ADVANCES
18 Scientific American, March 2022
yumiyum/Getty ImagesMEDICINE
Portable View
Compact MRIs could
bring down the cost of
powerful medical scanning
Magnetic resonance imaging (MRI)
scanners are crucial tools in modern medi-
cine. But these behemoths typically cost
$1 million to $3 million; they require pur-
pose-built rooms to contain their powerful
magnetic fields and block outside signals,
plus elaborate liquid-helium cooling sys-
tems. About two thirds of the world’s
people lack access to such devices,
90 percent of which are located in high-
income countries.
Now, however, lower-cost alternatives
are coming closer. In Nature Communica-
tions, researchers at the University of Hong
Kong, led by biomedical engineer Ed Wu,
describe an MRI scanner that is compact
enough to move on wheels, needs no
shielding and draws power from a stan-
dard wall socket. This approach— a new
entry in a category known as ultralow-field
(ULF) MRI—lacks the resolution needed
for some precision diagnostics, but its
material costs are estimated at under
$20,000. And its design and algorithms are
open source, inviting researchers every-
where to help develop the technology.
MRI exploits the fact that we are
mostly made of water. The protons in
water’s hydrogen atoms have magnetically
charged “spins,” which can be temporarily
aligned by a scanner’s magnetic field and
then probed by radio-frequency pulses.
Different tissues have distinct water con-
centrations and magnetic properties,
which generate light and dark contrasts
in reconstructed images.
Instead of the standard superconduct-
ing electromagnets, this ULF design uses
permanent magnets that do not require
cooling. It also generates far less magne-
tism than a standard MRI scanner, elimi-
nating the need for shields. The main
trade-off is that the signals are weaker,
resulting in lower image resolution.
To enable portability, the new design
eschews physical shielding against exter-
nal radio-frequency noise. Instead a “deep-
learning” algorithm recognizes and pre-
dicts interference signals, then subtracts
them from the measured signals. “That’s
one very useful innovation here,” says
biomedical engineer Sairam Geethanath
of Columbia University, who was not
involved in the new research. “It’s similar
to noise-cancellation headphones, where
you’re trying to learn the noise pattern in
real time and suppress it.”
The team demonstrated the device
by scanning 25 patients and comparing
the images with those from a standard
high-powered MRI machine. The
researchers could identify most of the
same pathologies, including tumors and
stroke. “The images appear to be of suffi-
cient quality to be clinically useful in a
number of scenarios,” says neuroscientist
Tom Johnstone of Swinburne University of
Technology in Melbourne, Australia, who
was also not involved in the study. “Rapid
assessment of stroke, which has a large
impact on success of interventions, could
be facilitated by ULF MRI being located in
more towns or even mobile units.”The new design joins a growing list
of ULF MRI scanners being developed.
A U.S. company called Hyperfine re -
ceived fda approval last year for a porta-
ble scanner, but details of the design are
proprietary; Wu and his colleagues have
made their data, designs and code avail-
able online, which could speed improve-
ments to ULF.
Ultimately ULF devices are not
intended to completely replace high-field
scanners. Instead they hold promise in tri-
age settings, where patients cannot be
moved or time is critical, Geethanath says.
Wu says he believes the range of appli-
cations will likely grow as performance
improves. “Right now MRI systems are
built as if we don’t know anything about
what we’re scanning,” he says, “but often
the information we need is very subtle”—
namely, to identify what is different from
the expected. “That’s going to be a huge
revolution, driven by cheap computing.”
— Simon MakinMRI machines are particularly
useful for scanning brains.