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Record W4385715528 · doi:10.1097/rct.0000000000001531

Hemodynamic Characteristics of Intracranial Atherosclerotic Stenosis: A Pilot Study of Contrast Enhancement Time-Density Curves Based on Regions of Interest

2023· article· en· W4385715528 on OpenAlexaboutno aff
Xiang Yu, Aijing Dong, Weiguo Zhang, Ping Chen

Bibliographic record

VenueJournal of Computer Assisted Tomography · 2023
Typearticle
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineHounsfield scaleArea under the curveOcclusionConfidence intervalHemodynamicsStenosisCardiologyRadiologyStroke (engine)Odds ratioRegion of interestReceiver operating characteristicNuclear medicineInternal medicineComputed tomography

Abstract

fetched live from OpenAlex

OBJECTIVE: The present study aimed to analyze the hemodynamic characteristics of occluded vessels responsible for acute ischemic stroke and to diagnose the occlusion types. METHODS: Multimodal computed tomography (CT) was used to accurately identify the range of occlusion of large intracranial vessels. Regions of interest (ROI 1-3 ) were manually delineated at sites 2 mm away from the proximal, middle, and distal portions of each occlusion, generating 3 contrast enhancement time-density curves. The peak CT attenuation values, or Hounsfield units (H 1-3 ), and time-to-peak values (T 1-3 ) were extracted from each curve. H 0 and T 0 of the time-density curve, based on ROI 0 of the automatically recognized input artery, were used as the baseline values with which the odds ratios of each parameter, H 1-3/0 and T 1-3/0 , were obtained. The present study aimed to establish prediction models for intracranial atherosclerotic stenosis (ICAS) based on each ROI's time-density curve. RESULTS: Among the 33 acutely occluded intracranial vessels, 10 were found to have ICAS, whereas 23 did not, based on the diagnostic criteria. Significant differences were observed in patient sex, neutrophil-to-lymphocyte ratio upon admission, Alberta Stroke Program Early CT Score 24-48 hours after reperfusion therapy, and H 1/0 , H 3/0 , and T 3/0 between the ICAS and non-ICAS groups ( P < 0.05). The prediction model (model 3) based on the ROI 3 time-density curve showed the best performance for the diagnosis of ICAS (area under the curve, 0.944; 95% confidence interval, 0.854-1.000). The prediction models based on ROI 1 (model 1) and ROI 2 (model 2) showed moderate diagnostic performance (area under the curve, 0.817 vs 0.822, respectively). The best visualization for proximal occlusions was in the first phase (arterial phase) of multiphase CT angiography, and in the second phase (early venous phase) for distal occlusions. CONCLUSIONS: The contrast enhancement time-density curves of the ROIs at all evaluated portions of the acute ischemic stroke occlusions provided a visual display of the blood flow characteristics of the responsible vessels. The time-density curve of the ROI placed 2 mm from the distal occlusion was a combined effect of residual blood flow and collateral establishment, thus providing good performance for the diagnosis of ICAS.

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)0.003
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 score0.001
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.036
GPT teacher head0.263
Teacher spread0.227 · 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".

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Citations0
Published2023
Admission routes1
Has abstractyes

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