4072 - Spinal Injury Imaging by Nano-Robots

Description:
  • Spinal cord and nerve cell injuries
  • Drug delivery
  • Lab automation

Abstract

USC researchers have developed a technique to locate and heal spinal cord and nerve injuries at the cell level. A swarm of nano- or micron-scale robots with high sensitivity chemical sensors are delivered to the suspected injury area. These robots capture the chemical signature of injured spinal cells, and the grouping of robots around the injured cells generates imaging signals detectable by X-ray. This technique avoids the limitations of traditional methods as it uses both chemical sensors and X-ray technology to accurately guide the robots to the injured area. The robots can also carry particles or compounds for repairing the injury.

Benefit

  •  Accurately locates spinal cord and nerve cell injuries
  • Repairs spinal cord and nerve injuries at the cell level
  • Accurately delivers drugs to injured area

Market Application

There are approximately 17,000 new spinal cord injuries each year. To avoid paralysis, doctors must precisely locate the injured area — but traditional techniques often fail to accurately localize injuries, and their results are difficult to analyze. In worst-case scenarios, patients’ may be under-treated, and their risk of paralysis could be increased. Given the prevalence and severity of spinal cord injuries, a technique is needed to accurately locate the injured area and collect easy-to-analyze signals.

Publications

Magnetically Levitated Nano-Robots: An Application to Visualization of Nerve Cells Injuries, Medicine Meets Virtual Reality 15, J.D. Westwood et al. (Eds.) IOS Press 2007

Other

Stage of Development

  • Experimentally validated
  • Available for exclusive and non-exclusive license

Patent Information:

  • Title: Spinal Injury Imaging by Magnetically Levitated sensors
  • App Type: Utility
  • Country: United States
  • Serial No.: 12/273,354
  • Patent No.: 8,200,310
  • File Date: 11/18/2008
  • Issued Date: 6/12/2012
  • Expire Date: 1/18/2030
  • Patent Status: Patent Issued