Parallel imaging is a relatively new class of techniques capable of significantly increasing the speed of magnetic resonance imaging acquisitions by taking advantage of the spatial information inherent in an array of radiofrequency coils. The basic principles of parallel imaging techniques are described, and implications for a variety of clinical applications are discussed. These techniques may be applied across a broad range of examination types and organ systems, and recent advances place parallel imaging on the verge of widespread clinical use.
Dr. Sodickson is currently a 4th-year Radiology Resident at
Brigham and Women's Hospital, Boston, MA. He earned his BS in
Physics from the Massachusetts Institute of Technology, his PhD
in Medical Physics from the Harvard-MIT Division of Health
Sciences and Technology, and his MD from Harvard Medical
Parallel imaging has recently emerged as a powerful new approach
to magnetic resonance imaging (MRI) acquisition that enables
significant reductions in acquisition time. While a variety of
different techniques have emerged, the common principle behind all
of them is to use the spatial information inherent in the elements
of a radiofrequency (RF) coil array to allow a reduction in the
number of time-consuming phase-encode steps required during the
scan. These techniques may be applied to any existing pulse
sequence, and, in their simplest implementations, can be used to
reduce imaging time at fixed resolution, or, alternatively, to
increase resolution at fixed imaging time. The savings in imaging
time can, however, be applied toward a variety of other ends as
This article summarizes some of the fundamental principles, the
practical operational requirements, and the developing clinical
applications of parallel MRI techniques. The basic mechanisms of
spatial encoding in parallel acquisitions are reviewed, along with
the associated tradeoffs in signal-to-noise ratio (SNR). Pulse
sequences and acquisition strategies that are particularly
synergistic with parallel imaging are described. After a survey of
the broad range of clinical studies that benefit from typical
levels of acceleration, the frontiers of parallel imaging
development are explored, including order-of-magnitude
accelerations for volumetric imaging, and combinations with
Review of traditional spatial encoding in magnetic
Since the beginning of MRI, spatial encoding has generally been
achieved by taking advantage of the spatially dependent evolution
of nuclear spins (typically protons) in an externally applied
magnetic field gradient to fill a plane or a volume of k-space,
which is then Fourier- transformed to produce the two-dimensional
(2D) or three-dimensional (3D) image matrix. Spatial localization
along the frequency-encode direction is quite rapid, and is
determined by the local precession frequency as signal is collected
in the presence of the readout gradient.
Spatial encoding along the orthogonal phase-encode direction is
much more time consuming, and accounts for the lengthy acquisition
times encountered in traditional imaging methods. Evolution under
phase-encoding gradients is determined by numerous repetitions of
the pulse sequence with incremented phase- encoding gradient steps,
each incurring an additional repetition time (TR). Traditionally
(in the absence of half-Fourier techniques), this requires a number
of phase-encode repetitions equal to the phase-encode matrix size,
and results in long examination times.
In 2D acquisition techniques, individual slices are imaged
separately after excitation by an RF pulse in the presence of the
slice-select gradient. A full plane of k-space is filled by the
acquired signal, and Fourier-transformed to produce the individual
image slice. In contrast, 3D techniques excite the entire image
volume at once, and spatially encode along the "slice direction" as
well with additional phase-encode steps, resulting in a 3D volume
of signal that is Fourier-transformed along all 3 dimensions to
produce the full volumetric image matrix.
Radiofrequency coils with nearly uniform sensitivity over the
imaging volume (eg, the prototypical body coil) are often used to
image large volumes. For focused imaging of smaller volumes,
numerous surface coil designs exist, which have higher sensitivity
in defined regions of interest. Coil arrays, or so-called "phased
array coils," combine the benefits of the increased SNR of the
individual component coil elements with the larger coverage area of
their combination. In traditional use, multiple receiver systems
separately collect the signal from each of these coil array
elements, and a composite image is formed as the square root of the
sum of squares of the individual images, as this conveniently
approximates the highest achievable overall SNR.
