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Pen-like instrument detects cancer in mere seconds

The instrument developed at UT Austin is claimed to be both much quicker and more accurate at detecting cancer than existing approaches(Credit: University of Texas at Austin)

Distinguishing cancerous tissue from healthy tissue is a chief concern when it comes to surgery, which is why medical scientists are continually looking at new technologies to help surgeons sort the good from the bad. Over the years, we’ve seen research advances in the form of glowing compounds that light up cancerous cells and smart scalpels that offer visual and audio guidance. Now researchers at the University of Texas (UT) at Austin have developed a pen-like device that identifies cancerous tissue during surgery, boosting the chances of a successful procedure.

“If you talk to cancer patients after surgery, one of the first things many will say is ‘I hope the surgeon got all the cancer out,'” says Livia Schiavinato Eberlin, an assistant professor of chemistry at UT Austin who led the team. “It’s just heartbreaking when that’s not the case. But our technology could vastly improve the odds that surgeons really do remove every last trace of cancer during surgery.”

Telling cancerous tissue apart from healthy tissue is key during surgery, and not just to ensure that all the tumor is removed. Taking too much healthy tissue can also be dangerous, raising the prospect of damage to muscle and nerve function, along with other painful side effects.

Currently, the state-of-the-art method surgeons use to differentiate cancer and healthy tissues is called Frozen Section Analysis. The downside to this approach is that it requires a sample to be prepared and assessed by a pathologist, which can take more than 30 minutes and leaves the patient exposed to increased risk of infection. Furthermore, it can prove unreliable in as many as 10 to 20 percent of cases.

The instrument developed at UT Austin is claimed to be both much quicker and more accurate than current approaches. Called the MasSpec Pen, it works by detecting the biomarkers of certain types of cancer, using software to check them against a catalog of 253 samples comprising both healthy and cancerous tissues of the breast, lung, thyroid and ovary.

“Cancer cells have dysregulated metabolism as they’re growing out of control,” says Eberlin. “Because the metabolites in cancer and normal cells are so different, we extract and analyze them with the MasSpec Pen to obtain a molecular fingerprint of the tissue. What is incredible is that through this simple and gentle chemical process, the MasSpec Pen rapidly provides diagnostic molecular information without causing tissue damage.”

The pen simply needs to be held against the tissue while a foot pedal is used to kick off the process. This sees a drop of water fall onto the tissue, allowing small molecules to be absorbed into the liquid. This water is then fed into a mass spectrometer, an instrument with the ability to detect thousands of molecules and interpret the molecular fingerprints of various cancers.

Once this analysis is completed, a connected computer screen will automatically display “Normal” or “Cancer” within about 10 seconds, and for certain cancers, will even name the subtype, such as “lung cancer,” for example. When testing the MasSpec Pen on 253 tissue samples taken from cancer patients, it proved more than 96 percent accurate and was also able to detect cancer in marginal areas between normal and cancerous tissue.

“Any time we can offer the patient a more precise surgery, a quicker surgery or a safer surgery, that’s something we want to do,” says James Suliburk, head of endocrine surgery at Baylor College of Medicine and a collaborator on the project. “This technology does all three. It allows us to be much more precise in what tissue we remove and what we leave behind.”

The team has filed patents for the technology, and expects to start testing it during oncologic surgeries in 2018. A paper describing the research was published in Science Translational Medicine, while the video below provides an overview of how it works.

Source: University of Texas at Austin


Henry Sapiecha

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