GE Healthcare, Fujitsu to develop AI to help spot brain aneurysms

head and brain
A new collaboration between GE Healthcare and Fujitsu will include a surgical tool for planning stent interventions, using fluid modeling to predict the risk of aneurysm rupture. (Image credit: American Heart Association)

GE Healthcare signed on to a new Australian research collaboration to develop artificial intelligence tools to quickly and automatically diagnose brain aneurysms.

GE will be contributing its Revolution CT scanners to the “co-creation” effort. The project is being led by the Australian division of Fujitsu, the Tokyo-based IT services firm, which will focus on developing the AI and digital solutions. Additionally, Sydney’s Macquarie University and Macquarie Medical Imaging will provide clinical expertise for the product’s development and testing.

The group hopes to offer a commercial solution to radiology practices in Australia before going worldwide. The project has also received a grant from the Australian government of $2.1 million AUD, or about $1.4 million.

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“As the consequences of brain aneurysm rupture are often fatal, effective and expedient detection is crucial,” Matt Tucker, president and CEO of GE Healthcare Australia & New Zealand, said in a statement. “Unfortunately screening and monitoring takes time and specialist expertise not afforded by every radiology practice.”

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The AI algorithm will be trained to look for abnormalities within the brain including in blood vessels within the circle of Willis, the arterial ring at the base of the brain. The system also will be designed to help track and monitor aneurysms over the long term.

An additional focus of the project will include a surgical planning tool for intervention with a stent, applying fluid modeling to predict the risk of rupturing the aneurysm.

“This is an amazing opportunity to be able to address the problem of the rapid and accurate diagnosis of brain aneurysms,” said John Magnussen, a diagnostic and interventional radiologist at Macquarie Medical Imaging.

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“Even in ideal circumstances, detecting brain aneurysms is time and expertise intensive and missed aneurysms can have terrible outcomes,” Magnussen added. “By creating an AI assistant to automatically flag potential aneurysms and allow for accurate follow-up, we can make a huge difference to patient care.”

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