Basic principles of parallel
After a number of early proposals
of ways to use multiple RF coils to increase data acquisition
speeds in MRI, the field of parallel imaging for clinical use first
blossomed with the introduction of the SMASH (SiMultaneous
Acquisition of Spatial Harmonics) technique.
This was soon followed by the SENSE (SENSitivity Encoding)
and subsequently by a wide variety of related hybrid and
All of these methods use spatial variations in the coil
sensitivities of the individual array elements to take the place of
time consuming phase-encoding gradient steps. By using combined
spatial encoding with both gradients and coil sensitivities, these
techniques allow reduced sampling densities in k-space, which
correspond to aliased images in the spatial domain. Parallel
imaging reconstructions use knowledge of the spatial behavior of
the individual coil sensitivities to reconstruct the intervening
lines in k-space in these under-sampled data sets, or equivalently,
to unfold aliased pixels within the corresponding aliased images.
The number of slow, serial phase-encode steps that comprise the
temporal bottleneck in MR imaging is decreased, resulting in
increased imaging speed.
An individual wire loop or coil array element has a spatially
localized coil sensitivity (Figure 1A and 1B), which determines the
portion of the imaging volume from which it is capable of
collecting signal. An array of such elements (Figure 1C and 1D)
produces separate coil sensitivities spatially displaced along the
length of the array. Each individual element effectively "sees" a
different portion of the imaging volume, and samples the target
magnetization density shaded by its own coil sensitivity function.
If the coil is appropriately aligned along the phase-encode
direction, then this spatial information may be exploited to allow
for a decreased amount of gradient encoding.
Two intuitive pictures are helpful to understand the image
reconstruction approaches of parallel imaging. The k-space picture
exemplifies the original SMASH technique.
Figure 2A shows that appropriate linear combinations of the coil
sensitivity functions may be produced to simulate sinusoidal
variations in signal across the image plane. In this schematic
example, summing the signal from all coils produces a nearly
uniform sensitivity, while adding or subtracting the signal from
adjacent coils in appropriate combinations produces an overall
signal modulated by sinusoids of varying spatial frequencies. As
evolution in the phase-encoding gradient normally produces
sinusoidal variations in magnetization across the image volume,
these combinations of signals from the elements of a coil array may
thus be used to mimic the effects of phase-encode gradient steps.
This allows for a decreased number of phase-encoding steps, with
the omitted lines in k-space filled in by appropriate signal
combinations (Figure 2B and 2C).
The image domain picture exemplifies the original SENSE
As shown in Figure 3A, each coil array element effectively samples
a different portion of the imaging volume, producing an image
shaded by its coil sensitivity. By undersampling k-space along the
phase-encode direction, aliased images are simultaneously acquired
from each coil (Figure 3B). Each aliased pixel is composed of a
linear combination of source pixels weighted by the coil
sensitivity of the array element at those source pixel locations.
Knowledge of the values of the coil sensitivities at all positions
allows a mathematical unfolding of the aliased pixels to produce
the full image without aliasing (Figure 3C).
Conceptually, there is equivalence of the k-space and image
domain pictures: Acquisition of undersampled k-space data for each
coil results in individual aliased images, and reconstruction of
the full image requires one to fill in the missing lines of
k-space, or equivalently, to "un-alias" the aliased images. The
numerous reconstruction techniques that have been introduced differ
largely in the specifics of their reconstruction algorithms and the
mathematical constraints applied. However, they may all be
understood as combinations of the intuitive k-space and image
domain pictures. The final images produced with the different
methods are not necessarily identical but may vary somewhat in the
nature of any residual aliasing artifacts, and in the details of
the noise profile across the image.
Figures 2 and 3 show one-dimensional accelerations performed
along traditional Cartesian axes, with the coil array aligned along
the phase-encode direction. Analogous techniques may be used to
separate image data from different slices that have been excited
Alternatively, parallel imaging may be performed along both
phase-encode directions in 3D acquisitions, for bidirectional,
multiplicative acceleration factors.
