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Record W2914040405 · doi:10.1148/radiol.2019181228

Automated Calculation of the Alberta Stroke Program Early CT Score: Feasibility and Reliability

2019· article· en· W2914040405 on OpenAlexaboutno aff
Christian Maegerlein, Johanna C. Fischer, Sebastian Mönch, Maria Berndt, Silke Wunderlich, Christian Seifert, Manuel Lehm, Tobias Boeckh‐Behrens, Claus Zimmer, Benjamin Friedrich

Bibliographic record

VenueRadiology · 2019
Typearticle
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineNeuroradiologistStroke (engine)OcclusionRetrospective cohort studyMiddle cerebral arteryRadiologyAcute strokeCohortSurgeryMagnetic resonance imagingInternal medicineIschemia

Abstract

fetched live from OpenAlex

Background The Alberta Stroke Program Early CT Score (ASPECTS) evaluation is a qualitative method to evaluate focal hypoattenuation at brain CT in early acute stroke. However, interobserver agreement is only moderate. Purpose To compare ASPECTS calculated by using an automatic software tool to neuroradiologist evaluation in the setting of acute stroke. Materials and Methods For this retrospective study, consensus ASPECTS were defined by two neuroradiologists based on baseline noncontrast CTs collected from January 2017 to December 2017 from patients with an occlusion in the middle cerebral artery and from an additional cohort of patients suspected of having stroke and no large vessel occlusion. Imaging data from both baseline and follow-up CT was evaluated for the consensus reading. After 6 weeks, the same two neuroradiologists again determined ASPECTS by using only the baseline CT. For comparison, ASPECTS was also calculated from baseline CT images by using a commercially available software (RAPID ASPECTS). Both methods were compared by using weighted κ statistics. Results CT scans from 100 patients with middle cerebral artery occlusion (44 women [mean age ± standard deviation, 75 years ± 14] and 56 men [mean age, 71 years ± 14]) and 52 patients suspected of having stroke and no large vessel occlusion (19 women [mean age, 69 years ± 18] and 33 men [68 years ± 15]) were evaluated. Neuroradiologists showed moderate agreement with the consensus score (κ = 0.57 and κ = 0.56). Software analysis showed substantial agreement (κ = 0.9) with the consensus score. Software analysis showed a substantial agreement (κ = 0.78) after greater than 1 hour between symptom onset and imaging, which increased to high agreement (κ = 0.92) in the time window greater than 4 hours. The neuroradiologist raters did not achieve comparable results to the software until the time interval of greater than 4 hours (κ = 0.83 and κ = 0.76). Conclusion In acute stroke of the middle cerebral artery, the Alberta Stroke Program Early CT score calculated with automated software had better agreement than that of human readers with a predefined consensus score. © RSNA, 2019 Online supplemental material is available for this article.

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 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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.262

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 studies0.0000.000
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 head0.013
GPT teacher head0.276
Teacher spread0.263 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations133
Published2019
Admission routes1
Has abstractyes

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