Case Western Reserve University to Develop Enhanced Medical Imaging AI
New four-year, $1.1 million project aims to build an AI alternative to traditional medical imaging processes that rely on chemical “contrast agents.”
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By - Researchers at Case Western Reserve University have received a four-year, $1.1 million grant from the National Science Foundation (NSF) to develop an artificial intelligence (AI) approach to make medical imaging more safe and efficient.
Current medical imaging processes for computed tomography (CT), magnetic resonance imaging (MRI), and X-rays rely on the use of chemical “contrast agents” to improve diagnostic accuracy.
However, these agents are often cost- and resource-intensive to use, and they can lead to potential side effects like allergic reactions. With increasing numbers of patients needing to undergo medical imaging, addressing these concerns will play a key role in maintaining care quality.
The development of a non-chemical imaging technique may help tackle these hurdles while also easing the burden of supply chain issues, such as the pandemic-era shortage of iodinated contrast media (ICM) and the global helium shortage.
Case Western Reserve University research teams will leverage their NSF funding to build an AI approach that is safer, quicker, and cheaper than traditional imaging methods by utilizing only non-contrast images.
The project is set to explore a novel category of image features that can be used to develop and validate new models for use with MRI scans. In doing so, the researchers hope to design an “AI contrast agent.”
“With this grant, our multidisciplinary team aims to improve the medical-imaging process for clinical staff and patients,” said project leader Shuo Li, PhD, an associate professor of biomedical engineering and computer data science at the university’s Case School of Engineering, in the news release. “Virtual contrast-enhanced imaging could save time and money while continuing to provide the best care to patients.”
The grant funding is supported by the NSF Smart Health and Biomedical Research in the Era of Artificial Intelligence and Advanced Data Science, a program designed to bolster biomedical and public health advances in computer and information science, behavioral and cognitive research, mathematics, statistics, and engineering.
This research reflects a broader interest in using AI to improve medical imaging. The global AI-enabled medical imaging market size was estimated at USD 762.84 million in 2022 and is expected to grow to USD 14,271.80 million by 2032, according to a recent report from Precedence Research.
This year, startups are capitalizing on this boom and moving to tackle current limitations in medical imaging as the radiology landscape shifts to accommodate new AI technologies aimed at transforming medical screenings, precision medicine, and patient risk assessment.
