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Record W2999135055 · doi:10.3174/ajnr.a6376

Displaying Multiphase CT Angiography Using a Time-Variant Color Map: Practical Considerations and Potential Applications in Patients with Acute Stroke

2020· review· en· W2999135055 on OpenAlexaff
Johanna M. Ospel, Ondřej Volný, Wu Qiu, Mohamed Najm, Nima Kashani, Mayank Goyal, Bijoy K. Menon

Bibliographic record

VenueAmerican Journal of Neuroradiology · 2020
Typereview
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsFoothills Medical CentreUniversity of Calgary
FundersStryker
KeywordsMedicineRadiologyOcclusionComputed tomography angiographyAcute strokeAngiographyStroke (engine)PerfusionPerfusion scanningCardiologyInternal medicine

Abstract

fetched live from OpenAlex

Various imaging protocols exist for the identification of vessel occlusion and assessment of collateral flow in acute stroke. CT perfusion is particularly popular because the color maps are a striking visual indicator of pathology. Multiphase CTA has similar diagnostic and prognostic ability but requires more expertise to interpret. This article presents a new multiphase CTA display format that incorporates vascular information from all phases of the multiphase CTA series in a single time-variant color map, thereby facilitating multiphase CTA interpretation, particularly for less experienced readers. Exemplary cases of multiphase CTA from this new display format are compared with conventional multiphase CTA, CT perfusion, and follow-up imaging to demonstrate how time-variant multiphase CTA color maps facilitate assessment of collateral flow, detection of distal and multiple intracranial occlusions, differentiation of pseudo-occlusion from real occlusion, and assessment of flow relevance of stenoses, ante- and retrograde flow patterns, and clot permeability.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.018
GPT teacher head0.314
Teacher spread0.297 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations47
Published2020
Admission routes1
Has abstractyes

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Same venueAmerican Journal of NeuroradiologySame topicAcute Ischemic Stroke ManagementFrench-language works237,207