Abstract TP55: Rate of Infarct Growth in Acute Ischemic Stroke is Independent of Apparent Diffusion Coefficient Threshold
Bibliographic record
Abstract
Background: For acute stroke assessment, apparent diffusion coefficient (ADC) obtained from diffusion-weighted imaging (DWI) provides sensitive detection of infarct volume. Identification of infarct growth in patients with acute ischemic stroke (AIS) is important for determining the efficacy of stroke therapy. Reported ADC thresholds for detecting AIS vary from 550 to 650 x10^-6mm^2/s. Therefore, the measurement of infarct growth is not standardized. Hypothesis: Measurement of the rate of infarct growth after stroke is independent of the ADC threshold used. Methods: 38 AIS patients (age; 71.5±17.0) were imaged acutely (within 4h) after stroke symptoms (Time1-Baseline) and repeated at 24h (Time2) on a 3T MR scanner. DTI data with 15 directions was acquired and used for ADC map calculations. Lesion volumes were calculated with ADC thresholds of 550, 600, 630 and 650 x10^-6mm^2/s using ANTONIA software. Rate (r) of infarct growth was calculated by r=Δvolume(ADC2-ADC1)/Δtime(time2-time1). Results: ADC volume and rate of infarct growth is reported in table 1. No significant difference was found in the rate of infarct growth between the two time points (one way ANOVA). Conclusion: Quantification of infarct evolution is critical for determining the efficacy of stroke therapy. Although absolute lesion volumes vary considerably, the rate of infarct growth is independent of the ADC threshold and should be the preferred measure of acute infarct growth.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".