Cavitation After Acute Symptomatic Lacunar Stroke Depends on Time, Location, and MRI Sequence
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Definitions for chronic lacunar infarcts vary. Recent retrospective studies suggest that many acute lacunar strokes do not develop a cavitated appearance. We determined the characteristics of acute lacunar infarcts on follow-up MRI in consecutive patients participating in prospective research studies. METHODS: Patients with acute lacunar infarction on diffusion-weighted imaging were selected from 3 prospective cohort studies of minor stroke imaged within <24 hours of onset. Follow-up MRI was performed at 30 days (Vascular Imaging of Acute Stroke for Identifying Predictors of Clinical Outcome and Recurrent Ischemic Events [VISION] study, n=21) or 90 days (VISION-2 and CT and MRI in the Triage of TIA and Minor Cerebrovascular Events to Identify High Risk Patients [CATCH] studies, n=34). Evidence of cavitation on MRI was rated separately on fluid-attenuated inversion recovery, T1, and T2 sequences by 2 independent study physicians; discrepant readings were resolved by consensus. RESULTS: Probable or definite cavitation on any sequence was more common at 90 days compared with 30 days (P≤0.001 for all sequences). At 90 days, evidence of cavitation was seen on at least 1 sequence in 33 of 34 patients (97%). The T1-weighted sequence was most sensitive to the presence of cavitation (94% at 90 days). By contrast, the fluid-attenuated inversion recovery sequence frequently failed to show evidence of cavitation in the brain stem or thalamus (only 10 of 18 [56%] showed cavitation). CONCLUSIONS: MRI scanning at 90 days with T1-weighted imaging reveals evidence of cavitation in nearly all cases of acute lacunar infarction. By contrast, reliance on fluid-attenuated inversion recovery alone will miss many cavitated lesions in the thalamus and brain stem. These factors should be taken into account in the development of standardized criteria for lacunar infarction on MRI.
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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 | 0.007 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".