A new system can identify genetic mutations in brain tumors in minutes during surgery, a significant advance from the days or weeks it currently takes. This rapid analysis gives surgeons critical, real-time information to guide their decisions in the operating room, potentially improving patient outcomes by allowing for more precise tumor removal and immediate, targeted treatment.
The innovative techniques, developed by separate research teams, use different methods—one employing mass spectrometry and the other a specialized polymerase chain reaction (PCR) test—but both deliver a molecular diagnosis with unprecedented speed. This leap forward addresses a major challenge in neurosurgery: the inability to quickly identify a tumor’s specific genetic makeup, which dictates its behavior and response to treatment. Armed with this knowledge during an operation, surgeons can better determine how much tissue to remove and whether to administer localized therapies, ushering in a new era of personalized medicine for brain cancer patients.
Groundbreaking Techniques for Real-Time Analysis
Researchers have developed two distinct but equally promising methods for rapid intraoperative diagnosis of brain tumors. One team, from Mayo Clinic, has pioneered a platform that uses mass spectrometry to detect isocitrate dehydrogenase (IDH) mutations, a key genetic marker in gliomas, the most common type of brain cancer. This technique analyzes small tissue biopsies taken during surgery and can provide a result within two minutes. Neurosurgeons can collect samples from the tumor’s core and surrounding areas to assess its spread and make more informed decisions about the extent of resection needed to improve patient outcomes.
A second team, from NYU Langone Health, has developed an “Ultra-Rapid droplet digital PCR” (UR-ddPCR) system. This method can measure the level of tumor cells in a tissue sample in about 15 minutes and is sensitive enough to detect as few as five cancer cells per square millimeter. The UR-ddPCR has proven to be as accurate as standard PCR tests, which typically take several hours to produce results, making them impractical for use during surgery. Daniel Orringer, a neurosurgeon and co-senior investigator on the study, stated that this technology allows surgeons to determine which cells are cancerous with a level of accuracy never before possible in a surgical setting.
Improving Surgical Precision and Patient Outcomes
The primary advantage of these new technologies is their potential to significantly enhance the precision of brain tumor surgery. For many cancers, particularly gliomas, the success of the operation and the prevention of recurrence depend on removing as much of the tumor as possible. However, it is often difficult for surgeons to distinguish between cancerous and healthy brain tissue at the microscopic level. The ability to identify genetic mutations in real-time provides a clear, molecular-level map of the tumor’s boundaries.
With this information, surgeons can be more aggressive in removing cancerous tissue while minimizing damage to healthy brain matter, which is crucial for preserving neurological function. The Mayo Clinic study, which involved over 240 biopsies from patients undergoing surgery for suspected gliomas between 2021 and 2023, demonstrated that their mass spectrometry platform could identify IDH mutations with 100% accuracy. This level of precision can help surgeons tailor the procedure to the specific characteristics of each patient’s tumor, leading to more effective treatment and a better prognosis.
A New Era of Personalized Medicine
Beyond guiding surgical decisions, rapid intraoperative diagnosis opens the door for immediate, targeted therapies. Researchers hope that new treatments developed to target specific mutations, such as those in the IDH gene, can be delivered directly into the brain in the operating room at the time of surgery. This approach, a cornerstone of personalized medicine, could significantly improve the efficacy of cancer treatments by attacking the tumor at its source before it has a chance to regrow.
Gilad Evrony, a co-senior investigator on the UR-ddPCR study, noted that the technology has the potential to be used for cancers outside the brain as well. The ability to make a quick and accurate molecular diagnosis during surgery could revolutionize the treatment of many types of cancer, allowing for more tailored and effective therapies across the board.
The Role of Artificial Intelligence
In addition to these new diagnostic platforms, artificial intelligence is also playing an increasingly important role in the rapid analysis of brain tumors. An AI tool called CHARM (Cryosection Histopathology Assessment and Review Machine) has been developed by researchers at Harvard Medical School. CHARM can decode a brain tumor’s DNA to determine its molecular identity during surgery, providing a diagnosis with 93% accuracy. This is a significant improvement over the traditional method of freezing and examining tissue samples under a microscope, which can alter the appearance of cells and interfere with the accuracy of the evaluation.
Another AI-based system, DeepGlioma, can detect genetic mutations in brain tumors in under 90 seconds. Developed by researchers at the University of Michigan, DeepGlioma uses a rapid, high-resolution optical imaging method called stimulated Raman histology to analyze tumor specimens. Todd Hollon, a neurosurgeon and senior author of the study, said that this technology “has the potential to change the field of neurosurgery by immediately improving comprehensive management of patients with diffuse gliomas.”
Future Directions and Clinical Validation
While these new technologies hold immense promise, they are still in the early stages of development and require further clinical validation before they can be widely adopted. The researchers behind the Mayo Clinic’s mass spectrometry platform are conducting more research to identify other molecular signatures in tumors that lack the IDH mutation and plan to broaden their discoveries to include other types of brain cancers. Similarly, the developers of CHARM are working to secure FDA approval for their AI tool.
The integration of these rapid diagnostic tools into routine surgical practice could represent a paradigm shift in the treatment of brain cancer. By providing surgeons with real-time, molecular-level information, these technologies have the potential to improve surgical outcomes, reduce the risk of recurrence, and pave the way for more effective, personalized therapies. As these systems continue to be refined and validated, they offer new hope to patients with this challenging disease.