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X-ray Approach To Track Surgical Devices And Minimize Radiation Exposure Devised By Researchers

April 16, 2013
Image Caption; This graphic illustrates a surgical tool in a human lung. The blue curve corresponds to what we expect the device to do. The green curve represents what would happen in a real procedure were some perturbations introduced. The red-dots represent the estimated shape based on where the new x-ray algorithm says the surgical tool actually is. Credit: Edgar Lobaton

North Carolina State University

Researchers from North Carolina State University and the University of North Carolina at Chapel Hill (UNC) have developed a new tool to help surgeons use X-rays to track devices used in “minimally invasive” surgical procedures while also limiting the patient´s exposure to radiation from the X-rays.

Many surgical procedures now use long, thin devices — such as “steerable needles” — that can be inserted into a patient´s body through a small incision and then steered to a target location. These “minimally invasive” procedures allow doctors to perform surgeries without having to make major incisions, which decreases the risk of infection and shortens the patient´s recovery time.

However, these techniques pose a challenge to surgeons, because it is difficult for them to determine precisely where the surgical device is in the patient´s body.

One solution to the problem is to use X-rays to track the progress of the surgical device in the patient. But doctors want to minimize the number of X-rays taken, in order to limit the patient´s exposure to radiation.

“We have now developed an algorithm to determine the fewest number of X-rays that need to be taken, as well as what angles they need to be taken from, in order to give surgeons the information they need on a surgical device´s location in the body,” says Dr. Edgar Lobaton, an assistant professor of electrical and computer engineering at NC State and lead author of a paper on the research.

The new tool is a computer program that allows surgeons to enter what type of procedure they´ll be performing and how precise they need the location data to be. Those variables are then plugged into the algorithm developed by the research team, which tells the surgeon how many X-rays will be needed — and from which angles — to produce the necessary location details.

For example, if a surgeon needs only a fairly general idea of where a device is located, only two or three X-rays may be needed — whereas more X-rays would be required if the surgeon needs extremely precise location data.

The paper, “Continuous Shape Estimation of Continuum Robots Using X-ray Images,” will be presented at the IEEE International Conference on Robotics and Automation, being held in Karlsruhe, Germany, May 6-10. The paper was co-authored by Jingua Fu, a former graduate student at UNC; Luis Torres, a Ph.D. student at UNC; and Dr. Ron Alterovitz, an assistant professor of computer science at UNC. The research was supported by the National Science Foundation and the National Institutes of Health.

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Source: North Carolina State University



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