Abstract 2546: Correlation Between Diffusion-weighted Imaging (DWI) Lesion Volume And Alberta Stroke Program Early CT Score (ASPECTS) In Patients Undergoing Acute Stroke Intervention
Bibliographic record
Abstract
Background and Purpose: Selection of patients for endovascular acute stroke therapy is evolving into imaging based paradigms that quantitatively assess infarct core thresholds beyond which reperfusion is considered futile or detrimental. We sought to determine whether a correlation exists between pre-intervention infarct volume as measured by DWI MRI and ASPECT scores on CT in patients with acute stroke treated with endovascular therapy who underwent both a pre-procedure MRI scan and a non-contrast CT scan at our institution. Methods: Retrospective review of a prospectively maintained database of acute ischemic strokes treated with endovascular therapy at the University of Pittsburgh Medical Center during 2004-2011. CT-ASPECT scores were prospectively scored by blinded observers. Infarct volume on DWI was determined by automated software analysis (RAPID, n=25 and MIPAV, n=53). The following additional factors were considered: age, NIHSS, time from last seen well (TLSW) to angiography, site of clot occlusion, time between obtaining CT scan and MRI, and parenchymal hematoma (PH) formation. Results: Of 77 patients included in the study, there was a significant negative correlation between CT-ASPECT score and DWI volume size (p<0.0001, by ANOVA). Table 1 outlines the distribution of ASPECTS scores and corresponding mean DWI volumes along with other variables of interest. The mean time between obtaining the CT and MRI scan was 207 minutes. Conclusions: A CT-ASPECT score of 7 or greater corresponds to an average DWI volume of 23 ml or less. Recent studies have shown that a pre treatment DWI volume of <25 ml is predictive of favorable outcomes. Therefore, our findings provide further support of the concept that an ASPECT score cut off of 7 or greater corresponds to core volume thresholds that are predictive of good outcomes following revascularization. Future prospective studies are needed to compare the benefit of CT ASPECTS scores alone versus DWI MRI or other advanced imaging modalities as selection tool for acute stroke endovascular therapy.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 0.000 |
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.
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".