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Updated: Jan 7, 2026
Real-Time, Two-Color Stimulated Raman Scattering Imaging of Mouse Brain for Tissue Diagnosis
Published on: February 1, 2022
The Intraoperative Utility of Raman Spectroscopy for Neurosurgical Oncology
Jia-Shu Chen1, Jun Yeop Oh1, Todd C Hollon2
1Department of Neurological Surgery, University of California San Francisco, San Francisco, CA 94143, USA.
Abstract:
Maximal safe surgical resection is a foundational principle in brain tumor surgery. To date, many intraoperative modalities have been developed to help facilitate the identification of brain tumor versus normal brain tissue so that surgical resection is maximized but limited to the boundaries of the tumor for preservation of neurological function. Of note, Raman spectroscopy has been adapted into one of these modalities because of its ability to provide rapid, non-destructive, label-free intraoperative evaluation of tumor borders and molecular classifications and help guide surgical decision-making in real time. In this review, we performed a literature review of the landmark studies incorporating Raman spectroscopy into neurosurgical care to highlight its current applications and limitations. In this modern day, Raman spectroscopy is able to detect tumor cells intraoperatively for primary glial neoplasms, meningiomas, and brain metastases with greater than 90% accuracy. For glioma surgery, a major recent advancement is the ability to detect different mutations intraoperatively, specifically IDH, 1p19q co-deletion, and ATRX, given their implications on survival and how much extent of resection should be ideally achieved. With recent advancements in artificial intelligence and their integration into stimulated Raman histology, many of these tasks can be completed in as fast as ~10 s and on average 2-3 min. Despite the incorporation of artificial intelligence, spectral data can still be heavily influenced by background noise, and its preprocessing has significant variability across platforms, which can impact the accuracy of results. Overall, Raman spectroscopy has significantly changed the intraoperative workflow of brain tumor surgery, and this review highlights the capabilities that neurosurgeons can currently take advantage of in their practice, the existing data to support it, and the areas that researchers can further optimize to improve accuracy and patient outcomes.
Insights
Raman spectroscopy offers accurate, real-time intraoperative brain tumor detection and molecular classification. Advancements in artificial intelligence enhance speed, improving surgical resection and patient outcomes.
Area of Science:
- Neurosurgery
- Oncology
- Spectroscopy
Background:
- Maximal safe surgical resection is crucial in brain tumor surgery.
- Intraoperative modalities aid in distinguishing tumor from normal tissue.
- Raman spectroscopy provides label-free, real-time molecular evaluation.
Purpose of the Study:
- To review landmark studies on Raman spectroscopy in neurosurgery.
- To highlight current applications and limitations of this technology.
- To discuss its impact on surgical decision-making.
Main Methods:
- Literature review of studies using Raman spectroscopy in neurosurgery.
- Analysis of accuracy in detecting various brain tumors.
- Evaluation of AI integration for molecular classification.
Main Results:
- Raman spectroscopy achieves >90% accuracy in detecting glial neoplasms, meningiomas, and metastases.
- Intraoperative detection of glioma mutations (IDH, 1p19q, ATRX) is now possible.
- AI integration with stimulated Raman histology significantly reduces analysis time.
Conclusions:
- Raman spectroscopy is transforming intraoperative brain tumor surgery.
- It enables precise tumor margin identification and molecular subtyping.
- Further optimization is needed to address spectral noise and platform variability.
