Whole-Brain Perfusion CT Patterns of Brain Arteriovenous Malformations: A Pilot Study in 18 Patients
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Little is known about the pathological mechanism or the anatomic and functional imaging features related to the clinical manifestations in patients with brain AVM. The purpose of this pilot study was to describe the pattern of whole-brain PCT abnormalities in brain AVMs and their potential to differentiate underlying pathomechanisms. MATERIALS AND METHODS: Whole-brain PCT performed on a 320-detector row CT scanner was analyzed in 18 patients with untreated brain AVMs. The patterns of perfusion abnormalities on CBV, CBF, and MTT maps were analyzed and were related to clinical presentation and cerebral angiography. RESULTS: The presenting symptoms were seizures (n = 5), focal neurologic deficit (n = 5), hemorrhage (n = 4), chemosis (n = 1), and none (n = 3). Three types of extranidal brain parenchymal perfusion abnormalities were noted. Decreased CBF, CBV, and MTT (pattern 1, "functional" arterial steal) were identified in 8 patients. Seizure was the most common presenting symptom in these patients (n = 5). Decreased CBF and CBV, and increased MTT (pattern 2, "ischemic" arterial steal) were noted in 4 patients. Focal neurologic deficit was the most common presenting symptom for these patients (n = 3). Increased CBV and MTT (pattern 3, venous congestion) were seen in 5 patients with presenting symptoms of neurologic deficit (n = 2), seizure (n = 1), hemorrhage (n = 1), and chemosis (n = 1). In 2 patients, pre- and posttreatment PCT was performed, which showed improvement of perfusion abnormalities. CONCLUSIONS: Whole-brain PCT shows different patterns of perfusion abnormalities in patients with brain AVM. These perfusion patterns may discriminate the different pathologic mechanisms involved in these malformations.
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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) | 0.001 | 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".