Echo-shifted multislice EPI for high-speed fMRI

Magnetic Resonance Im

Echo-shifted multislice EPI for high-speed fMRI

Andrew Gibson, Andrew M. Peters, Richard Bowtell4

Sir Peter Mansfield Magnetic Resonance Centre, School of Physics and Astronomy, University of Nottingham, NG7 2RD Nottingham, UK

Received 2 December 2005; accepted 2 December 2005

Abstract

The advantages of event-related functional Magnetic Resonance Imaging (fMRI) and the increasing use of fMRI in cognitive experiments

are both driving the development of techniques that allow images sensitive to the blood oxygen level-dependent effect to be acquired at ever-

higher temporal resolution. Here, we present a technique based on the use of echo shifting (ES) in conjunction with a multislice (MS) echo

planar imaging (EPI) readout, which allows T2*-weighted images to be generated with a repetition time per slice that is less than the echo

time (TE). Using this ES-MS-EPI approach, it is shown that images with a TE of 40 ms can be acquired with an acquisition time per slice of

only 27 ms. The utility of the MS-ES-EPI sequence is demonstrated in a visual-motor, event-related fMRI study in which nine-slice image

volumes are acquired continuously at a rate of 4.1 Hz. The sequence is shown to produce reliable activation associated with both visual

stimuli and motor actions.

D 2006 Elsevier Inc. All rights reserved.

Keywords: fMRI; High-speed; Echo shifting; Temporal resolution

1. Introduction

Functional magnetic resonance imaging (fMRI) has

proven to be a very powerful tool in the investigation of

human brain function. The rate of image acquisition is an

important parameter in the design of any fMRI experiment,

since changing the temporal resolution can affect many

characteristics of the acquired data. Increasing the temporal

resolution with which fMRI data are acquired has a number

of advantages. First, the resulting improvement in the

sampling and, hence, characterization of the haemodynamic

response increases the potential analytical power of the

technique and also reduces problems in analysis caused when

spatially separate regions of the brain are sampled at different

times. This is particularly advantageous in event-related

fMRI in which short interstimulus intervals [1,2] are used or

in which small differences in the timing of activation across

trials need to be assessed [3]. Second, increasing the rate of

acquisition of images in fMRI experiments via reduction of

the repetition time (TR) between successive radiofrequency

(RF) excitations can increase the efficiency with which

activation is detected. The signal-to-noise ratio (SNR) of a

0730-725X/$ – see front matter D 2006 Elsevier Inc. All rights reserved.

doi:10.1016/j.mri.2005.12.030

4 Corresponding author. Tel.: +44 115 9514737; fax: +44 115

9515166.

E-mail address: [email protected] (R. Bowtell).

voxel time course in an fMRI experiment depends upon the

volumar TR of the experiment. Reducing TR leads to a

decrease in SNR in each image due to saturation; however,

the number of images acquired per unit time increases, and

with an optimal choice of flip angle, this leads to an overall

increase in image SNR per unit time. This is favorable for

fMRI experiments where temporal filtering is used to average

signals over time to give a smoothed, reduced-noise repre-

sentation of the original signal. As the filter shape is usually

designed to match the form of the haemodynamic response,

any increase in SNR per unit time in the data will lead to an

increase in the blood oxygen level-dependent (BOLD)

contrast-to-noise ratio of the temporally filtered data. Thus,

as the SNR of the filtered data increases with increased

sampling rate, the efficiency of detection will increase,

assuming all other factors are held constant. Increasing the

sampling rate in an fMRI study also has the advantage of

allowing for the possible detection and subsequent removal

of physiological noise due to cardiac and respiratory effects

[4–6]. For example, if the physiological noise is critically

sampled, standard temporal filtering techniques can be used

to attenuate frequencies at which physiological noise occurs.

With volumar TRs of 2 to 3 s, as are commonly employed in

fMRI experiments, fluctuations linked to the cardiac cycle

are undersampled. Consequently, their contributions to signal

variation are aliased to lower frequencies, making them

aging 24 (2006) 433–442

Fig. 1. Results of a Monte Carlo simulation, demonstrating the increased

efficiency (Z score) of detection with decreasing volumar TR, for a

simulated train of haemodynamic responses. The simulation also shows that

at lower volumar TRs, the variability in the efficiency (Z score) decreases.

