aceArtificial intelligence–based tumor detection using stimulated Raman histology in patients undergoing neurosurgical biopsies
OBJECTIVE Intraoperative confirmation of diagnostic tumor tissue is critical in neurosurgical biopsies, particularly in stereotactic procedures, in which sampling error remains a major limitation. Stimulated Raman histology (SRH) enables rapid, label-free tissue imaging directly in the operating room. This study aimed to evaluate the performance of intraoperative SRH combined with artificial intelligence (AI)–based tumor detection using a CE (Conformité Européenne)–certified algorithm under routine clinical cond…
In 204 scans from 89 biopsy patients, the Glioma Reveal algorithm detected tumor tissue with 80.9% initial accuracy, rising to 94.1% after expert review, giving rapid intraoperative confirmation of tumor tissue.
The algorithm reached only 62.5% accuracy on nonneoplastic lesions because of reactive mimics, and sensitivity for gliomas and lymphomas was 78.8%, with false negatives driven by tissue heterogeneity.
This was a retrospective single-center study, and the higher accuracy figures relied on expert re-review of discordant cases rather than the algorithm alone; heterogeneity and sampling differences affected metrics.
Evidence
- Peer-reviewedNeurosurgical Focus2026-10-28
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Truvace Impact Record TRV-2026-2298, v1: “Artificial intelligence–based tumor detection using stimulated Raman histology in patients undergoing neurosurgical biopsies.” Truvace, 2026-10-28. /record/TRV-2026-2298 (accessed at citation time). sha256 cfb0cbd9d75a7f09…
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