Researchers from Virginia Tech and GE Global Research Center are developing unusual cardiac computed tomography (CT) architectures and methods, including a newly patented approach to a long-standing challenge in local CT image reconstruction.
With funding from the National Institutes for Health (NIH), the research team will also evaluate the performance of various cardiac CT system designs to determine the most promising designs and demonstrate their clinical feasibility and utility.
Cardiovascular disease is the leading cause of death globally and a large burden on the healthcare system. Better detection of hardening or clogging of arteries and other blood vessels before symptoms occur is needed. Better image quality at lower radiation dose is the immediate need being addressed by the research project. The project is led by Ge Wang, director of the Biomedical Imaging Division of the Virginia Tech–Wake Forest School of Biomedical Engineering and Sciences, and Bruno De Man, a CT authority at GE Global Research Center.
Faster, dynamic imaging to capture the beating heart and algorithms or computations that can present the most exact images from X-ray projections are also among project goals. "Cardiac CT technology needs major improvements to capture a fast beating heart with better clarity at lower risk," says Wang.
In traditional X-ray CT imaging, data is recorded behind the patient. Everything is superimposed along the X-ray path through the patient. In other words, an X-ray projection of the heart includes the bone and muscle along the way to the detectors. With current CT, the X-rays probe the patient along multiple wide beams focused on the patient including a region of interest, such as the heart, from various orientations. That is, the source of the X-rays rotate around the individual as he or she lies inside a large aperture, then a computer program reconstructs images from the exposures.
This CT process increases radiation exposure but generates a lot of different views to be analyzed by physicians for diagnosis. In many cases, like cardiac CT, the area of interest is just a relatively small region within the larger body. "It was realized long before that one could reduce the radiation dose by sending X-rays just through the region of interest from different directions, and then reconstruct that region from resultant local data," says Wang.
Depending upon the algorithm used, the resulting images can, to different degrees, portray sharp borders or edges from tissue or bone within the region of interest but cannot show X-ray linear attenuation coefficients accurately. "This has been known for decades as the 'interior problem'," says Wang. A method known as lambda tomography addresses the interior problem by producing changes in the density of the image.
"However, physicians need quantitative images, and hence lambda tomography has not been clinically used," said Wang. His group at Virginia Tech, in collaboration with Professor Yangbo Ye at the University of Iowa, developed the now patented "interior tomography" method for interior reconstruction of a region of interest image to replace lambda tomography.
"We assume a known sub-region within the region of interest – such as an air gap, a blood area, or an implant in the heart. With a known sub-region, we can solve the interior problem in a theoretically exact and mathematically stable fashion – we can produce an accurate image!" says Wang.
Interior tomography is a theoretical breakthrough, and Wang and colleagues as well as peer groups have been developing it and publishing results. The patent application was filed in 2007.