AAPM: Video game processors help reduce CT rad dose
A reconstruction algorithm based on graphic processing unit (GPU) platforms originally designed for 3D video games could yield a 10-fold reduction in the amount of radiation patients receive during cone-beam CT scans, according to a study presented at the annual meeting of the American Association of Physicists in Medicine (AAPM) on July 21.
Cone-beam CT is associated with fairly high cumulative radiation dose when multiple studies are acquired as part of an image-guided radiation therapy (IGRT) protocol .
Reducing the total number of x-ray projections and the mAs level per projection during a CT scan can help minimize patient's exposure to radiation, but the change results in noisy, mathematically incomplete data that takes hours to process using current iterative reconstruction approaches. Because cone-beam CT is mainly used for treatment setup while patients are in the treatment position, fast reconstruction is a requirement, explained the study's lead author Xun Jia, a postdoctoral fellow at University of California, San Diego.
Jia and colleagues set out to develop a fast GPU-based algorithm to reconstruct cone-beam CT images from undersampled and noisy projection data to lower the radiation dose. They developed a CT reconstruction algorithm for GPU platforms that processes data in parallel to increase efficiency and enable CBCT reconstruction in about two minutes. Phantom studies indicated cone-beam CT reconstruction image quality sufficient for IGRT with 20 to 40 x-ray projections and 0.1 mAs per projection compared to current protocols that require 360 projections with 0.4 mAs per projection.
The new method resulted in 36 to 72 times less radiation exposure for patients, said Jia, and reconstruction time ranged from 77 seconds to 130 seconds, which Jia estimated to be 100 times faster than similar iterative reconstruction approaches.
“With our technique, we can reconstruct cone-beam CT images with only a few projections--40 in most cases--and lower mAs levels,” summed Jia. The technique delivers computational efficiency to make the iterative cone-beam CT reconstruction approach applicable in clinical environments.
The technique may have wider applications. “The most interesting and compelling possibilities of this technique are beyond cancer radiotherapy,” noted the study's senior author Steve B. Jiang, PhD, an associate professor of radiation oncology at University of California, San Diego. “Our work, when extended from cancer radiotherapy to general diagnostic imaging, may provide a unique solution to solve [radiation dose concerns] by reducing the CT dose per scan by a factor of 10 or more,” he stated.
Cone-beam CT is associated with fairly high cumulative radiation dose when multiple studies are acquired as part of an image-guided radiation therapy (IGRT) protocol .
Reducing the total number of x-ray projections and the mAs level per projection during a CT scan can help minimize patient's exposure to radiation, but the change results in noisy, mathematically incomplete data that takes hours to process using current iterative reconstruction approaches. Because cone-beam CT is mainly used for treatment setup while patients are in the treatment position, fast reconstruction is a requirement, explained the study's lead author Xun Jia, a postdoctoral fellow at University of California, San Diego.
Jia and colleagues set out to develop a fast GPU-based algorithm to reconstruct cone-beam CT images from undersampled and noisy projection data to lower the radiation dose. They developed a CT reconstruction algorithm for GPU platforms that processes data in parallel to increase efficiency and enable CBCT reconstruction in about two minutes. Phantom studies indicated cone-beam CT reconstruction image quality sufficient for IGRT with 20 to 40 x-ray projections and 0.1 mAs per projection compared to current protocols that require 360 projections with 0.4 mAs per projection.
The new method resulted in 36 to 72 times less radiation exposure for patients, said Jia, and reconstruction time ranged from 77 seconds to 130 seconds, which Jia estimated to be 100 times faster than similar iterative reconstruction approaches.
“With our technique, we can reconstruct cone-beam CT images with only a few projections--40 in most cases--and lower mAs levels,” summed Jia. The technique delivers computational efficiency to make the iterative cone-beam CT reconstruction approach applicable in clinical environments.
The technique may have wider applications. “The most interesting and compelling possibilities of this technique are beyond cancer radiotherapy,” noted the study's senior author Steve B. Jiang, PhD, an associate professor of radiation oncology at University of California, San Diego. “Our work, when extended from cancer radiotherapy to general diagnostic imaging, may provide a unique solution to solve [radiation dose concerns] by reducing the CT dose per scan by a factor of 10 or more,” he stated.