiologyPathologyScintigraphy

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.389
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.099
GPT teacher head0.391
Teacher spread0.291 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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