Arterial Spin Labeling Perfusion Magnetic Resonance Imaging Performed in Acute Perinatal Stroke Reveals Hyperperfusion Associated With Ischemic Injury
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Perfusion-weighted imaging in adults with acute stroke often reveals hypoperfusion in the ischemic core and in a surrounding area of nondiffusion-restricted penumbral tissue. Perinatal stroke is common, but the perfusion pattern is rarely documented. We aimed to describe the perfusion pattern in newborns with perinatal stroke. METHODS: Neonates with clinical features of acute stroke underwent magnetic resonance imaging. Perfusion data were obtained using pseudocontinuous arterial spin labeling. Strokes were classified as arterial, venous, or both. Core infarction was determined by the presence of restricted diffusion on diffusion-weighted imaging. Perfusion-weighted imaging and susceptibility-weighted imaging signal in the ischemic area were visually compared with the homologous region in the contralesional hemisphere. Electroencephalogram data were evaluated for seizure activity. RESULTS: In 25 neonates with acute stroke, 8 of 11 (73%) with arterial ischemic stroke demonstrated hyperperfusion, 1 of 9 (11%) with venous stroke, and 4 of 5 (80%) with both. Hypoperfusion was observed in 3 of 9 (33%) with venous and none with arterial ischemic stroke. Perfusion was normal in 4 of 9 (45%) with venous and 1 of 5 (20%) with both. Twenty-one of 24 patients (88%) with electroencephalogram data had either electrographic seizures or focal sharp waves in the ipsilesional hemisphere (11/11 arterial ischemic stroke, 6/9 venous, and 4/5 both). CONCLUSIONS: Perfusion-weighted imaging can be obtained in neonates with acute stroke and often reveals hyperperfusion in the infarct core. Penumbra in arterial ischemic stroke is seldom found. Hyperperfusion may be caused by poststroke reperfusion or to neuronal hyperexcitability of stroke-associated seizure. Its identification may be useful for consideration of therapy for acute neonatal stroke.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".