Not a toy (anymore): Video game tech to support CT dose software

Researchers at Rensselaer Polytechnic Institute (RPI) in Troy, N.Y., are beginning work to develop a technique to accurately calculate radiation exposure from CT scans by leveraging computer graphics cards similar to the type used in the video game industry.

The $2.6 million study, funded by a grant from the National Institute of Biomedical Imaging and Bioengineering (NIBIB), will focus on new Monte Carlo simulation software to be run on NVIDIA video cards. Monte Carlo is a simulation originally developed as an outgrowth of nuclear weapons research in the 1940s, and is the only computational method to provide accurate dose estimate results for non-uniform 3D subjects like the human body, according to a press release from RPI.

Currently, the widespread use of the Monte Carlo calculation is severely limited because of the 10-hour calculation time required by standard desktop computers. Researchers hope that by running the software on graphic processing units (GPUs), calculation time can be cut to less than 60 seconds, according to X. George Xu, PhD, professor and head of the nuclear engineering program at RPI, who is leading the research.

“With this new study, we hope to bring massively parallel computing power—currently available only to national laboratories and major research universities such as Rensselaer—to busy and resource-limited hospitals,” said Xu in the release. “There is a high level of interest at the national level to quantify and reduce the amount of ionizing radiation involved in medical imaging. Our parallel computing method has the potential to be used in everyday clinical procedures, which would dramatically decrease the amount of radiation we receive from CT scans.”

Xu has already spent nearly a decade developing software that uses highly realistic 3D virtual reality models, or computational phantoms, to calculate the exact amount of radiation a specific organ will receive from a CT scan. Since GPUs are based on stream processing, which allows for efficient parallel processing, the software can run quickly on a small number of connected video cards. Preliminary results from the research team have shown that a single $2,000 GPU card can perform as fast as a 1,000-CPU cluster using existing Monte Carlo code, according to RPI.

Once developed and validated, the researchers will evaluate the clinical benefit of the technology using typical diagnostic CT scanning protocols of the head, chest and abdomen from Massachusetts General Hospital (MGH) in Boston.

In addition to RPI and MGH, GE Global Research and Los Alamos National Lab in New Mexico are also partners in the research.