A. Gibson et al. / Magnetic Resonance Imaging 24 (2006) 433–442434

difficult to eliminate by simple low-pass filtering. Third,

increasing the volumar acquisition rate potentially allows

more accurate correction of subject motion, as movement

occurring during the acquisition of an individual image

volume will be reduced. When three-dimensional data are

acquired via phase encoding across multiple excitations,

movement during one volumar acquisition leads to image

blurring and formation of artifacts that cannot be corrected by

simple motion correction algorithms. In the case of multislice

(MS) fMRI data, movement during the acquisition of an MS

set means that different slices are acquired with the head at

different positions so that the resulting data does not truly

conform to the model of rigid body motion often assumed in

motion correction algorithms [7].

Improvement in the accuracy with which the haemody-

namic response can be characterized as the volumar

sampling rate is increased has been demonstrated previously

via simulation and experiment by Dilharreguy et al. [3]. In

particular, their work showed a decrease in the accuracy of

determination of the time at which the haemodynamic

response peaks by approximately 50 ms for each second by

which TR is increased in MS echo planar experiments for

TRs in the range of 0.5–2.5 s.

The improved characterization of cardiac fluctuations via

a reduction in TR has been particularly explored in studies

of functional connectivity [8], where it is important to

sample cardiac fluctuations adequately [9,10], so that their

contribution to covariation of signal in apparently connected

spatial regions can be eliminated.

1.1. Improved efficiency of detection of BOLD responses

In order to illustrate the potential for improved efficiency

of detection of BOLD responses through reduction of the

volumar TR, fMRI data sampled at a range of TR values

was simulated and then subjected to a conventional

statistical analysis. In generating the simulated data, it was

assumed that T2bTR so that steady-state transverse mag-

netization was not formed, and it was also assumed that the

Ernst angle was employed for RF excitation, so that the

signal strength was given by

S TRð Þ ¼ S0

ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi1� e�TR=T1

1þ e�TR=T1

sð1Þ

where S0 is the signal that would be measured at the same

echo time (TE) using a 908 pulse with TRNNT1. The noise,

r, in the fMRI signal can be modeled using the theory of

Kruger and Glover [11] as

r ¼ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffir20 þ S TRð Þ½ �2k2

qð2Þ

where r0 is the intrinsic thermal and scanner noise and

the physiological noise is given by the product of k and

S(TR). k is an TE-dependent constant, which characterizes

the sum of the BOLD and non-BOLD physiological noise

contributions [11].

The event-related haemodynamic response to a stimulus

was modeled using a typical gamma-variate function [12],

giving a peak signal change of 2%. The simulated data

represented 10 responses to stimuli separated by a 15-s

interstimulus time, giving a total time series duration of

2.5 min. A random delay (in the range of F2.5 s) was

introduced at the start of the time series to model the effects

of slice ordering and variable haemodynamic delays. The

simulated response was then sampled using different TRs

varying from 0.2–5 s, and the level of white noise predicted

by Eq. (2) was added. The resulting time series were then

temporally filtered with a 2.8-s-width Gaussian filter, as

might be used in the analysis of event-related fMRI data. A

cross-correlation statistic was subsequently produced using

the response prior to addition of noise as the reference. The

correlation coefficient was then converted to a Z score,

allowing for the correct number of degrees of freedom of the

data. In order to investigate the variability of the efficiency

of detection, the simulation was repeated 100 times at each

TR with different random noise and delays. The results of

the simulation are shown in Fig. 1, where the error bars

represent F1 standard deviation of the averaged Z score at

each value of TR. The simulation shows that efficiency

(Z score) increases with decreasing TR, as predicted from

simple noise analysis. The variability in the Z score also

decreases with decreasing TR. This is important as the

efficiency of detection of a response ideally should not

depend strongly on the slice timing. The simulation shows

that for increased efficiency with decreased variability, it is

best to scan with as small a TR as possible.

