Epidurals are generally very safe, but with the five layers of tissue through which the needle must pass, there is some opportunity for things to go awry. MIT scientists may be bringing a new level of precision to such medical procedures, developing an optical sensor that can be embedded into the tip of a needle to give anesthesiologists immediate feedback on the surrounding tissue and ensure they hit the right spot.
While more than 13 million epidurals are performed in the US each year, the epidural space surrounding the spinal cord — the target area for these pain-blocking procedures — is not so easy to get to. Anesthesiologists need to pass a four-to-six-inch needle (10-15 cm) through five layers made up of skin, fat, and three kinds of ligament in order to reach the area.
At present, anesthesiologists "blindly" feel for changes in resistance between the layers of tissue as a guide to determine when the needle hits the right spot. Most of the time, this plays out without a problem, but sometimes a patient's tissue might differ from the norm, which makes things a little trickier.
In up to 10 percent of cases, the needles are inserted too deeply or into the wrong tissue and hit the dura mater, a membrane surrounding the spinal cord and cerebrospinal fluid. These outcomes can result in complications that include reduced effectiveness of the drug, severe headaches and sometimes, a stroke or spinal injury.
Looking to reduce the risks, MIT scientists have been working to develop an optical sensor that would inform the anesthesiologist of the whereabouts of the needle as it is guided through the body. This involved testing various technologies including fluorescence and reflectance spectroscopy, but it was a technique relying on Raman spectroscopy that has brought about their promising breakthrough.
Raman spectroscopy relies on scattered light, typically from a laser in the visible, near-infrared or near-ultraviolet range to track energy shifts in molecular vibrations of a sample and reveal clues about its chemical composition. It has been used before for purposes ranging from the analysis of artwork to identifying ingredients in pharmaceuticals, but MIT scientists are now discovering its potential when it comes to the human body.
"In MIT Laser Biomedical Research Center, we have advanced the techniques to solve biomedical problems," MIT research scientist Jeon Woong Kang explained to New Atlas. "For example, we have developed spectroscopic cancer diagnosis, atherosclerosis detection, non-invasive transdermal glucose monitoring and so on."
The team embedded a Raman spectroscopy sensor inside a needle tip and tested it in pig tissue. The sensor collected Raman signals to measure the concentration of proteins such as albumin, actin and collagen and distinguished between eight different tissue layers around the epidural space with 100 percent accuracy. In contrast, fluorescence and reflectance spectroscopy were able to identify some, but not all eight of the layers.
"The sensor is continuously measuring Raman spectroscopy signals, which tells you the chemical composition of the tissue," says Kang. "From the chemical composition you can identify all tissue layers, from skin to spinal cord."
The sensor still requires some further development before it enters clinical use. For a start, it is too big to fit inside the needles normally used for epidural procedures, so the team is working to reduce its diameter from the 2 mm it currently measures down to 0.5 mm. There is also the question of how the feedback would best be delivered to anesthesiologists, something Kang tells us they are currently exploring.
"We did not finalize the feedback yet," he says. "We're running surveys and collecting clinicians' opinions. Two of the most common preferences include display and sound."
Eventually, the team believes the technology could not just improve the safety of epidurals, but other medical procedures where accuracy is paramount, such as injecting drugs into joints and cancer biopsies.
The research was published in the journal Anesthesiology.
Source: MIT
