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A GPS for Brain Surgery

By Joe Sugarman
Illustration of a brain with electrical pulses going through it
Xingde Li is a professor of biomedical engineering and electrical and computer engineering at the Johns Hopkins Whiting School of Engineering.
Operating on the brain is an exact science with little room for error, yet surgeons tasked with removing cancerous tumors walk a fine line: Remove more than just the tumor and the patient could suffer permanent brain damage; don’t remove enough and the cancer could come back. 
Now a multidisciplinary team of researchers at Johns Hopkins has developed a new technology that allows surgeons to distinguish cancerous tumors in the brain from healthy tissue via simple color-coded maps. During surgeries, doctors will have a constantly updated picture of what to remove and what to leave untouched.
“I don’t think there is anything out there in the market or in other research efforts that matches what we’re doing already—which is being able to clearly see fingers of cancer cells in the brain,” says Alfredo Quiñones-Hinojosa, a professor of neurosurgery, neuroscience, and oncology at the Johns Hopkins School of Medicine and the clinical leader of the research team. “It will enable us to do much better surgeries. There is nothing out there like it.”
The technology is called optical coherence tomography, and it has been around since the early 1990s for use in imaging transparent tissue like the human retina. OCT works much like ultrasound, where sound waves are bounced off an object to determine its location and size, but this technique utilizes infrared light waves instead. Work by Xingde Li, a professor of biomedical engineering and the engineering leader of the research team, and Carmen Kut, an MD/PhD student working in Li’s lab, has advanced the technology to be used for imaging nontransparent tissue like the brain. And while other labs around the world are working on similar technologies, the Hopkins team has pioneered a way to recognize the signature of cancer cells in the brain and simultaneously color-code them on a monitor as red, while representing normal cells in green. A prototype of the device has been tested with surprising clarity on mouse brains impregnated with cancer cells and human brain tissue removed during surgeries. 
“The resolution is amazing,” says Quiñones-Hinojosa. “It’s like if you look at a Google map of the Earth from space, you see the water and the land. An MRI (which surgeons currently use to image the brain) allows you to distinguish that. But if you want to see what the roof of a building at Johns Hopkins looks like, you really have to zoom in. That’s what OCT allows you to do. You really get that level of detail.” 
Li says the technology also improves on a traditional MRI in that OCT can be employed by surgeons in real time during an operation; it doesn’t emit harmful radiation like X-rays, CT scans, or PET scans; and it will likely cost several hundred thousand dollars versus several million for an MRI machine. Plus, Li says, “it’s small enough to put the whole system in a suitcase.”
Researchers say the technology can also potentially be used in diagnosing disease and guiding biopsies with unprecedented accuracy. The instrument’s imaging probe can be designed to be as small as half a millimeter, meaning it could be used to capture images within tiny tributaries in the cardiovascular system and digestive tract. 
For now, Li says his team is working on improving the imaging speed of the technology as well as developing an improved light source. Clinical trials are scheduled to begin over the next several months. Quiñones-Hinojosa can’t wait to utilize the technology in his operating room. “With this tool, we will be able to see things in surgery that we were not able to see before. It will enable us to take out more tumor and therefore help our patients even more.”  
Abstract illustration of a man's head with a target in front
Tom Jay

The Hopkins team has pioneered a way to recognize the signature of cancer cells in the brain and simultaneously color-code them on a monitor as red, while representing normal cells in green.

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