The theory used in the simulation is simplistic on several

levels. The noise in the haemodynamic response is assumed

to be white, irrespective of its source. It is clear that

physiologically induced noise will not be white in nature

and will have components that fall into definite frequency

bands. If this noise is critically sampled at short TRs, it

would mean that it would have more spectral power in the

A. Gibson et al. / Magnetic Resonance Imaging 24 (2006) 433–442 435

stop band of the filter than assumed in the model, which

would be advantageous. Physiological noise resulting from

haemodynamic fluctuations is likely to have a correlation

time of a few seconds as a result of the time scale of the

haemodynamic response. It will consequently survive the

filtering process, and the gain in efficiency achieved by

going to short sampling times will therefore be reduced.

1.2. Sequences for rapid acquisition of T2*-weighted

volumar image data

The vast majority of fMRI experiments that are currently

carried out employ an MS, echo planar imaging (EPI)

sequence, as shown in Fig. 2A for image acquisition. Such

sequences typically employ a TR of a few seconds, which is

needed to acquire data from multiple (N10) slices, since

each slice acquisition requires a time of the order of 100 ms.

Analysis of Fig. 2A shows that the minimum volumar TR

is in fact given by

TRcNSL � TRF=2þ TEþ TEPI=2ð Þ ð3Þ

where NSL is the number of slices sampled, TRF is the

duration of the RF pulse used for selective excitation and

TEPI is the duration of the echo train generated by the

switched gradient of the EPI sequence. Assuming a TE of

36 ms, as is commonly employed in fMRI at 3 T and use of

an EPI sequence involving sampling of 64 echoes with a

1-kHz gradient switching frequency, and an RF pulse

duration of 4 ms, gives a time per slice of about 70 ms.

At 1.5 T where T2* and, hence, the optimal TE for fMRI is

longer, a greater time per slice is required.

Inspection of Eq. (3) shows that for a fixed number of

slices, the most significant reduction of TR can be achieved

by decreasing TE. However, this is not normally an

acceptable approach since it leads to a reduction in the

BOLD contrast. This leaves the alternative of shortening

TRF or TEPI. Since TRF is generally much shorter than TE

and TEPI, reducing its value has little effect on TR whilst

leading to significant increases in the required RF power.

Reduction of TEPI is more productive and can be achieved

by increasing both the gradient switching rate and gradient

strength and/or employing parallel imaging [13,14] so as to

reduce the number of echoes acquired. Both strategies can,

however, yield only limited reductions in TR, the former

approach being restricted by the performance of gradient

hardware and the need to avoid peripheral nerve stimulation,

whilst use of too high speed-up factors in parallel imaging

causes significant spatially varying noise enhancement [13].

Revisiting the example mentioned above, a two-fold

reduction in the number of k-space lines sampled and an

increase in the gradient switching frequency by a factor of

1.5 would yield a minimum TR of about 50 ms per slice, at

the cost of a 1.7-fold reduction in SNR due to the shortening

of the echo-train from 32- to 11-ms duration.

The echo volumar imaging (EVI) technique [15] offers

an alternative approach to the rapid generation of three-

dimensional, T2*-weighted image data. EVI generates three

dimensional images using a single RF excitation, followed by

application of a periodic, switched gradient waveform and

two orthogonal blipped gradients (applied as the switched

gradient reverses sign). The switched gradient generates a

train of gradient echoes that are phase-encoded in two

orthogonal directions by the blipped gradients. Unfortunate-

ly, generating large image matrices with EVI necessitates the

use of long echo trains, leading to a high sensitivity to image

distortion due to magnetic field inhomogeneity [16]. Conse-

quently, at high field, EVI is not well suited to use in fMRI

studies where whole-brain coverage is required in conjunc-

tion with reasonable spatial resolution. EVI does, however,

offer significant potential for the study of small cortical

regions with high spatial and temporal resolution [17].

