Brain Reorganization after Endovascular Treatment in a Patient with a Large Arteriovenous Malformation: The Role of Diagnostic and Functional Neuroimaging Techniques
Bibliographic record
Abstract
We describe a case of brain cortical reorganization after embolization of a large right temporal arteriovenous malformation. A comprehensive imaging protocol, including functional magnetic resonance imaging (fMRI), cortical thickness analysis and 320-row computed tomography (CT) perfusion was used to provide information on brain plasticity and potential steal phenomenon. A 25-year-old man known for a right temporal grade V Spetzler-Martin classification arteriovenous malformation (AVM) presented with left progressive hemiparesis. He underwent functional 3T magnetic resonance imaging (fMRI), cortical thickness analysis, and CT perfusion (CT 320 row, Aquilion ONE, Toshiba, Tokyo, Japan) before and after endovascular treatment. The results were compared to look for modifications in brain perfusion and organization. An improvement in the left hemiparesis and a reorganization of motor function were observed after endovascular treatment. Modifications in the angioarchitecture and perfusion of an extensive AVM may be accompanied by a functional and structural reorganization of the brain. The location in the so-called eloquent regions may not be sufficient to explain the wide spectrum of symptoms that these patients can present. A more comprehensive approach considering a global involvement of the brain in patients with large AVMs is suggested to achieve the best treatment strategy and to stage treatment in incurable AVMs.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".