Unenhanced Dual-Energy Computed Tomography
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
PURPOSE: The aim of this study was to determine whether dual-energy computed tomography (DECT) imaging is superior to conventional noncontrast computed tomography (CT) imaging for the detection of acute ischemic stroke. MATERIALS AND METHODS: This was a retrospective, single-center study of 40 patients who presented to the emergency department (ED) of a major, acute care, teaching center with signs and symptoms of acute stroke. Only those patients who presented to the ED within 4 hours of symptom onset were included in this study. All 40 patients received a noncontrast DECT of the head at the time of presentation. Each patient also received standard noncontrast CT of the head 24 hours after their initial presentation to the ED. "Brain edema" images were then reconstructed using 3-material decomposition with parameters adjusted to suppress gray/white matter contrast while preserving edema and increasing its conspicuity. The initial unenhanced, mixed images, brain edema, and 24-hour follow-up true noncontrast (TNC) images were reviewed and assigned Alberta Stroke Program Early CT scores. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated. RESULTS: Of the 40 patients, 28 (70%) were diagnosed with an acute infarction. Brain edema reconstructions were better able to predict end infarction volume, with Alberta Stroke Program Early CT scores similar to the 24-hour follow-up TNC CT (7.75 vs 7.7; P > 0.05), whereas the mixed images routinely underestimated the extent of infarction (8.975 vs 7.7; P < 0.001). Initial TNC images had a sensitivity, specificity, PPV, and NPV of 80% (95% confidence interval [CI], 51.9%-95.7%), 72.7% (95% CI, 39%-94%), 80% (95% CI, 51.9%-95.7%), and 72.73% (95% CI, 51.91%-95.67%), respectively. The DECT brain edema images provided a sensitivity, specificity, PPV, and NPV of 93.33% (95% CI, 68.05%-99.83%), 100% (95% CI, 71.51%-100%), 100% (95% CI, 76.84%-100%), and 91.67% (95% CI, 61.52%-99.79%), respectively. There was very good interrater reliability across all 3 imaging techniques. CONCLUSION: Brain edema reconstructions are able to more accurately detect edema and end-infarct volume as compared with initial TNC images. This provides a better assessment of the degree and extent of infarction and may serve to better guide therapy in the future.
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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 | 0.000 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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