Principles of echo-shifting with a train of observations

(PRESTO) imaging [18,19] has also been used for rapid

acquisition of three-dimensional fMRI data [20–22]. PRES-

TO employs multiple RF excitations of the volume, in

conjunction with echo shifting (ES), so as to achieve a TE

that is greater than the inter-RF pulse spacing, TR. A partial

EPI readout is generally carried out after each excitation, and

in three-dimensional mode, a varying phase-encoding

gradient is applied in the third dimension immediately after

RF excitation. In a recent implementation of 3D-PRESTO in

combination with partial Fourier encoding and parallel

imaging, Klarhffer et al. [20] were able to generate

T2*-weighted images (with 4�4�4-mm3 voxels) covering

the whole brain, with an acquisition time of 0.5 s per volume.

Implementation of 3D-PRESTO involves the use of short

TRs (e.g., TR=29 ms), leading to the formation of steady-

state transverse magnetization, which causes a more com-

plicated signal dependence on TR, TE, T1, T2 and T2* than

obtained in MS EPI. In addition, the persistence of highly

dephased magnetization over several TR periods leads to

sensitivity to motion and consequent temporal instability.

This is often ameliorated via the use navigator echoes [21].

Here, we present a technique based on the use of ES in

conjunction with MS EPI. This allows images in an MS set

to be generated with a TR per slice that is less than the TE,

thus speeding up the volumar data acquisition rate compared

with conventional MS EPI, without altering image contrast.

This MS-ES-EPI sequence has been implemented at 3 T and

used to generate images with a TE of 40 ms and an

acquisition time per slice of only 27 ms. The utility of the

MS-ES-EPI sequence is demonstrated in a visual-motor,

event-related fMRI study in which a nine-slice volume is

acquired continuously at a volumar data rate of 4.1 Hz. The

sequence is shown reliably to detect activation associated

with both visual and motor stimuli.

2. Method

2.1. The MS-ES-EPI sequence

Fig. 2B shows the timing diagram describing the MS-

ES-EPI sequence. Successive slices are sequentially excited,

Fig. 2. (A) Conventional MS EPI sequence. The relative areas under the gradient pulses applied along the slice direction are shown numerically, and the

number of the slice excited by each RF pulse is also indicated. (B) MS-ES-EPI sequence. The signal excited from slice 1 by the first RF pulse is refocused in

the period following the second RF pulse, so that TENTR/Nslice. The gradient pulses on the slice axis that are shown using dashed lines can be added to provide

greater dephasing of the signal from any slice during periods in which it is not being measured.



but the negative polarity-refocusing gradient pulse that

usually follows immediately after slice selection is omitted,

and a negative gradient lobe, the area of which is 1.5 times

that of the slice-select gradient, is added at a time

immediately preceding the application of the selective RF

pulse. This combination of gradient pulses acts to shift the

gradient echo of the signal formed due to each RF

excitation by a time equal to the RF pulse separation

[18]. Consequently, the signal from the nth slice is

measured in the interval following the RF pulse that

excites the n+1th slice, so that the TE is greater than the

RF pulse spacing. The EPI switched (read) and blipped

(phase-encoding) gradients are played out in the period

between RF pulses, and both gradient waveforms are ad-

justed to have zero total area in each inter-RF-pulse

interval, so that no phase is accumulated between succes-

sive RF pulse applications.

Inspection of Fig. 2B, shows that the minimum time

needed to acquire a MS data set using the MS-ES-EPI

sequence is reduced to

TR ¼ NSL � TRFþTEPIð Þ ð4Þ

whilst the minimum TE is equal to 1.5 (TRF+TEPI).

Considering, once again, an EPI sequence involving

sampling of 64 echoes with a 1-kHz gradient switching

frequency and an RF pulse duration of 4 ms, the MS-ES-EPI

sequence gives an acquisition time per slice of about 36 ms,

whilst the minimum TE is 54 ms.

