Dual-Energy CT Characteristics of Parathyroid Adenomas on 25-and 55-Second 4D-CT Acquisitions
Bibliographic record
Abstract
OBJECTIVE: The objective of this study was to compare the dual-energy computed tomography (CT) characteristics of parathyroid adenomas (PAs), thyroid tissue, and lymph nodes (LNs) and assess whether the spectral information can improve distinction of these tissues. METHODS: Dual-energy CT scans from 20 patients with pathologically proven PAs were retrospectively evaluated, identifying 19 eligible PAs and region of interest analysis used for spectral characterization. RESULTS: There was a significant difference in multiple spectral parameters between PAs, LNs, and the thyroid gland (P < 0.05-0.0001). The greatest difference in spectral characteristics of PAs compared with that of LNs was on the 25-second acquisition, whereas the 55-second acquisition was better for distinguishing PAs from the thyroid gland. CONCLUSIONS: Four-dimensional CT acquired in dual-energy CT mode has the potential to further enhance diagnostic accuracy for PA identification on individual phases of the perfusion study.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 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) | 0.002 | 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 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".