Interobserver Agreement of ASPECT Score Distribution for Noncontrast CT, CT Angiography, and CT Perfusion in Acute Stroke
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: The Alberta Stroke program early CT score (ASPECTS) is a semiquantative scale for estimating extent and distribution of early ischemic changes within the MCA territory in the acute stroke setting. Good interobserver agreement of total ASPECTS is demonstrated for noncontrast CT (NCCT) and other imaging modalities. Our purpose is to assess interobserver agreement for individual ASPECTS regions for different imaging modalities. METHODS: One hundred and eighty-one consecutive patients presenting with acute stroke symptoms within 4.5 hours of onset were included. Four readers assigned total and individual ASPECTS for NCCT, CT angiography source images (CTA-SI), and CTP maps of cerebral blood volume (CTP-CBV). Interobserver agreement was assessed by measuring internal consistency and concordance of total and individual ASPECTS using Cronbach's α and intraclass correlation coefficient, respectively. RESULTS: Total ASPECTS demonstrated very good concordance and internal consistency for all 3 modalities. Intraclass correlation coefficient and Cronbach's α were 0.834 and 0.859 for NCCT, 0.876 and 0.894 for CTA, and 0.903 and 0.911 for CTP-CBV, respectively. Performance for individual ASPECTS regions was inferior to total ASPECTS, but incremental improvement in interobserver reliability was demonstrated for NCCT, CTA-SI, and CTP-CBV, respectively. Highest concordance was shown for caudate, lentiform, and M1-M3, whereas performance for internal capsule and M4-M6 was poorer. CONCLUSIONS: CTP-CBV demonstrates the highest interobserver agreement for individual ASPECTS regions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".