Algorithm Improves MRI Interpretation
An improved algorithm can dramatically enhance the capture and interpretation of full-body MRIs, particularly in the abdominal region, according to a new study slated for presentation Thursday at the annual meeting of the American Roentgen Ray Society (ARRS) in Chicago.
Motion artifacts in MRIs, such as patient movement, often appear as ghosting artifacts that may obscure clinical information, says Candice Bookwalter, MD, PhD, presenting author for the study.
“Almost every acquisition during an MR abdominal exam requires a breath-hold to limit motion,” Bookwalter explains. “For example, a routine liver exam includes at least nine breath-holds. Even with fast imaging techniques, these breath holds are often long and difficult for patients, and failed breath holds are almost always identified only after image acquisition. This is particularly problematic in timed post-contrast imaging.”
With this in mind, Bookwalter and her team developed the Motion Artifact Removal by Retrospective Resolution Reduction (MARs) algorithm to identify the transition between breath-holds and free breathing. This allows for better retrospective reviews of images and reduces the need for additional imaging. “MARs detected and removed motion corrupted data automatically in our asymptomatic volunteers and patients, which improved the overall image quality,” Bookwalter observes.
In a study performed at the University Hospital at Case Medical Center, Case Western Reserve University, Bookwalter and her colleagues successfully demonstrated how the MARs technique permits radiologists and technicians to create clinically useful images, even in the presence of motion. She believes the algorithm will prove to be a useful tool for image interpretation.
“The MARs algorithm requires very little alteration of the clinical MR protocol,” she concludes. “We envision the final application of this technique to be completely automatic and likely applied by the clinical technologist prior to presentation to the radiologist.”