The collab seeks to use a portable, low-cost MRI scanner to increase access for neurology patients.
Photo/Thumb have been modified. Courtesy of Siarhei - stock.adobe.com.
MRI scans could soon be more accessible for patients in the hospital who cannot be transported, thanks to a collaboration announced today between the Yale School of Medicine and Hyperfine Research.
Hyperfine created a portable MRI device called Point-of-Care MRI, which can be moved directly to a patient’s bedside and operate in any healthcare setting, the company claims.
As part of a two-year study in conjunction with the American Heart Association, Yale New Haven Hospital in Connecticut deployed the Point-of-Care systems. The goal of the study is to overcome barriers that prevent the routine use of MRI on unstable neurology intensive care unit patients who cannot be transported.
Current MRI systems require a strict and limited access environment, mainly due to their design, said Kevin Sheth, M.D., a professor of neurology and neurosurgery at the Yale School of Medicine.
“I’m excited to be part of project that is finding a way to bring MRI to patients in a feasible, safe and efficient way,” Sheth said. “The availability and accessibility of a portable MRI scanner has allowed us to test some patients with multiple MRI exams over a time span of hours to days.”
Yale New Haven Hospital is testing the clinical workflow, user interface and image quality of the MRI system. The technology is being used to scan patients with known brain pathology, including hemorrhages, ischemic stroke, hematomas, tumors and edema. The hospital is also collecting anonymized versions of traditional MRI and CT scans of the same patients to compare.
Nearly 140 brain MRI exams of 123 patients have been taken so far.
“As Hyperfine’s first clinical partner, Yale is helping us to change how medicine is practiced with Point-of-Care MRI,” said Jonathan Rothberg, Ph.D., founder and chairman of Hyperfine Research. “Yale’s early experience with the system will guide us as we seek to revolutionize medical imaging by making MRI more accessible.”
The preliminary findings of the research will be announced in early 2020.
“This could open up a new level of access to the rich data MRI brings, and that could have a significant impact on how we care for patients,” Sheth concluded.
Get the best insights inside digital health directly to your inbox.
Machine Learning Analyzes MRI Scans 186-Times Faster than Humans
AI Accurately Detects Key Findings in Chest X-Rays in 10 Seconds