Accuracy and reliability of PBV ASPECTS, CBV ASPECTS and NCCT ASPECTS in acute ischaemic stroke: a matched-pair analysis
Bibliographic record
Abstract
Background and purpose To investigate the reliability and accuracy of Alberta Stroke Program Early Computed Tomography Scores (ASPECTS) derived from flatpanel detector computed tomography pooled blood volume maps compared to non-contrast computed tomography and multidetector computed tomography perfusion cerebral blood volume maps. Methods ASPECTS from pooled blood volume maps were evaluated retrospectively by two experienced readers for 37 consecutive patients with acute middle cerebral artery (MCA) M1 occlusion who underwent flatpanel detector computed tomography perfusion imaging before mechanical thrombectomy between November 2016 and February 2019. For comparison with ASPECTS from non-contrast computed tomography and cerebral blood volume maps, a matched-pair analysis according to pre-stroke modified Rankin scale, age, stroke severity, site of occlusion, time from stroke onset to imaging and final modified thrombolysis in cerebral infarction (mTICI) was performed in a separate group of patients who underwent multimodal computed tomography prior to mechanical thrombectomy between June 2015 and February 2019. Follow-up ASPECTS were derived from either non-contrast computed tomography or from magnetic resonance imaging (in seven patients) one day after mechanical thrombectomy. Results Interrater agreement was best for non-contrast computed tomography ASPECTS (w-kappa = 0.74, vs. w-kappa = 0.63 for cerebral blood volume ASPECTS and w-kappa = 0.53 for pooled blood volume ASPECTS). Also, accuracy, defined as correlation between acute and follow-up ASPECTS, was best for non-contrast computed tomography ASPECTS (Spearman ρ = 0.86 (0.65–0.97), P < 0.001), while it was lower and comparable for pooled blood volume ASPECTS (ρ = 0.58 (0.32–0.79), P < 0.001) and cerebral blood volume ASPECTS (ρ = 0.52 (0.17–0.80), P = 0.001). It was noteworthy that cases of relevant infarct overestimation by two or more ASPECTS regions (compared to follow-up imaging) were observed for both acute pooled blood volume and cerebral blood volume ASPECTS but occurred more often for acute pooled blood volume ASPECTS (25% vs. 5%, P = 0.02). Conclusion Non-contrast computed tomography ASPECTS outperformed both pooled blood volume ASPECTS and cerebral blood volume ASPECTS in accuracy and reliability. Importantly, relevant infarct overestimation was observed more often in pooled blood volume ASPECTS than cerebral blood volume ASPECTS, limiting its present clinical applicability for acute stroke imaging.
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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 | 0.009 | 0.042 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".