Researchers from the University of Houston have developed a concept for MRI-powered millimeter-size “millirobots” that could one day perform unprecedented minimally invasive medical treatments.
This technology could be used to treat hydrocephalus, for example. Current treatments require drilling through the skull to implant pressure-relieving shunts, said Aaron T. Becker, assistant professor of electrical and computer engineering at the University of Houston.
But MRI scanners alone don’t produce enough force to pierce tissues (or insert needles). So the researchers drew upon the principle of the “Gauss gun.”
Here’s how the a Gauss gun works: a single steel ball rolls down a chamber, setting off a chain reaction when it smashes into the next ball, etc., until the last ball flies forward, moving much more quickly the initial ball.
Based on that concept, the researchers imagine a medical robot with a barrel self-assembled from three small high-impact 3D-printed plastic components, with slender titanium rod spacers separating two steel balls.
Aaron T. Becker, assistant professor of electrical and computer engineering at the University of Houston, said the potential technology could be used to treat hydrocephalus and other conditions, allowing surgeons to avoid current treatments that require cutting through the skull to implant pressure-relieving shunts.
Becker was first author of a paper presented at ICRA, the conference of the IEEE Robotics and Automation Society, nominated for best conference paper and best medical robotics paper.
“Hydrocephalus, among other conditions, is a candidate for correction by our millirobots because the ventricles are fluid-filled and connect to the spinal canal,” Becker said. “Our noninvasive approach would eventually require simply a hypodermic needle or lumbar puncture to introduce the components into the spinal canal, and the components could be steered out of the body afterwards.”
Future work will focus on exploring clinical context, miniaturizing the device, and optimizing material selection.
Image and article via Kurzweilai