e-ASPECTS software is non-inferior to \nneuroradiologists in applying the \nASPECT score to computed \ntomography scans of acute ischemic \nstroke patients
Bibliographic record
Abstract
Background: \nThe Alberta Stroke Program Early Computed Tomography Score (ASPECTS) is an established 10-point quantitative topographic computed tomography scan score to assess early ischemic changes. We performed a non-inferiority trial between the e-ASPECTS software and neuroradiologists in scoring ASPECTS on non-contrast enhanced computed tomography images of acute ischemic stroke patients. \n \nMethods : \nIn this multicenter study, e-ASPECTS and three independent neuroradiologists retrospectively and blindly assessed baseline non-contrast enhanced computed tomography images of 132 patients with acute anterior circulation ischemic stroke. Follow-up scans served as ground truth to determine the definite area of infarction. Sensitivity, specificity, and accuracy for region- and score-based analysis, receiver-operating characteristic curves, Bland-Altman plots and Matthews correlation coefficients relative to the ground truth were calculated and comparisons were made between neuroradiologists and different pre-specified e-ASPECTS operating points. The non-inferiority margin was set to 10% for both sensitivity and specificity on region-based analysis. \n \nResults : \nIn total 2640 (132 patients × 20 regions per patient) ASPECTS regions were scored. Mean time from onset to baseline computed tomography was 146 ± 124 min and median NIH Stroke Scale (NIHSS) was 11 (6–17, interquartile range). Median ASPECTS for ground truth on follow-up imaging was 8 (6.5–9, interquartile range). In the region-based analysis, two e-ASPECTS operating points (sensitivity, specificity, and accuracy of 44%, 93%, 87% and 44%, 91%, 85%) were statistically non-inferior to all three neuroradiologists (all p-values <0.003). Both Matthews correlation coefficients for e-ASPECTS were higher (0.36 and 0.34) than those of all neuroradiologists (0.32, 0.31, and 0.3). \n \nConclusions : \ne-ASPECTS was non-inferior to three neuroradiologists in scoring ASPECTS on non-contrast enhanced computed tomography images of acute stroke patients.
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 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| 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".