Raman-based tools can give a brain-surgery team another source of information about tumor tissue, but they do not eliminate uncertainty or continuously show the whole tumor margin. Two distinct approaches are being studied: a probe that measures tissue in place and stimulated Raman histology (SRH), which analyzes tissue after it has been removed. Studies report promising diagnostic accuracy, but have not established better survival or neurological outcomes.
How Raman methods provide information about brain tissue
Raman spectroscopy identifies molecular composition by measuring light scattered by tissue. The resulting signal can be analyzed by a classifier to estimate whether tissue is tumor or normal. In brain surgery, however, “Raman imaging” can refer to different workflows with different roles in the operating room.
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In situ probe: a point measurement on tissue in the brain
The Sentry approach uses a handheld probe connected by fiber-optic cable to a near-infrared laser and spectrometer. The probe tip contacts tissue being assessed, and a machine-learning classifier returns a tumor-versus-normal prediction in real time. It is a point measurement, not a scan that maps the whole brain or continuously displays the tumor boundary. The 2024 multicenter study evaluated this in situ workflow.
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1Repair Windows errors before they cause bigger problems2Fix the driver behind crashes, sound loss and screen glitches3Clear out junk files and repair common Windows errorsStimulated Raman histology: an image of tissue that has been removed
SRH produces histology-like images from fresh tissue without the usual frozen-section staining workflow. In the studied workflow, a deep-learning model interprets those images to support a rapid intraoperative diagnosis. The tissue must first be sampled and removed; SRH is not a live view of the entire tumor margin in the brain. The 2020 multicenter trial evaluated SRH with deep neural networks.
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What the clinical studies have found
The reported percentages describe how accurately study systems classified tissue or made predictions in specific study settings. They are not evidence that using Raman technology improves the amount of tumor removed, survival, or neurological function.
In situ spectroscopy: 2024 multicenter study
At two hospitals, investigators studied 67 adults undergoing open brain surgery and collected 976 in situ spectroscopy measurements with corresponding tissue specimens. Reported diagnostic accuracy was 91% for glioblastoma, 97% for brain metastases, and 96% for meningioma. Surgeons were blinded to the Raman measurements, so the study did not test whether acting on the probe’s predictions changes surgical decisions or patient outcomes. Read the study in Scientific Reports.
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SRH plus deep learning: 2020 prospective trial
In a separate multicenter prospective trial, the algorithm produced predictions in under 150 seconds. Overall accuracy was 94.6%, compared with 93.9% for pathologist interpretation of conventional histology. These results concern diagnosis from tissue samples, rather than direct guidance at the live tumor boundary. Read the Nature Medicine study.
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SRH at tumor margins: 2024 initial experience
A Heidelberg study assessed 70 consecutive adult cases. The authors reported an area under the curve (AUC) of 0.77 for diagnostic predictions and an AUC of 0.93 for IDH mutation prediction among the 18 patients assessed for that feature. SRH findings from tumor-margin samples corresponded with postoperative MRI in four of five cases. That small comparison is promising but does not establish clinical benefit; the authors describe a need for further refinement and workflow integration. See the PubMed record.
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Can Raman imaging show the brain tumor margin?
Not as a continuous, whole-margin image based on the evidence described here. An in situ probe samples tissue at the contact point. SRH creates images from a removed sample, including samples taken near a margin, but that is not the same as displaying the entire boundary during surgery. Margin sampling may help teams assess tissue, yet the available five-case comparison with postoperative MRI is too small to show that Raman methods reliably define margins or improve how much tumor surgeons can safely remove.
Is Raman technology used in brain surgery now?
Use and availability depend on the specific system, setting, and jurisdiction. The National Cancer Institute reported in 2020 that SRH systems were in use at some major cancer centers, while noting financial, regulatory, and clinician-training challenges to broader integration. That does not mean every hospital has access to SRH or that all Raman approaches are routine clinical tools. The NCI overview describes the SRH workflow and its clinical context.
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As of October 8, 2026, Reveal Surgical describes Sentry as a future flagship product and labels it “Currently for investigational use only.” That product-specific statement does not establish availability or regulatory status for other Raman systems. Check the manufacturer’s current Sentry page.
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Regulatory claims also need to be tied to the exact product and place. A U.S. SBIR portfolio record states that an Invenio NIO system had CE certification for brain tumor margin identification; a separate SBIR award record from 2016–2018 describes planned development of an FDA-cleared stimulated Raman scattering instrument. Those records concern different products and periods. They do not show present FDA authorization for all Raman systems or a uniform regulatory status worldwide. Invenio Imaging portfolio record and 2016–2018 SBIR award record.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What “takes guesswork out” should mean
Raman methods can add molecular information and rapid diagnostic predictions to an operation. Whether that information helps a surgeon make a better decision is a separate question from whether a classifier is accurate in a study. The in situ study blinded surgeons to its measurements, and SRH studies analyzed samples rather than continuously guiding the surgeon’s hand at the live boundary. The evidence here therefore supports promise as an added diagnostic signal—not a claim that guesswork has disappeared or that patient outcomes have improved.
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