Globally, the demand for improved health care delivery while
managing escalating costs is a major challenge. Measuring the
biomagnetic fields that emanate from the human brain already
impacts the treatment of epilepsy, brain tumours and other brain
disorders. This roadmap explores how superconducting technologies
are poised to impact health care. Biomagnetism is the study of
magnetic fields of biological origin. Biomagnetic fields are
typically very weak, often in the femtotesla range, making their
measurement challenging. The earliest
in vivo human measurements were made with room-temperature
coils. In 1963, Baule and McFee (1963
Am.
Heart J.
55 95−6) reported the magnetic field produced by
electric currents in the heart (‘magnetocardiography’),
and in 1968, Cohen (1968
Science
161 784−6) described the magnetic field generated
by alpha-rhythm currents in the brain
(‘magnetoencephalography’). Subsequently, in 1970,
Cohen
et al (1970
Appl. Phys. Lett.
16 278–80) reported the recording of a
magnetocardiogram using a Superconducting QUantum Interference
Device (SQUID). Just two years later, in 1972, Cohen (1972
Science
175 664–6) described the use of a SQUID in
magnetoencephalography. These last two papers set the scene for
applications of SQUIDs in biomagnetism, the subject of this
roadmap.
The SQUID is a combination of two fundamental properties of
superconductors. The first is flux quantization—the fact that
the magnetic flux Φ in a closed superconducting loop is
quantized in units of the magnetic flux quantum, Φ
0 ≡
h/2
e, ≈ 2.07 × 10
−15 Tm
2 (Deaver and Fairbank 1961
Phys. Rev. Lett.
7 43–6, Doll R and Näbauer M 1961
Phys. Rev. Lett.
7 51–2). Here,
h is the Planck constant and
e the elementary charge. The second property is the
Josephson effect, predicted in 1962 by Josephson (1962
Phys. Lett.
1 251–3) and observed by Anderson and Rowell (1963
Phys. Rev. Lett.
10 230–2) in 1963. The Josephson junction consists
of two weakly coupled superconductors separated by a tunnel barrier
or other weak link. A tiny electric current is able to flow between
the superconductors as a supercurrent, without developing a voltage
across them. At currents above the ‘critical current’
(maximum supercurrent), however, a voltage is developed. In 1964,
Jaklevic
et al (1964
Phys. Rev. Lett.
12 159–60) observed quantum interference between
two Josephson junctions connected in series on a superconducting
loop, giving birth to the dc SQUID. The essential property of the
SQUID is that a steady increase in the magnetic flux threading the
loop causes the critical current to oscillate with a period of one
flux quantum. In today’s SQUIDs, using conventional
semiconductor readout electronics, one can typically detect a
change in Φ corresponding to 10
−6 Φ
0 in one second. Although early practical SQUIDs were
usually made from bulk superconductors, for example, niobium or
Pb-Sn solder blobs, today’s devices are invariably made from
thin superconducting films patterned with photolithography or even
electron lithography. An extensive description of SQUIDs and their
applications can be found in the
SQUID Handbooks (Clarke and Braginski 2004
Fundamentals and Technology of SQUIDs and SQUID Systems
vol I (Weinheim,
Germany: Wiley-VCH), Clarke and Braginski 2006
Applications of SQUIDs and SQUID Systems
vol II
(Weinheim, Germany: Wiley-VCH)).
The roadmap begins (chapter 1) with a brief review of the
state-of-the-art of SQUID-based magnetometers and gradiometers for
biomagnetic measurements. The magnetic field noise referred to the
pick-up loop is typically a few fT Hz
−1/2, often limited by noise in the metallized
thermal insulation of the dewar rather than by intrinsic SQUID
noise. The authors describe a pathway to achieve an intrinsic
magnetic field noise as low as 0.1 fT Hz
−1/2, approximately the Nyquist noise of the human
body. They also descibe a technology to defeat dewar noise.
Chapter 2 reviews the neuroscientific and clinical use of
magnetoencephalography (MEG), by far the most widespread
application of biomagnetism with systems containing typically 300
sensors cooled to liquid-helium temperature, 4.2 K. Two important
clinical applications are presurgical mapping of focal epilepsy and
of eloquent cortex in brain‐tumor patients. Reducing the
sensor-to-brain separation and the system noise level would both
improve spatial resolution. The very recent commercial innovation
that replaces the need for frequent manual transfer of liquid
helium with an automated system that collects and liquefies the gas
and transfers the liquid to the dewar will make MEG systems more
accessible.
