November 2, 2015

Technique distinguishes brain tumors at the margins

At a Glance

  • An experimental technique is proving effective at distinguishing the margins of growing tumors in human brain and spinal tissue.
  • With further improvement, the approach might one day be used in the clinic to help guide more precise and effective tumor surgeries.
Brain tissue.
Brain tumor tissue with cells in a disordered pattern. SRS microscope images, with lipid in green and protein in blue. Normal brain contains sparse cells with bundles of nerve fibers, called axons (top), but brain tumor tissue is full of cells in a disordered pattern (bottom). These are difficult to differentiate during surgery, making it hard for a surgeon to know where the tumor stops.University of Michigan Health System

Recognizing where tumors end and normal brain tissue begins is a major challenge during surgery. Removing healthy tissue can cause neurologic problems, but leaving tumor tissue behind can allow the cancer to spread again.

Researchers have been testing different ways to tell the difference between tumors and normal tissue during surgery. One promising approach is called stimulated Raman scattering (SRS) microscopy. Certain chemical bonds in molecules can produce unique patterns of scattered light called Raman spectra. Shining lasers on tissues can excite particular Raman frequencies without causing harm. The weak light signals the tissues emit depend on their mix of molecules, such as lipids and proteins. SRS microscopy could potentially be used to generate images during surgery, eliminating the time-consuming process of removing and then analyzing the tissue.

In past work, an NIH-funded research team led by Dr. Sunney Xie at Harvard University and Dr. Daniel Orringer at the University of Michigan Medical School showed that SRS microscopy could recognize the difference between tumors and normal brain tissue in living mice. It could also be used in excised surgical samples to detect human glioblastoma, a diffuse form of malignant brain cancer for which tumor margins can’t be easily discerned.

In their latest study, the researchers evaluated the ability of SRS microscopy to detect tumor infiltration in tissue samples from 22 people with a range of brain and spinal tumors. The scientists collected SRS images at 2 Raman frequencies selected to detect proteins and lipids. For comparison, they froze the samples and stained them with hematoxylin and eosin (H&E), the current approach used to diagnose brain tumors. The work appeared on October 14, 2015, in Science Translational Medicine.

The group had neuropathologists rate 75 SRS images and 75 similar H&E images. They found the techniques were equally effective at detecting tumor infiltration.

The team next set out to create an automated method to detect tumor infiltration during surgery. They built a program that quantified the number of cell nuclei, density of nerve cells, and protein/lipid ratio in each image based on the SRS imaging data. The resulting “classifier” program consistently agreed with pathologists in distinguishing tumor-infiltrated brain tissue.

The team also showed that SRS microscopy could detect tumor infiltration up to 10 mm beyond the gross margin of a glioblastoma tumor, where it would be undetectable to a surgeon.

“The ability to determine tumor margins without having to send samples to a pathologist could increase patient safety and improve outcomes by shortening the length of surgeries and reducing the number of cases where cancer cells are left behind,” says Dr. Richard Conroy of NIH’s National Institute of Biomedical Imaging and Bioengineering (NIBIB), which helped fund the study.

The researchers are now working to develop methods for using SRS microscopes in the operating room to improve the accuracy and safety of brain tumor surgery.

 —by Harrison Wein, Ph.D.

Related Links

References: Detection of human brain tumor infiltration with quantitative stimulated Raman scattering microscopy. Ji M, Lewis S, Camelo-Piragua S, Ramkissoon SH, Snuderl M, Venneti S, Fisher-Hubbard A, Garrard M, Fu D, Wang AC, Heth JA, Maher CO, Sanai N, Johnson TD, Freudiger CW, Sagher O, Xie XS, Orringer DA. Sci Transl Med. 2015 Oct 14;7(309):309ra163. doi: 10.1126/scitranslmed.aab0195. PMID: 26468325.

Funding: NIH’s National Institute of Biomedical Imaging and Bioengineering (NIBIB), National Cancer Institute (NCI), National Institute of Neurologic Disorders and Stroke (NINDS), and Director's Transformative Research Award Program; American Association of Neurological Surgeons NREF Young Clinician Investigator Award; and Michigan Institute for Clinical and Health Research.