First cleared by the FDA almost one year ago, Hyperfine’s Swoop system is designed to scan the heads of people ages two and older, while weighing about one-tenth of a conventional MRI system.
Hyperfine Research has raised $90 million to scale up the commercial rollout of its wheeled, bedside MRI scanner in the U.S. and abroad, following its debut last year.
The funds will also support the company’s development programs, which aim to secure new regulatory clearances both for hardware and artificial intelligence-driven software that aim to expand the scanner’s clinical uses inside and outside the hospital setting.
The company’s series D round was backed by GV, formerly known as Google Ventures, as well as Nextrans, Axiom Associates, Huami, Colle Capital, LSS and Altium Capital.
First cleared by the FDA almost one year ago last February, Hyperfine’s Swoop system is designed to scan the heads of people ages two and older, while weighing about one-tenth of a conventional MRI system.
It runs off a common power outlet, is operated by a tablet and is small enough to fit in an elevator—and uses permanent magnets and low-power radio waves that do not require additional shielding. This allows it to be wheeled into an ICU to scan the brain of a stroke patient, for example, instead of having the patient undergo a risky transfer through a hospital to a separate radiology unit.
In addition, the FDA last month cleared the company’s deep learning-powered application for interpreting images of brain injuries—enabling the automatic measuring of cerebrospinal fluid-filled cavities in the brain and the identification of shifts in the midline separating the brain’s two hemispheres, which is typically the sign of a traumatic injury or a stroke.
“I think of our device as a workflow solution,” Hyperfine’s chief medical and chief strategy officer, Khan Siddiqui, said in an interview. “At the end of the day, imaging is a way to make faster decisions on whoever you’re treating.”
“So if you’re just generating images, it’s not really helping with the decision-making process—it doesn’t really do much. Our focus is really on how we can help that clinician, as well as the patient, derive those decisions faster and right at the point of care,” Siddiqui said.
