Dual-Layer Spectral CT Imaging of Upper Aerodigestive Tract Cancer: Analysis of Spectral Imaging Parameters and Impact on Tumor Staging
Bibliographic record
Abstract
<h3>BACKGROUND AND PURPOSE:</h3> Dual-layer spectral CT is a novel technology that utilized conventional single-tube CT acquisition with a dual-layer detector for the separation of high and low-energy photons to create spectral data for material decomposition. We evaluated the spectral parameters of iodine density and Z-effective values in primary head and neck squamous cell carcinoma and determined its impact on local tumor staging. <h3>MATERIALS AND METHODS:</h3> Twenty-one patients with primary head and neck squamous cell carcinoma and 15 healthy controls were retrospectively evaluated. Iodine density (milligram/milliliter) and Z-effective values were compared quantitatively between head and neck squamous cell carcinoma and normal neck mucosa. The receiver operating characteristic area under the curve determined the diagnostic performance of the spectral data for local staging. We compared conventional CT images without and with iodine density and Z-effective images to determine its impact on local tumor staging. <h3>RESULTS:</h3> Primary head and neck squamous cell carcinoma showed higher mean iodine density (2.01 [SD, 0.26] mg/mL, <i>P </i>< .001) and Z-effective values (8.21 [SD, 0.36], <i>P </i>< .001). A high interobserver correlation was demonstrated for ROI measurements for both the control group (iodine density, κ = 0.71, and Z-effective values, κ = 0.78) and head and neck squamous cell carcinoma (iodine density, κ = 0.84, and Z-effective values, κ = 0.75) group. The area under the curve for iodine density and Z-effective values was 0.98 and 0.93, respectively. Optimal thresholds were identified as 1.58 mg/mL (95% CI, 1.45–1.71 mg/mL; <i>P </i>< .001; sensitivity = 1.0; specificity = .0.93) for iodine density and 8.08 (95% CI, 7.96–8.19; <i>P </i>< .001; sensitivity = 0.86; specificity = 0.93) for Z-effective values. Conventional CT with the addition of dual-layer spectral data (iodine density and Z-effective values) improved the accuracy of local tumor staging in 3 of 21 patients (14%) with head and neck squamous cell carcinoma compared with the criterion standard surgical staging/histopathology. <h3>CONCLUSIONS:</h3> Dual-layer spectral iodine density and Z-effective values provided increased quantitative and qualitative differentiation between upper aerodigestive head and neck squamous cell carcinoma and normal mucosa. Increased tissue differentiation improved the local tumor staging accuracy.
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 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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".