MR angiography may be years away from competing effectively with x-ray coronary angiography, but the methods that might one day reach that level of performance are taking shape today. One of the most promising is self-navigated MRA, a process that
MR angiography may be years away from competing effectively with x-ray coronary angiography, but the methods that might one day reach that level of performance are taking shape today. One of the most promising is self-navigated MRA, a process that incorporates both breath-hold and free-breathing data sets.
Researchers at GE and Brigham and Women’s Hospital in Boston have compiled and are testing an algorithm that compares and averages these data sets. The result is an increased signal-to-noise ratio and improved image quality. Resolution with the new technique approaches 0.5 mm in-plane and 2 mm through-plane, according to Christopher J. Hardy, a physicist at GE’s corporate R&D center.
“Coronary angio is a projection technique, so you could argue that it has very poor through-plane resolution but, of course, very good in-plane resolution,” Hardy said. “While I think it is going to be a stretch to actually match the resolution of coronary angio in-plane, I think we can get close.”
Hardy believes self-navigated coronary artery MRA could provide the means for getting there. The technique is really a hybrid of existing breath-hold and free-breathing methods. Self-navigation overcomes or mitigates problems encountered in the other two. Breath-hold MR coronary angio typically achieves a low signal-to-noise ratio because of the brief time during which data can be collected. Images generated from data averaged over multiple breath-holds are impaired by the varying positions of the patient’s diaphragm. Collecting free-breathing data using respiratory navigation may not provide reproducible results because breathing patterns may be irregular.
The method being developed at GE first acquires a reference data set of coronary artery images during a 16-second breath-hold. The arteries are then sampled repeatedly with the patient breathing normally and the resulting data are compared with the breath-hold data set. A specific number of averages is cranked into the algorithm, which calculates a final image based on the free-breathing data that most closely match the corresponding reference data set.
As seen in tests on normal volunteers, ghosting and blurring that appear in free-breathing images disappear when best-match averaging is done. Hardy noted, however, that when more than a third of the images are averaged, blurring returns. The severity of the problem increases with the addition of more images beyond the one-third proportion.
The next step is to build the algorithm into a real-time imaging system that will allow image quality to be monitored throughout the process. Doing so will require hardware as well as software enhancements. Currently the calculations take several minutes to generate images, according to Hardy.
“If we go to special hardware, we could do much better,” he said. The development process, however, will be time-consuming. Hardy believes that technology capable of quickly delivering clinical results comparable to those of x-ray-based coronary angiography is still a long way off. “I think within four or five years, we may have something,” he said.