These approaches may also be generalized to non-Cartesian
trajectories such as undersampled spiral and radial acquisitions.
Non-Cartesian k-space trajectories result in more complex aliasing
patterns and underfilling of k-space, resulting in increased
computational complexity of the image reconstruction.
Impact on signal-to-noise ratio
As in most MRI techniques, the decreased imaging time in
parallel MRI studies typically incurs a penalty in SNR. SNR is
degraded in parallel imaging by two fundamental mechanisms. A
general principle of MR signal acquisition is that each acquired
point in k-space adds signal coherently while averaging the
incoherent noise. Reducing the number of acquired phase-encoded
k-space lines by an acceleration factor, R, thus causes a decrease
in the net SNR by a factor ÖR. In addition, all parallel imaging
reconstruction algorithms introduce an additional noise
amplification factor or geometry factor, g. This g factor is always
>1 and is spatially dependent in a manner determined by the coil
array geometry, the imaging volume, and the details of the
reconstruction algorithm used.
The g factor also increases in a complex fashion with higher values
of the acceleration factor R. The net SNR is thus as follows:
SNR = SNR
refers to the SNR of a corresponding unaccelerated image. Given
this expected degradation in SNR, the most natural applications of
parallel imaging involve studies in which there is SNR or
contrast-to-noise ratio (CNR) to spare, such as contrast-enhanced
MR angiography (CE-MRA), or volumetric acquisitions that boost SNR
by acquiring signal from the entire image volume at once rather
than sequentially from each slice.
Knowledge of the individual coil sensitivity functions must be
obtained to perform any parallel imaging reconstruction, as this
will allow the appropriate linear combination of signals to
reconstruct the omitted k-space lines or to unfold the aliased
images. Any errors in the coil sensitivity estimates may result in
residual aliasing artifacts. Sensitivity maps may be obtained from
low resolution pre-scans of the patient with the coil array in
place. Alternatively, a number of autocalibrating techniques have
been developed that acquire enough extra data during the scan
itself to extract the sensitivity profiles.
The simplest such techniques acquire the center of k-space in its
entirety to serve as the sensitivity maps, which are then used to
fill in the undersampled periphery of k-space. These
autocalibrating techniques are particularly beneficial in settings
where patient or organ motion is present, as any variations in
sensitivity profiles are intrinsically updated throughout the
Parallel imaging imposes particular hardware requirements. Coil
arrays must be used, with separate preamplifiers and receivers for
each individual element, and appropriate decoupling networks to
decrease crosstalk between elements. Parallel imaging techniques
may be used with existing coil arrays, but many tailored array
geometries have also been designed specifically with parallel
imaging in mind for better results.
Recently, the three major vendors of MR scanners have all
implemented versions of parallel imaging in their commercial
systems. Philips scanners (Philips Medical Systems, Best, The
Netherlands) incorporate 6 separate receivers, and use a SENSE
reconstruction. Siemens systems (Siemens Medical Solutions,
Erlangen, Germany) typically have 4 receivers, with some 8 receiver
systems available, and use iPAT (integrated Parallel Acquisition
Technology) with a choice of a self-calibrating SENSE-like and a
self-calibrating SMASH-like (GRAPPA,
GeneRalized Autocalibrating Partially Parallel Acquisition)
reconstruction. General Electric (GE Medical Systems, Milwaukee WI)
has both 4 and 8 receiver systems, and currently performs parallel
imaging with ASSET (Array Spatial and Sensitivity Encoding
Technique), a SENSE-
While operational details vary from vendor to vendor, a scan
performed with parallel imaging techniques typically involves
choosing and positioning an appropriate coil array, specifying the
acceleration factor, and either performing a sensitivity
calibration at some point during the examination or using a
vendor's self-calibrating approaches. The parallel imaging
reconstructions are then performed automatically on these
commercial systems to produce full, unaliased images by appropriate
manipulation of the data gathered from each of the individual coil
Options for using increased
Perhaps the most obvious application of parallel imaging is to
decrease the acquisition time with fixed resolution and imaging
parameters. This approach may be used to shorten breath-hold
durations, to increase anatomic coverage in a fixed scan time, or
to increase patient throughput. It may be used to increase temporal
resolution, particularly for dynamic techniques such as cardiac
and time-resolved MRA.
