Low-Energy Virtual Monochromatic Dual-Energy Computed Tomography Images for the Evaluation of Head and Neck Squamous Cell Carcinoma: A Study of Tumor Visibility Compared With Single-Energy Computed Tomography and User Acceptance
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE: Dual-energy computed tomography (CT) 40-keV virtual monochromatic images (VMIs) have been reported to improve visualization of head and neck squamous cell carcinoma, but a direct comparison to single-energy CT (SECT) is lacking, and there is debate regarding subjective user preference. We compared 40-keV VMIs with SECT and performed a subjective evaluation of their utility and acceptability for clinical use. METHODS: A total of 60 dual-energy CT and 60 SECT scans from 2 different institutions were evaluated. Tumor conspicuity was evaluated objectively using absolute and relative attenuation and subjectively by 3 head and neck specialists and 3 general radiologists. RESULTS: Tumors had significantly higher absolute and relative attenuation on 40-keV VMIs (P < 0.0001). Subjectively, the 40-keV VMIs improved visualization, with substantial (κ, 0.61-0.80) to almost perfect (κ, 0.81-1) interrater agreements. CONCLUSIONS: The 40-keV VMIs improve tumor visibility objectively and subjectively both by head and neck specialists and general radiologists.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it