The form of the gradient waveform applied in the slice

direction means that the transverse magnetization generated

by excitation of a particular slice by the nth RF pulse is

modulated by a phase factor of the form eiks m�1ð Þs

2 in the

period following the n+mth RF pulse, where s is the spatial

coordinate in the slice direction and ks=cGsTRF. Conse-

quently, the phase dispersion across a slice of thickness, Ds,

is ks (m�1) Ds/2, taking a value of zero only when m=1,

and for other values having a minimum phase dispersion of

ks Ds/2. This dispersion needs to be large enough to crush

the signal to very low levels in all interpulse periods except

when m=1. If a larger phase dispersion is required to

achieve an adequate level of signal attenuation, this can be

achieved by adding gradient lobes at the beginning and end

of the interpulse period, the areas of which are in the ratio

1:�2, as shown using dashed lines in Fig. 2B. ES over

more than one interpulse period can be achieved by

varying the ratio of the gradient pulse areas, as introduced

by Liu et al. [18] in their original description of the

PRESTO technique.

2.2. Implementation at 3 T

The MS-ES-EPI sequence was implemented on a 3-T

imaging system that was previously constructed inhouse

and equipped with an insert head gradient coil [23]. This

system has only one RF channel for reception, and so,

implementation of parallel imaging in conjunction with the

MS-ES-EPI sequence was not possible. A sinusoidal,

switched gradient waveform of 1.9-kHz frequency was

generated using a simple resonant circuit. Using a selective

RF pulse of 1.5-ms duration, images with a matrix size of

64�64 pixels were acquired with an in-plane resolution of

4 mm and a slice thickness of 10 mm. For this sequence, 64

echoes were acquired in a time of 17 ms. An extra 3 ms was

required at the beginning of the echo train for the k-space

pre-excursion in the blipped gradient direction and applica-

tion of a dephasing gradient pulse in the slice direction. A

time of 5 ms was needed at the end of the echo train

for application of a rephasing gradient lobe in the phase-

encoding direction and a dephasing gradient pulse in

the slice direction. This gave an acquisition time per slice

of 27 ms, and in these experiments, each volume consisted

of nine slices, giving a volumar acquisition rate of 4.1 Hz.

The minimum possible TE of 40 ms was employed, which

is close to the optimum value for generating BOLD contrast

at 3 T. The slice gradient waveform applied gave a value

of ks of 14 mm�1 so that the minimum phase dispersion

of unwanted coherences across the slice thickness was

70 radians.

Initial experiments were carried out using a transmit/

receive birdcage RF coil and employed a coronal slice

orientation. In a series of 21 experiments, the flip angle of

the RF excitation pulse was varied between 08 and 1368,and the image intensity in regions of grey and white matter

was measured and compared with the predicted signal

strength. In each experiment, 220 MS data sets were

acquired in 54 s, and the data from the first 100 volumes

was discarded to ensure that the signal had come to

steady state.

2.3. Visual/motor fMRI studies

The MS-ES-EPI technique was then applied in an fMRI

study employing a simple, visually cued motor task. Five

healthy volunteers were presented with a series of visual

stimuli in the form of a flashing checkerboard at 29.16-s

intervals. The duration of each stimulus was either 5 or 1 s.

The subjects were instructed to press a button with the

thumb of the right hand at the end of each visual cue, and

the time of the button press was recorded. Fifteen cycles of

each condition were presented, giving a total imaging time

of 14 min and 35 s; during this time, a total of 3600 volumes

of data were collected. Each volume consisting of 9, sagittal

slices spanning the left hemisphere of the brain

(4�4�10-mm3 voxel dimensions) was acquired in 243 ms,

with TE=40 ms. A surface RF coil of 14-cm diameter was

positioned on the right side of the head and used for both

signal excitation and reception.

The data were analyzed in MEDx (Medical Numerics,

VA, USA) and motion correction, normalization and

spatial and temporal filtering [12] were applied prior to

statistical analysis. A correlation analysis with a delayed

boxcar convolved with a gamma-variate function was used

to identify activated regions of interest. Voxels showing a

Fig. 3. An example 9-slice image volume acquired using the MS-ES-EPI sequence. Images were acquired with a matrix size of 64�64 pixels, a slice thickness

of 10 mm, in-plane resolution of 4 mm and an TE of 40 ms. Using an RF pulse separation of 27 ms, the whole volume was acquired in 243 ms.


pattern of activity associated with the motor action or

visual stimulus were identified for further data processing

to explore the timing of the haemodynamic responses.