Alternatively, parallel imaging may be used to increase image
matrix and spatial resolution in a fixed scan time.
It may be used to improve image quality, for example by decreasing
T2 blurring effects from long echo trains in Fast Spin-Echo (FSE),
Turbo Spin-Echo (TSE), or single-shot sequences.
The shortened acquisition times can decrease artifacts secondary to
patient motion, susceptibility and chemical shift effects. In
certain circumstances, pulse sequences may even be optimized to
SNR, despite the inherent SNR losses of faster acquisition times
and g factor. This may be achieved, for example, by using decreased
bandwidth, increased repetition time, and increased flip angle
during a gradient-echo sequence.
Faster scan time in CE-MRA may support an increased rate of
contrast injection to boost CNR. Other applications making use of
parallel imaging for more than mere speed have also been described:
for example, a number of techniques have been developed using
parallel imaging techniques for detection and correction of motion
or other artifacts.
Clinical applications of parallel imaging
Parallel imaging has been applied across a wide variety of organ
systems and examination types.
Although, it is impossible to discuss or reference all of them
here, an effort has been made to include many of the seminal
initial works, along with a sampling of compelling recent
Contrast-enhanced MR angiography is a particularly attractive
application, in part due to the intrinsically high CNR from
contrast administration. The time savings of parallel imaging may
be used to advantage in MRA to increase resolution in a given
imaging time, or to increase temporal resolution in the move toward
time-resolved angiography, thus diminishing concerns of missing the
contrast bolus, or of venous contamination. These benefits have
been shown in MRA of the aorta and visceral vessels,
and peripheral MRA.
Figures 4 and 5 show examples of renal and peripheral vascular MRA,
with combinations of speed and spatial resolution that would not
have been achievable without parallel imaging.
Significant efforts have been made toward improving cardiac MRI
with parallel imaging.
Intuitively, the faster acquisition speeds may lessen some of the
challenges of imaging this moving target. As shown in Figures 6 and
7, applications to cardiac imaging have ranged from coronary
which benefits from increased resolution in a given imaging time,
to functional and real-time cardiac imaging,
for which temporal resolution is of the essence.
Abdominal imaging applications (Figure 8) stand to improve
significantly from parallel imaging techniques. Faster acquisition
may be applied toward increasing anatomic coverage in a given
breath-hold, or reducing breath-hold lengths to diminish
respiratory or other motion artifacts.
Alternatively, time savings may be used to increase resolution for
better visualization of small lesions.
Benefits to breast imaging have been shown both by increasing
temporal resolution in dynamic imaging,
and by permitting simultaneous examination of both breasts with
standard single-breast resolution.
The challenges of imaging the moving fetus make fetal MRI an area
ripe for the application of parallel imaging techniques.
Applications to neurologic imaging are also on the rise. Imaging
accelerations have been applied to spectroscopy,
diffusion-weighted imaging (DWI),
diffusion tensor imaging and white matter tractography,
and functional MRI (fMRI).
Figure 9 shows a high CNR phase-contrast MRA of the brain in a scan
time made feasible only by the application of parallel imaging
Benefits at higher field strengths of 3T to 7T are quite promising
to the future of high-field neuroimaging as well. Significant
reductions in susceptibility artifacts at high field have been
shown, as Figure 10 illustrates for echoplanar DWI at 3T.
Pushing the limits
For conventional coil array designs and typical imaging volumes,
the noise amplification g factor can rise prohibitively as the
acceleration factor increases. As a result, typical accelerations
along one dimension generally do not exceed a factor of 4. It has
been shown, however, that accelerations may be performed along both
phase-encode axes of a 3D acquisition with significantly lower g
factors for equivalent accelerations.
