Spectral CT Improves Image Quality, Reduces Radiation Exposure
Recent technological advances have contributed to the development of photon-counting detectors (PCD), which are now able to discriminate between photons based on energy level, providing information about the composition of an object in a single scan.
"PCDs are the next big thing in CT," said Radin A. Nasirudin, Dipl.-Ing, of the Department of Diagnostic and Interventional Radiology, Technische Universitat München, Munich, Germany, in a presentation Tuesday.
Incorporating photon-counting detector technology into CT—a technique called spectral CT—not only relays this additional information in a single scan, but due to quantum efficiency, noise can be drastically reduced. This means that better image quality can be achieved with lower radiation dose, Nasirudin said. "Current estimates on dose reduction suggest a decrease by a factor of two or more."
In his study, "Application of Photon-counting CT: Metal Artifact Reduction," Nasirudin and colleagues investigated the advantages this technique provides in reducing metal artifacts.
"Artifacts caused by metal objects are common and can significantly reduce the diagnostic quality in daily clinical practice," Nasirudin said. "Although there are many well-established methods for metal artifact reduction, most involve segmentation and thresholding for detection of the metal object, which is prone to reintroduce new artifacts."
With this in mind, Nasirudin and colleagues developed an algorithm—spectral-driven iterative reconstruction (SPIR)—that utilizes spectral information to reduce metal artifact in CT.
Researchers used a Monte Carlo simulator to simulate spectral CT projection data of a jaw phantom consisting of bone, soft tissue, teeth and gold implants. The resulting spectral projection data were decomposed to determine the spatial location and density of the gold. That information was then incorporated into a penalized maximum likelihood iterative reconstruction algorithm.
"The results from our investigation into the reduction of metal artifacts are promising," Nasirudin said. "The material decomposition technique is able to detect the metal implant from other components of the phantom." When compared to a known shape, the error from detecting the implant by material decomposition is less than 2 pixels, he said, which "strongly suggests" the technique is able to accurately detect the spatial location and density of any dental implant.
Use of the technique resulted in in a reduction of streaking artifacts without compromising any other anatomical information, Nasirudin said. When visually compared to other techniques like filtered-back projection or standard penalized maximum likelihood iterative reconstruction, "our method delivers superior image quality while preserving the details around the metal implant," he said.
It's significant that this technique seems to work well with any shape of dental implant, he said. For example, researchers first used the technique with a jaw phantom that had a circle-shaped metal implant, but later tested the algorithm with more realistic dental implants that produced images with high diagnostic quality.
In addition, he said the parameters for the iterative reconstruction (such as number of iterations and the strength of the penalty) didn't change from one shape to another, indicating that "our method can be extended to other parts of the body such as the lower extremity or the spine."
The study demonstrates that information provided by spectral CT "will be a central key to overcoming image quality issues in current clinical CT," Nasirudin said. "We foresee that the clinical introduction of spectral CT will lead to more clinically relevant applications while possibly reducing radiation exposure to the general population."