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Record W4205170083 · doi:10.1017/cjn.2021.342

P.062 Does the intensity of brain parenchymal contrast staining on post-recanalization dual energy head CT (DECT) of stroke patients predict the fate of brain tissue?

2021· article· en· W4205170083 on OpenAlexvenueno aff
Bedoor Alomran, Danielle Byrne, Jonathan M. Walsh, Nicolas Murray, Fabio Settecase, Bethany Rohr, Axel Rohr

Bibliographic record

VenueCanadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques · 2021
Typearticle
Languageen
FieldMedicine
TopicRadiomics and Machine Learning in Medical Imaging
Canadian institutionsnot available
Fundersnot available
KeywordsParenchymaStainingMedicineIodineBrain infarctionSuperior sagittal sinusNuclear medicineStroke (engine)RadiologyContrast (vision)InfarctionPathologyIschemiaMyocardial infarctionCardiologyInternal medicineChemistry

Abstract

fetched live from OpenAlex

Background: On DECT, the ratio of maximum iodine concentration within parenchyma compared to the superior sagittal sinus has been shown to predict hemorrhagic transformation. We aimed to determine if this ratio also predicts the development of an infarct. Methods: 53 patients with small infarct cores (ASPECTS≥7) and good endovascular recanalization (mTICI 2b/3) were enrolled. Maximum brain parenchymal iodine concentration as per DECT relative to the superior sagittal sinus (iodine ratio) was correlated with the development of an infarct on follow up CT. Results: All patients showed contrast staining, 52 developed infarcts in the area of staining. The extent of infarction (smaller, equal or larger than area of staining) did not correlate with the iodine ratio. Conclusions: Brain parenchyma with contrast staining on post-procedure head CT almost invariably goes on to infarct, however the extent of infarct development is not predicted by the intensity of contrast staining. n=53 patients with successful recanalization of anterior circulation LVO infarct (TICI2b,3) with post procedural parenchymal iodine staining There was no correlation between the degree of contrast staining on initial post procedural CT as expressed in iodine ratio and F/U infarct extent.

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)0.000
metaresearch head score (Gemma)0.002
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 score0.012
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
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)0.0120.002

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 head0.017
GPT teacher head0.279
Teacher spread0.262 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

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Same venueCanadian Journal of Neurological Sciences / Journal Canadien des Sciences NeurologiquesSame topicRadiomics and Machine Learning in Medical ImagingFrench-language works237,207