Estimation of Acute Infarct Volume with Reference Maps: A Simple Visual Tool for Decision Making in Thrombectomy Cases
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Thrombectomy within 24 hours can improve outcomes in selected patients with a clinical-infarct mismatch. We devised an easy-to-use visual estimation tool that allows infarct volume estimation in centers with limited resources. METHODS: We identified 1,031 patients with cardioembolic or large-artery atherosclerosis infarction on diffusion-weighted images (DWIs) obtained before recanalization therapy and within 24 hours of onset, and occlusion of the internal carotid or middle cerebral artery. Acute DWIs were mapped onto a standard template and used to create visual reference maps with known lesion volumes, which were then used in a validation study (with 130 cases) against software estimates of infarct volume. RESULTS: The DWI reference map chart comprises 144 maps corresponding to 12 different infarct volumes (0.5, 1, 2, 3, 5, 7, 9, 11, 13, 15, 17, and 19 mL) in each of 12 template slices (Montreal Neurological Institute z-axis -15 to 51 mm). Infarct volume in a patient is estimated by selecting a slice with a similar infarct size at the corresponding z-axis level on the reference maps and then adding up over all slices. The method yielded good correlations to software volumetrics and was easily learned by both experienced and junior physicians, with approximately 1 to 2 minutes spent per case. The sensitivity, specificity, and accuracy for detecting threshold infarct volumes (<21, <31, and <51 mL) were very high (all about >90%). CONCLUSION: s We developed easy-to-use reference maps that allow prompt and reliable visual estimation of infarct volumes for triaging patients to thrombectomy in acute stroke.
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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".