Can Axial-Based Nodal Size Criteria Be Used in Other Imaging Planes to Accurately Determine “Enlarged” Head and Neck Lymph Nodes?
Bibliographic record
Abstract
Objective. We evaluate if axial-based lymph node size criteria can be applied to coronal and sagittal planes. Methods. Fifty pretreatment computed tomographic (CT) neck exams were evaluated in patients with head and neck squamous cell carcinoma (SCCa) and neck lymphadenopathy. Axial-based size criteria were applied to all 3 imaging planes, measured, and classified as "enlarged" if equal to or exceeding size criteria. Results. 222 lymph nodes were "enlarged" in one imaging plane; however, 53.2% (118/222) of these were "enlarged" in all 3 planes. Classification concordance between axial versus coronal/sagittal planes was poor (kappa = -0.09 and -0.07, resp., P < 0.05). The McNemar test showed systematic misclassification when comparing axial versus coronal (P < 0.001) and axial versus sagittal (P < 0.001) planes. Conclusion. Classification of "enlarged" lymph nodes differs between axial versus coronal/sagittal imaging planes when axial-based nodal size criteria are applied independently to all three imaging planes, and exclusively used without other morphologic nodal data.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 teacher head, 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".