A highly promising means of placing the sensors substantially
closer to the scalp for MEG is to use high-transition-temperature
(high-
T
c) SQUID sensors and flux transformers (chapter 3).
Operation of these devices at liquid-nitrogen temperature, 77 K,
enables one to minimize or even omit metallic thermal insulation
between the sensors and the dewar. Noise levels of a few fT Hz
−1/2 have already been achieved, and lower values
are likely. The dewars can be made relatively flexible, and thus
able to be placed close to the skull irrespective of the size of
the head, potentially providing higher spatial resolution than
liquid-helium based systems. The successful realization of a
commercial high-
T
c MEG system would have a major commercial impact.
Chapter 4 introduces the concept of SQUID-based ultra-low-field
magnetic resonance imaging (ULF MRI) operating at typically several
kHz, some four orders of magnitude lower than conventional,
clinical MRI machines. Potential advantages of ULF MRI include
higher image contrast than for conventional MRI, enabling
methodologies not currently available. Examples include screening
for cancer without a contrast agent, imaging traumatic brain injury
(TBI) and degenerative diseases such as Alzheimer’s, and
determining the elapsed time since a stroke. The major current
problem with ULF MRI is that its signal-to-noise ratio (SNR) is low
compared with high-field MRI. Realistic solutions to this problem
are proposed, including implementing sensors with a noise level of
0.1 fT Hz
−1/2.
A logical and exciting prospect (chapter 5) is to combine MEG
and ULF MRI into a single system in which both signal sources are
detected with the same array of SQUIDs. A prototype system is
described. The combination of MEG and ULF MRI allows one to obtain
structural images of the head concurrently with the recording of
brain activity. Since all MEG images require an MRI to determine
source locations underlying the MEG signal, the combined modality
would give a precise registration of the two images; the
combination of MEG with high-field MRI can produce registration
errors as large as 5 mm. The use of multiple sensors for ULF MRI
increases both the SNR and the field of view.
Chapter 6 describes another potentially far-reaching application
of ULF MRI, namely neuronal current imaging (NCI) of the brain.
Currently available neuronal imaging techniques include MEG, which
is fast but has relatively poor spatial resolution, perhaps 10 mm,
and functional MRI (fMRI) which has a millimeter resolution but is
slow, on the order of seconds, and furthermore does not directly
measure neuronal signals. NCI combines the ability of direct
measurement of MEG with the spatial precision of MRI. In essence,
the magnetic fields generated by neural currents shift the
frequency of the magnetic resonance signal at a location that is
imaged by the three-dimensional magnetic field gradients that form
the basis of MRI. The currently achieved sensitivity of NCI is not
quite sufficient to realize its goal, but it is close. The
realization of NCI would represent a revolution in functional brain
imaging.
Improved techniques for immunoassay are always being sought, and
chapter 7 introduces an entirely new topic, magnetic nanoparticles
for immunoassay. These particles are bio-funtionalized, for example
with a specific antibody which binds to its corresponding antigen,
if it is present. Any resulting changes in the properties of the
nanoparticles are detected with a SQUID. For liquid-phase
detection, there are three basic methods: AC susceptibility,
magnetic relaxation and remanence measurement. These methods, which
have been successfully implemented for both
in vivo and
ex vivo applications, are highly sensitive and, although
further development is required, it appears highly likely that at
least some of them will be commercialized.
Chapter 8 concludes the roadmap with an assessment of the
commercial market for MEG systems. Despite the huge advances that
have been realized since MEG was first introduced, the number of
commercial systems deployed around the world remains small, around
250 units employing about 50 000 SQUIDs. The slow adoption of this
technology is undoubtedly in part due to the high cost, not least
because of the need to surround the entire system in an expensive
magnetically shielded room. Nonetheless, the recent introduction of
automatically refilling liquid-helium systems, the ongoing
reduction in sensor noise, the potential availability of high-
T
c SQUID systems, the availability of new and better
software and the combination of MEG with ULF MRI all have the
potential to increase the market size in the not-so-distant future.
In particular, there is a great and growing need for better
noninvasive technologies to measure brain function. There are
hundreds of millions of people in the world who suffer from brain
disorders such as epilepsy, stroke, dementia or depression. The
enormous cost to society of these diseases can be reduced by
earlier and more accurate detection and diagnosis. Once the
challenges outlined in this roadmap have been met and the
outstanding problems have been solved, the potential demand for
SQUID-based health technology can be expected to increase by ten-
if not hundred-fold.