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Record W2755844843 · doi:10.1097/rli.0000000000000413

Unenhanced Dual-Energy Computed Tomography

2017· article· en· W2755844843 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueInvestigative Radiology · 2017
Typearticle
Languageen
FieldEngineering
TopicAdvanced X-ray and CT Imaging
Canadian institutionsBC Cancer Agency
Fundersnot available
KeywordsMedicineEmergency departmentRadiologyEdemaStroke (engine)Computed tomographyAcute strokeInfarctionTomographyPredictive valueCerebral edemaNuclear medicineSurgeryInternal medicineMyocardial infarction

Abstract

fetched live from OpenAlex

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.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.190
Threshold uncertainty score0.827

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.016
GPT teacher head0.234
Teacher spread0.219 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it