Reduced Intravenous Contrast Dose Portal Venous Phase Photon-Counting Computed Tomography Compared With Conventional Energy-Integrating Detector Portal Venous Phase Computed Tomography
Bibliographic record
Abstract
OBJECTIVE: The aim of this study was to compare portal venous phase photon-counting CT (PCCT) using 20 cc less than weight-based contrast dosing with energy-integrating detector CT (EID-CT) using weight-based dosing by quantitative and qualitative analysis. METHODS: Fifty adult patients who underwent a reduced intravenous contrast dose portal venous phase PCCT from May 1, 2023, to August 10, 2023, and a prior portal-venous EID-CT with weight-based contrast dosing were retrospectively identified. Hounsfield units (HU) and noise (SD of HU) were obtained from region-of-interest measurements on 70-keV PCCT and EID-CT in 4 hepatic segments, the main and right portal vein, and both paraspinal muscles. Signal-to-noise and contrast-to-noise ratios were computed. Three abdominal radiologists qualitatively assessed overall image quality, hepatic enhancement, and confidence for metastasis identification on 5-point Likert scales. Readers also recorded the presence/absence of hepatic metastases. Quantitative variables were compared with paired t tests, and multiple comparisons were accounted for with a Bonferroni-adjusted α level of .0016. Ordinal logistic regression was used to evaluate qualitative assessments. Interreader agreement for hepatic metastases was calculated using Fleiss' κ. RESULTS: Fifty patients (32 women; mean [SD] age, 64 [13] years) were included. There was no significant difference in hepatic HU, portal vein HU, noise, and signal-to-noise or contrast-to-noise ratio between reduced contrast dose portal venous phase PCCT versus EID-CT (all P s > 0.0016). Image quality, degree of hepatic enhancement, and confidence for metastasis identification were not different for reduced dose PCCT 70-keV images and EID-CT ( P = 0.06-0.69). κ Value for metastasis identification was 0.86 (95% confidence interval, 0.70-1.00) with PCCT and 0.78 (95% confidence interval, 0.59-0.98) with EID-CT. CONCLUSION: Reduced intravenous contrast portal venous phase PCCT 70-keV images had similar attenuation and image quality as EID-CT with weight-based dosing. Metastases were identified with near-perfect agreement in reduced dose PCCT 70-keV images.
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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 | 0.002 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 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".