A new way to process X-ray data can help reduce the amount of radiation patients receive during cone beam CT scans.
Cone beam CT plays an essential role in image-guided radiation therapy (IGRT), a state-of-the-art cancer treatment. IGRT uses repeated scans during a course of radiation therapy to precisely target tumors and minimize radiation damage in surrounding tissue. Though IGRT has improved outcomes, the large cumulative radiation dose from the repeated scans has raised concerns among physicians and patients.
Reducing the total number of X-ray projections and the mAs level per projection (by tuning down the X-ray generator pulse rate, pulse duration and/or current) 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 the current iterative reconstruction approaches. Because CBCT is mainly used for treatment setup while patients are in the treatment position, fast reconstruction is a requirement, explains lead author Xun Jia, a UCSD postdoctoral fellow.
Based on recent advances in the field of compressed sensing, Jia and his colleagues developed an innovative CT reconstruction algorithm for graphic processing unit (GPU) platforms. The GPU processes data in parallel -- increasing computational efficiency and making it possible to reconstruct a cone beam CT scan in about two minutes. (Modern GPU cards were originally designed to power 3D computer graphics, especially for video games.)