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Updated: Jun 24, 2025
Real-Time, Two-Color Stimulated Raman Scattering Imaging of Mouse Brain for Tissue Diagnosis
Published on: February 1, 2022
In situ brain tumor detection using a Raman spectroscopy system-results of a multicenter study
Katherine Ember1,2, Frédérick Dallaire1,2, Arthur Plante1,2
1Polytechnique Montréal, Montreal, Canada.
Abstract:
Safe and effective brain tumor surgery aims to remove tumor tissue, not non-tumoral brain. This is a challenge since tumor cells are often not visually distinguishable from peritumoral brain during surgery. To address this, we conducted a multicenter study testing whether the Sentry System could distinguish the three most common types of brain tumors from brain tissue in a label-free manner. The Sentry System is a new real time, in situ brain tumor detection device that merges Raman spectroscopy with machine learning tissue classifiers. Nine hundred and seventy-six in situ spectroscopy measurements and colocalized tissue specimens were acquired from 67 patients undergoing surgery for glioblastoma, brain metastases, or meningioma to assess tumor classification. The device achieved diagnostic accuracies of 91% for glioblastoma, 97% for brain metastases, and 96% for meningiomas. These data show that the Sentry System discriminated tumor containing tissue from non-tumoral brain in real time and prior to resection.
Insights
The Sentry System accurately distinguishes brain tumors from healthy brain tissue in real-time during surgery. This novel device uses Raman spectroscopy and AI to improve tumor removal and patient outcomes.
Area of Science:
- Neurosurgery
- Medical Technology
- Spectroscopy
Background:
- Distinguishing brain tumors from healthy tissue during surgery is challenging.
- Accurate tumor margin identification is crucial for effective surgical resection.
- Current methods lack real-time, label-free tissue differentiation.
Purpose of the Study:
- To evaluate the Sentry System's ability to differentiate common brain tumors from non-tumoral brain tissue.
- To assess the real-time, in situ diagnostic performance of the Sentry System.
- To validate the device's accuracy across glioblastoma, brain metastases, and meningioma.
Main Methods:
- A multicenter study involving 67 patients undergoing brain tumor surgery.
- Acquisition of 976 in situ Raman spectroscopy measurements.
- Utilized machine learning classifiers for label-free tissue analysis.
Main Results:
- The Sentry System achieved high diagnostic accuracies: 91% for glioblastoma, 97% for brain metastases, and 96% for meningiomas.
- The device successfully discriminated tumor-containing tissue from non-tumoral brain in real time.
- Spectroscopic data and tissue specimens were colocalized for validation.
Conclusions:
- The Sentry System demonstrates significant potential for real-time, intraoperative brain tumor detection.
- This technology can aid surgeons in achieving more precise tumor resection.
- The Sentry System offers a label-free approach to enhance surgical decision-making.
