As artificial intelligence (AI) becomes more widely utilized in radiology, experts warn that it is critical to examine the environmental impact of AI tools, according to a focus article published today in Radiology, a magazine of the Radiological Society of North America.
Health care and medical imaging make a major contribution to the greenhouse gas (GHG) emissions that drive global climate change. AI tools can improve radiology practice and sustainability by optimizing imaging processes, resulting in shorter scan times, increasing scheduling efficiency to save patient travel, and integrating decision-support systems to reduce low-value imaging. However, there is a drawback to AI usage.
“Medical imaging generates a lot of greenhouse gas emissions, but we often don’t think about the environmental impact of associated data storage and AI tools,” said Kate Hanneman, M.D., M.P.H., vice chair of research and associate professor at the University of Toronto and deputy lead of sustainability at the Joint Department of Medical Imaging, Toronto General Hospital. “The development and deployment of AI models consume large amounts of energy, and the data storage needs in medical imaging and AI are growing exponentially.”
Medical imaging generates a lot of greenhouse gas emissions, but we often don’t think about the environmental impact of associated data storage and AI tools. The development and deployment of AI models consume large amounts of energy, and the data storage needs in medical imaging and AI are growing exponentially.
Kate Hanneman
Dr. Hanneman and a team of experts investigated the advantages and disadvantages of adding AI techniques into radiology. AI has the ability to improve workflows, faster image acquisition, lower costs, and enhance the patient experience. However, the energy necessary to create AI tools and store the accompanying data has a considerable impact on GHG.
“We need to do a balancing act, bridging to the positive effects while minimizing the negative impacts,” says Dr. Hanneman. “Improving patient outcomes is our ultimate goal, but we want to do that while using less energy and generating less waste.”
Developing AI models requires large amounts of training data that health care institutions must store along with the billions of medical images generated annually. Many health systems use cloud storage, meaning the data is stored off-site and accessed electronically when needed.
“Even though we call it cloud storage, data are physically housed in centers that typically require large amounts of energy to power and cool,” Dr. Hanneman said. “Recent estimates suggest that the total global GHG emissions from all data centers is greater than the airline industry, which is absolutely staggering.”
A data center’s location has a significant impact on its sustainability, particularly if it is in a colder environment or near renewable energy sources. To reduce the overall environmental impact of data storage, the researchers suggested sharing resources and, where appropriate, cooperating with other providers and partners to spread the energy used more widely.
The researchers also suggested various ways to reduce GHG emissions from data storage and the AI model creation process. These included looking into computationally efficient AI algorithms, choosing hardware that uses less energy, applying data compression techniques, deleting redundant data, developing tiered storage systems, and collaborating with renewable energy suppliers.
“Departments that manage their cloud storage can take immediate action by choosing a sustainable partner,” she suggested.
Dr. Hanneman stated that, while hurdles and information gaps still exist, such as poor data on radiology-specific GHG emissions, resource limits, and complex laws, she expects that sustainability will become a quality metric in the decision-making process for AI and radiology.
“Environmental costs should be considered along with financial costs in health care and medical imaging,” she told the audience. “I believe AI can help us improve sustainability if we use the tools wisely.” We only need to be cautious and conscious of its energy use and GHG emissions.