Recently, order-of-magnitude accelerations have first been shown
for volumetric, CE-MRA of the thoracic and abdominal aorta.
These images were acquired at 1.5T, with a prototype 32-receiver
system (GE Global Research Center, Niskayuna, NY) and a 32-element
clamshell coil array with 16 elements each above and below the
patient. Three-fold acceleration was used in the craniocaudal
direction, and 4-fold acceleration was used transversely, for a
combined acceleration factor of 12. These high acceleration factors
make possible the acquisition of a large image volume at high
spatial and temporal resolution. Figure 11 shows a time-resolved
approach, with the entire 36 * 36 * 36 cm image volume acquired
dynamically every 4.5 seconds (reduced from the 54 seconds that
would have been required with a conventional acquisition). A higher
resolution approach with lower temporal resolution was also
described, utilizing 22 second volumetric breath-hold acquisitions
(reduced from 4.4 minutes). The large coverage volumes used in both
these approaches easily include the full arterial anatomy of the
abdomen in a single acquisition, including the entire celiac axis
and superior mesenteric artery territories anteriorly, the renal
arteries and inferior mesenteric artery, and even the gluteal
branches of the internal iliac arteries posteriorly.
These examples underscore the synergy of volumetric acquisition
with parallel imaging. Without the acquisition speeds of parallel
imaging, large volume 3D scans would not be possible in a single
breath-hold. Conversely, the increased SNR of volumetric scanning
enables high acceleration factors by compensating for the SNR
losses incurred by decreased acquisition times and the g factors of
parallel imaging techniques. The resulting acquisition speeds may
rival those of multidetector CT, or provide the time-resolved
benefits of conventional angiography, while at the same time
permitting the full range of tissue contrast mechanisms unique to
The recent advent of higher field systems ranging from 3T to 7T
will provide further synergy with parallel imaging techniques. The
increased baseline SNR will enable more widespread use of parallel
imaging, and the increased RF focusing ability (the narrower
spatial extent of the RF field for a given coil geometry) at higher
frequency is beneficial for improved reconstructions.
Parallel imaging also holds great promise in enabling higher field
work, and can easily be implemented to decrease RF power deposition
or specific absorption ratio (SAR) by reducing the length and/or
the density of echo trains, to decrease acoustic noise by reducing
the amount of required gradient switching,
and to reduce susceptibility artifacts (Figure 10) that become
increasingly troublesome with increasing field strength.
Parallel imaging techniques provide a powerful new set of tools
for use in clinical MRI. Recent technical advances and increased
availability to imaging centers place parallel imaging at the cusp
of widespread clinical use. Increased speeds do come at a
well-defined cost in SNR, which must be taken into account in the
planning of imaging protocols. However, for applications with
sufficient baseline SNR, parallel MRI can offer substantial
benefits. There is great synergy both with 3D volumetric
acquisitions and with high-field MR systems. As experience with
these techniques grows, the future of clinical MRI may well shift
toward rapid, volumetric acquisitions. Just as the advent of
multidetector CT scan-ners spurred an explosion of imaging
improvements, parallel imaging techniques promise to enable a broad
range of new clinical MR applications.
It has been a source of great pleasure to watch my brother Dr.
Daniel Sodickson's work evolve over the past several years, and to
see the techniques of parallel imaging expand from the research
realm into clinical practice. I thank him for the use of several
images, and for many enjoyable conversations on the finer points of
parallel MRI. Many thanks are due Dr. Frank Rybicki, for his
mentorship in this project and for his editorial assistance. I am
most grateful to Drs. Charles McKenzie, Neil Rofsky, Stefan
Schönberg, Jeffrey Maki, Thoralf Niendorf, Johan van den Brink,
Romhild Hoogeveen, and Christiane Kuhl, all of whom kindly
contributed samples of their work for reproduction here.