The presentation of a huge scalp hemangioma similar to an arteriovenous malformation presentation; case report and review of the literature
Bibliographic record
Abstract
Background Hemangiomas are the most common tumors of infancy, with a prevalence of 10–12 % by 1 year (3). They are classified as infantile or congenital (4). The congenital subtype was first described by Boon et al. in 1996 (5) and is divided into rapidly involuting congenital hemangiomas (RICH) and non-involuting congenital hemangiomas (NICH) (5,7,12). Herein, we report a neonate with a large, left extracranial scalp RICH detected at birth, accompanied by cutaneous features. This report also reviews the clinical characteristics and management of similar cases. Case description A full-term female neonate presented with a large, well-defined left parietal-occipital mass extending to the upper posterior neck. The lesion was covered by intact skin and hair, displayed purple discoloration, and displaced the left ear anteriorly and slightly downward. Magnetic resonance imaging (MRI) revealed a large, heterogeneous, solid scalp mass in the left parieto-occipital region, with strong, heterogeneous enhancement and a small non-enhancing central area. A scalp RICH was diagnosed. The infant developed torticollis and left posterior positional plagiocephaly, which improved with physiotherapy. After one year, the mass had regressed, leaving partial alopecia. Conclusion RICH presents at birth and exhibits distinct clinical, radiological, angiographic, and histopathological features. Prenatal diagnosis is possible using imaging modalities. The condition typically follows a benign course and often regresses spontaneously, obviating treatment. However, RICH can lead to life-threatening complications that may require intervention. Effective management depends on understanding the disease course and patient status and should involve a multidisciplinary team.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".