The hyperdense sylvian fissure MCA ”dot“ sign: a marker of acute CT ischemia
Bibliographic record
Abstract
P40 Background: The hyperdense appearance of the middle cerebral artery is now a familiar early warning of large cerebral infarction, brain oedema and poor prognosis. Less well described, however, is the hyperdensity associated with embolic occlusion of branches of the middle cerebral artery seen in the sylvian fissure (MCA ”dot“ sign). The aim of this study was to define this sign, and to determine the incidence, its diagnostic value, and reliability. Methods: Computed tomographic (CT) scans performed on patients with acute ischemic stroke within 3 hours of symptom onset were analysed for signs of thromboembolic stroke and evidence of early CT ischemia. Two neuroradiologists and two stroke neurologists initially blinded to all clinical information, and then with knowledge of the affected hemisphere evaluated scans for the presence of a hyperdense MCA sign (HMCA), a hyperdense sylvian fissure MCA ”dot“ sign, and for early MCA territory ischemic changes. Results: Of 100 consecutive patients presenting within 3 hours of symptom onset early CT ischemia was seen in 74 % of the baseline CT scans. The HMCA sign was seen in 5% of CT scans whereas the MCA ”dot“ sign was seen in 16% of which 2 were associated with a HMCA sign. The presence of a HMCA sign was associated with a greater probability of dependence or death than when a MCA ”dot“ sign was observed or no hyperdensity was seen (P<0.05). All 5 patients with a HMCA sign, including 2 with an associated MCA ”dot“ sign were either dead or dependent at 3 months. Patients with a dot sign alone had independent outcomes in 64% of cases (P<0.8). Balanced kappa statistics for both signs were in the moderate to good range when the side of stroke was known. Conclusions: The hyperdense sylvian fissure MCA ”dot“ sign is an early marker of thromboembolic occlusion of the distal MCA and of its branches.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".