Stimulated Raman histology for rapid and accurate intraoperative diagnosis of CNS tumors: Prospective blinded study

Daniel G. Eichberg, Ashish H. Shah, Long Di, Alexa M. Semonche, George Jimsheleishvili, Evan M. Luther, Christopher A. Sarkiss, Allan D. Levi, Sakir H. Gultekin, Ricardo J. Komotar, Michael E. Ivan

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


OBJECTIVE In some centers where brain tumor surgery is performed, the opportunity for expert intraoperative neuropathology consultation is lacking. Consequently, surgeons may not have access to the highest quality diagnostic histological data to inform surgical decision-making. Stimulated Raman histology (SRH) is a novel technology that allows for rapid acquisition of diagnostic histological images at the bedside. METHODS The authors performed a prospective blinded cohort study of 82 consecutive patients undergoing resection of CNS tumors to compare diagnostic time and accuracy of SRH simulation to the gold standard, i.e., frozen and permanent section diagnosis. Diagnostic accuracy was determined by concordance of SRH-simulated intraoperative pathology consultation with a blinded board-certified neuropathologist, with official frozen section and permanent section results. RESULTS Overall, the mean time to diagnosis was 30.5 ± 13.2 minutes faster (p < 0.0001) for SRH simulation than for frozen section, with similar diagnostic correlation: 91.5% (κ = 0.834, p < 0.0001) between SRH simulation and permanent section, and 91.5% between frozen and permanent section (κ = 0.894, p < 0.0001). CONCLUSIONS SRH-simulated intraoperative pathology consultation was significantly faster and equally accurate as frozen section.

Original languageEnglish (US)
Pages (from-to)137-143
Number of pages7
JournalJournal of neurosurgery
Issue number1
StatePublished - Jan 2021


  • Brain tumor
  • Frozen section
  • Oncology
  • Pathology
  • Permanent section
  • Stimulated Raman histology

ASJC Scopus subject areas

  • Surgery
  • Clinical Neurology


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