Fig. 4. Variation of the intensity of the signal generated by grey matter (blue)

and white matter (red) as a function of flip angle when using the MS-ES-EPI

sequence with TR=243 ms in a nine slice acquisition. The open circles show

experimentally measured values, from regions of interest in grey and white

matter, while the continuous lines show the values predicted using Eq. (4).

3. Results

Fig. 3 shows a volume data set consisting of nine

10-mm-thick coronal slices (64�64 matrix, 256�256 mm2

field of view), which was acquired in 243 ms using the bird-

cage RF coil. These images display significant T2* contrast,

reflecting the 40 ms TE. In addition, there is some signal

dropout in frontal areas due to dephasing across the

relatively large slice thickness. Fig. 4 shows the variation

of signal intensity in grey and white matter areas with flip

angle in MS-ES-EPI images acquired with a TR value of

243 ms. Experimental results are shown using open circles,

while the theoretical data calculated using the expression

S að Þ ¼ S0sin a1� e�TR=T1

1� cos a e�TR=T1ð5Þ

are shown using continuous lines. T1 values of 1330 and

830 ms were employed for grey and white matter in the

simulations [24]. In displaying the results, both simulated and

measured data values have been scaled by the maximum

signal strength over the range of flip angles considered.

Fig. 6. The haemodynamic response in active areas of visual cortex,

averaged over the 15 presentations of the 1-s (blue line) and 5-s (red line)

stimulus. The time course is the average of the pixels whose response

produced an above threshold Z score in the first stage of statistical analysis.

Fig. 5. An activation map from one subject performing the visual motor paradigm overlaid on a T2*-weighted high-speed MS PRESTO-EPI image. The Z score

is shown in grey and white, using a corrected threshold for statistical significance of Pb.001.


Fig. 5A shows the corrected Z score (Pb.001) map from

the correlation analysis overlaid on T2*-weighted MS-ES-

EPI image data produced from one subject who performed

the visual-motor task. The sagittal images show the signal

drop-off produced by the sensitivity profile of the surface

coil used in this experiment. Areas of high correlation are

apparent in visual and motor cortices. A similar pattern of

activation was identified in the four other subjects studied.

Fig. 6 shows the average response in visual cortex to visual

stimuli of 1- and 5-s duration in one subject, without

temporal smoothing. Sampling at 4.1 Hz yields more than

120 time points in each 30-s average time course. As

expected, the response to the longer duration stimulus peaks

later in time and is of higher peak amplitude.

To compare the time courses of the activation produced in

the motor cortex due to the button presses after visual cues of

long and short duration, the pixels shown to be activated by

the correlation analysis were selected for further processing.

The raw time-series data were high-pass temporally

smoothed to reduce the effect of baseline signal drift [12]

and corrected for variable haemodynamic lags across pixels.

The latter adjustment was performed by fitting a straight line

to the rising edge of the average response elicited by the

button press following the shorter visual cue (1-s duration) for

each pixel and then temporally shifting the whole pixel time

course so that the intercept of the straight line fit with the

baseline occurred at the same time point in all pixels [12]. The

Fig. 7. Representative time courses of the motor area activation shown in Fig. 5. (A) Part of the total time course for the motor activation clearly showing the

response to four single button presses, the first and last being the response to a 1-s cue and the second and third being the response to the 5-s cue. (B) The

average motor response to the 1-s visual cue, the error bars areF1 standard deviation over 15 cycles. The response in (C) is the motor response to the 5-s visual

cue; the extended length of the cue has produced a detectable early anticipatory response in the motor region and delayed the button press by 4 s, relative to the

response from the 1-s cue.


