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Record W4221042756 · doi:10.1111/jon.12988

Angiography suite cone‐beam CT perfusion for selection of thrombectomy patients: A pilot study

2022· article· en· W4221042756 on OpenAlexaboutno aff
Santiago Ortega‐Gutiérrez, Darko Quispe‐Orozco, Sebastian Schäfer, Mudassir Farooqui, Cynthia Zevallos, Sudeepta Dandapat, Alan Mendez‐Ruiz, Beverly Aagaard‐Kienitz, Nils Petersen, Colin P. Derdeyn

Bibliographic record

VenueJournal of Neuroimaging · 2022
Typearticle
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsnot available
FundersNational Institute of Neurological Disorders and Stroke
KeywordsMedicineIntraclass correlationInterquartile rangeNuclear medicineAngiographyPerfusion scanningPerfusionRadiologyStroke (engine)Cerebral blood flowProspective cohort studyOcclusionCardiologySurgery

Abstract

fetched live from OpenAlex

BACKGROUND AND PURPOSE: The availability of cone-beam CT perfusion (CBCTP) in angiography suites may improve large-vessel occlusion (LVO) triage and reduce reperfusion times for patients presenting during extended time window. We aim to evaluate the perfusion maps correlation and agreement between multidetector CT perfusion (MDCTP) and CBCTP when obtained sequentially in patients undergoing endovascular therapy. METHODS: This is a prospective, pilot, single-arm interventional cohort study of consecutive patients with anterior circulation LVO. All patients underwent MDCTP and CBCTP prior to endovascular therapy, generating cerebral blood flow (CBF), cerebral blood volume (CBV), mean transit time (MTT), and time-to-maximum/time to peak contrast concentration maps. We compared the two imaging modalities using three different methods: (1) six regions of interest (ROIs) placed in the anterior circulation territory; (2) ROIs placed in all 10 Alberta Stroke Program Early CT Score regions; and (3) ROI drawn around the entire ischemic area. ROI ratios (unaffected/affected area) were compared for all sequences in each method. We used the intraclass correlation coefficient to calculate the correlation between the studies. Bland-Altman plots were also created to measure the degree of agreement. Finally, a sensitivity analysis was done comparing both modalities in patients with low infarct growth rate. RESULTS: Fourteen patients were included (median age 81 years [74-87], 50% males, median National Institutes of Health Stroke Scale 19 [14-22]). Median time between studies was 42 minutes (interquartile range 29-61). Independently of the method used, we found moderate to excellent correlation in CBF, CBV, and MTT between modalities. CBF correlation further improved in patients with low infarct growth. CONCLUSION: These results demonstrate promising accuracy of CBCTP in evaluating ischemic tissue in patients presenting with LVO ischemic stroke.

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.024
GPT teacher head0.281
Teacher spread0.257 · 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 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

Citations13
Published2022
Admission routes1
Has abstractyes

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