MR imaging of dural arteriovenous fistulas draining into cerebellar cortical veins.
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Retrograde leptomeningeal venous drainage (RLVD) in a dural arteriovenous fistula (DAVF) is associated with intracerebral hemorrhage, nonhemorrhagic neurologic deficit, or death, and recognizing the presence of this drainage is important. We investigated the MR findings of DAVFs draining into cerebellar cortical veins and compared these findings with those of conventional angiography. METHODS: The MR and angiographic findings of six patients (five men, one woman; mean age, 73.4 years) with DAVF with RLVD into cerebellar cortical veins were reviewed retrospectively. Signal intensity characteristics, contrast material enhancement, topography of the lesion, and presence of signal voids were evaluated on MR images. Site of the shunt, feeding arteries, and draining veins were evaluated on angiograms. RESULTS: In all patients, MR images showed high signal intensity on T2-weighted images and peripheral enhancement on gadolinium-enhanced T1-weighted images at the inferior aspect of the cerebellar hemisphere. A combination of posterior meningeal and occipital arteries was the most frequent blood supply (83%) for these DAVFs. In all six patients, the inferior hemispheric vein was the primary draining vein. CONCLUSION: The characteristic MR findings of DAVF draining into cerebellar cortical veins represent venous congestive encephalopathy in the territory of the involved cortical vein.
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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 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".