resulting time courses were then used in an independent

component analysis (FastICA, Laboratory for Information

and Computer Science, Helsinki University of Technology)

over time to extract one time course associated with the motor

action. Fig. 7 shows representative time courses from the

same subject as shown in Fig. 5. Fig. 7A, shows a 120-s

portion of the total time course, in which the responses to four

button presses at 30-s intervals are evident. The first and

fourth responses each follow a visual cue of 1-s duration,

while the second and third follow cues of 5 s duration. The

longer duration of the response to the 5-s cues that is apparent

here, is more clearly seen in the averages of the 15 time

courses measured following the short and long cues, which

are shown in Fig. 7B and C. In both traces, time zero

corresponds to the start of the visual cue. Before averaging

the time courses across trials, the response to each button

press was time-shifted to take account of the slight variation

in the time of the button press relative to the end of the cue

across trials. The standard deviation of these response times

across subjects was about 80 ms. The different shape of the

haemodynamic response in the case of the longer visual cue

makes it difficult to compare the timings of the responses to

the different cues and seems to reflect the presence of an early

anticipatory response [25] superimposed on the later response

to the button press. To explore this hypothesis, the

haemodynamic response elicited by the button press follow-

ing the longer visual cue was modeled by convolving the

response to the 1-s cue, with a unit impulse at time zero added

to another varying strength impulse at a later time, nTR,

where n is an integer. n was varied in from 1 to 50,

corresponding to delays spanning the range 0.234–11.7 s. In

all subjects, the best fit of the modeled response to the

experimental data occurred when n=17, yielding a delay of

3.978 s, which is the closest accessible value to the expected

4-s time difference.

4. Discussion

The MS-ES-EPI sequence allows rapid acquisition of MS

T2*-weighted echo planar images by using the principle of


echo shifting [18] to make the TE longer than the time

between RF excitation of successive slices. The MS-ES-EPI

sequence has been implemented at 3 T and used to acquire

MS data sets made up of nine slices at a rate of more than

4 volumes per second. With this approach, the TR is

significantly longer than the T2 relaxation time in brain

tissue, and the images consequently show similar contrast to

conventional MS EPIs acquired with short TR. This is in

contrast to 3D-PRESTO imaging [18], in which volumar

RF excitation is employed with very short TR values, such

that TRbT2, and steady-state transverse magnetization

is formed, thus causing different contrast behavior.

The presence of steady-state transverse magnetization

not only leads to a higher SNR per unit time but also

makes the signal more sensitive to motion and consequent

temporal instability.

The results shown in Fig. 4 indicate that the variation

of signal intensity with flip angle in the MS-ES-EPI sequence

follows that expected from simple saturation recovery in grey

and white matter when using a TR of 243 ms. This implies

that the magnetization from each slice is largely unaffected by

the RF pulses applied to other slices and also that the

dephasing of magnetization due to the unbalanced gradient

pulses applied in the slice direction is high enough to

adequately attenuate the signal during all inter-RF pulse

periods except that into which the echo is shifted. In this

work, we used gradient pulses that provided a minimum of

70 radians of phase dispersion across the slice. Following

initial RF excitation, the dephased magnetization persists for

one inter-RF pulse period before it is refocused, ready for

image formation, consequently imparting some diffusion

weighting to the signal. With a value of TR/NSL of 243 ms

and ks=14 mm�1 the b factor characterizing the diffusion

weighting is approximately equal to 1.3 s mm�2 and, so, will

cause negligible attenuation of the tissue signal, although it

will reduce the intravascular signal contribution [26].

The MS-ES-EPI sequence produced robust BOLD

activation in all five subjects studied with the simple

visual/motor task in which nine slices were acquired every

243 ms. This allows the nature of the BOLD response at a

temporal sampling rate of 4.1 Hz. The resulting average

BOLD response in the visual cortex to the 1-s visual

stimulus peaks approximately 4 s earlier than that due to the

longer 4-s stimulus and has a peak magnitude that is

approximately half as large. The haemodynamic responses

in motor cortex resulting from the subject’s button presses

were significantly different in form, following the short and

long duration visual cues, which made it difficult to

compare fully the timings of the responses.

The experimental work described here was carried out on

a 3-T scanner equipped with only a single RF channel, so

that it was not possible to apply parallel imaging in

conjunction with MS-ES-EPI. Using parallel imaging would

allow a reduction in the time required for each EPI

acquisition, which could be translated into an increase in

the number of slices acquired at fixed TR with a slight

reduction in the TE. Alternatively, it could be used with

echo shifting over more than one inter-RF pulse spacing to

produce a more significant increase in the number of sample

slices or a reduction in the TR.

Acknowledgment

This work was supported by MRC grant G9900259.

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