Microfibrillar collagen hemostat–induced necrotizing granulomatous inflammation developing after craniotomy: a pediatric case series
Bibliographic record
Abstract
OBJECT: Microfibrillar collagen hemostat (MCH; trade name Avitene) is a partially water-insoluble acid salt of purified bovine corium collagen. This agent has been widely used to control hemorrhage at surgery, and especially during pediatric neurosurgeries at the authors' institution. Despite its effectiveness, rare case reports detailing adverse inflammatory reactions to MCH have been documented. Based primarily on MR imaging, postoperative reactions have most commonly elicited clinical differential diagnoses of tumor recurrence or abscess. According to the literature, MCH induces a very characteristic mixed inflammatory response that is rich in eosinophils; in light of these observations, many authors have suggested an allergy-based pathogenesis. METHODS: The authors retrospectively reviewed 3 pediatric neurosurgical cases treated at their institution, wherein a common histomorphological inflammatory reaction to MCH was elicited at the site of prior craniotomy. RESULTS: Case 1 is that of a 10-year-old girl whose diagnosis was a right temporal lobe ganglioglioma, classified as WHO Grade I. Case 2 is that of a 9-year-old boy whose diagnosis was a left parietal lobe anaplastic ependymoma, classified as WHO Grade III. Finally, Case 3 is that of a 15-year-old girl whose diagnosis was focal cortical dysplasia Type IIA affecting the left occipital lobe. Each patient presented with new or recurrent seizures 5–6 weeks after the initial resection. The postsurgical reactions incited by MCH mimicked the radiological appearance of either an abscess (Cases 2 and 3) or recurrent tumor (Case 1). Histologically, the mixed inflammatory infiltrate was typified by the presence of MCH-centric necrotizing granulomas that were surrounded by a palisade of macrophages and often several eosinophils. CONCLUSIONS: The findings are in keeping with previous case reports describing the clinicopathological features of adverse reactions occurring due to MCH. Based on the authors' observations, the possibility of an idiopathic inflammatory reaction to MCH should be considered when either seizures, a typical radiological appearance (that is, consistent with tumor recurrence or abscess formation), or both arise shortly after initial surgery. A conservative treatment approach to this type of inflammatory lesion appears to be the most appropriate management strategy.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".