Idiopathic Neonatal Subpial Hemorrhage with Underlying Cerebral Infarct: Imaging Features and Clinical Outcome
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Neonatal subpial hemorrhage with underlying cerebral infarct is a previously described but poorly understood clinicoradiographic syndrome. We sought to further characterize the cranial ultrasound and MR imaging characteristics and associated outcomes of this condition across the full range of gestational ages, including extreme and very preterm neonates. MATERIALS AND METHODS: This was a single tertiary pediatric center retrospective case series. Brain MR imaging and cranial ultrasound of neonates with subpial hemorrhage with underlying cerebral infarct were identified from a population-based radiology registry (2006-2020). Original images were reviewed by 2 neuroradiologists blinded to history and outcome. Clinical presentation, course, and outcome at >12 months were abstracted from medical records. The diagnostic utility of cranial ultrasound was compared with that of MR imaging. RESULTS: Sixteen patients were included (median gestational age, 36.5 weeks; range, 27-41 weeks; 31% premature). MR images were obtained acutely at the time of presentation between days 0 and 9 of life. On T2WI and DWI, a consistent presence of a hypointense subpial bleed and an underlying hyperintense cerebral cortex were recognized, which created a distinct MR imaging pattern resembling the yin-yang symbol. Findings of all the MRAs and MRVs were normal. Cranial ultrasound detected 6 of 7 MR imaging lesions with sonographic features correlating well with MR imaging. The 3 extreme or very preterm neonates did not survive. The remainder survived with relatively mild neurologic deficits. CONCLUSIONS: Subpial hemorrhage with underlying infarction is a recognizable condition with unique MR imaging and sonographic features. Improved recognition may advance understanding of risk factors and outcomes.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".