Invited Review

Functional Magnetic Resonance Imaging: A Reviewof Methodological Aspects and Clinical Applications

Jurgen Hennig, PhD,1* Oliver Speck, PhD,1 Martin A. Koch, PhD,2 andCornelius Weiller, MD2

This paper gives an overview of the recent literature onmethodological developments of functional magnetic reso-nance imaging (fMRI) and recent trends in clinical applica-tions. With the recent introduction of high-field systemsand methodological developments leading to more robustsignal behavior, fMRI is in a transition state from a re-search modality for use by experts to a standard procedurewith useful applications in patient management. Com-pared to the use in neuroscientific research, which is oftenbased on BOLD techniques alone, the application in pa-tients is distinguished by a multiparametric characteriza-tion of the brain using a combination of several techniques.Neuronal fiber tracking based on diffusion anisotropy mea-surements, in particular, has already turned out to providerelevant supplementary information to the BOLD-basedcortical activation maps.

Key Words: fMRI; methodology; clinical applications; EPI;spiral; high-field fMRIJ. Magn. Reson. Imaging 2003;18:1–15.© 2003 Wiley-Liss, Inc.

THE EXAMINATION OF BRAIN ACTIVATION by func-tional magnetic resonance imaging (fMRI) (1) has led toa revolution in neuroscience over the last decade. Therapid growth of the field is illustrated by Figure 1, whichshows the number of publications per year found by aMedLine (National Library of Medicine) search with thekey word phrase “fMRI AND brain.” The absolute num-ber of papers found varies strongly with the choice ofequally appropriate key words, but the overall trend isremarkably constant (including a mysterious dip in1997). It reflects a nearly linear growth of the field overthe years. Projections along this curve are of course

based on prediction: there may be continued growth(Fig. 1a), a saturation of the field once it has reached itslevel of maturity (Fig. 1b), or a decline (Fig. 1c). Giventhe rapid deployment of high-field scanners with fieldstrengths of 3 T and more, which are particularly wellsuited for fMRI, it seems safe to predict further growthat the same rate or higher over the next 4–5 years.

The sheer size of the field and the heterogeneity of itsmultiple aspects—from basic research into the physiol-ogy of brain activation to clinical applications in neuro-surgical operation planning—make it rather impossibleto provide a comprehensive overview within a singlereview article. Luckily, there are a number of reviewpapers available, which cover the recent literaturewithin a number of relevant fields of applications offMRI. Especially with respect to the physiological basisof fMRI, the reader is urged to look at the recent litera-ture (2–4). We will therefore concentrate on method-ological aspects, including measurement techniquesand field strength issues, and an update on some ex-emplary materials meant to be more illustrative thanexhaustive of the current possibilities of fMRI.

METHODOLOGY

Data Acquisition Techniques

BOLD-Based fMRI

Multislice echo planar imaging (EPI) covering the wholebrain as originally suggested by Ken Kwong in 1992 (5)can be regarded as the workhorse of current fMRI. Echotimes are tuned to the T2* of brain parenchyma using afield strength that maximizes the contrast-to-noise-ra-tio (CNR) of the BOLD response. Repetition times aretypically in the order of 2–3 seconds as a safe compro-mise to give appropriate temporal resolution whileavoiding signal loss by saturation. In the overwhelmingmajority of studies, gradient echo EPI is being used tomaximize the activation effect (6), although spin echoEPI has been shown to alleviate some problems likecontributions from larger vessels and misregistrationartifacts (7). A number of alternate, or in some aspectseven superior, techniques have been suggested for usein fMRI. It is, however, safe to say that EPI will continueto occupy a dominant role in the near future—if onlyaccording to the saying “If it’s not broken, don’t fix it.”

1Abt. Rontgendiagnostik, Section of Medical Physics, Freiburg, Ger-many.2Universitatsklinikum Hamburg-Eppendorf, Klinik und Poliklinik furNeurologie, Hamburg, Germany.Contract grant sponsor: Volkswagen-Stiftung; Contract grant sponsor:Deutsche Forschungsgemeinschaft; Contract grant sponsor: BMBF;Contract grant sponsor: European Union.*Address reprint requests to: J.H., Abt. Rontgendiagnostik, Section ofMedical Physics, Hugstetterstr. 55, 79106 Freiburg, Germany.E-mail: hennig@nz11.ukl.uni-freiburg.deReceived November 7, 2002; Accepted March 20, 2003.DOI 10.1002/jmri.10330Published online in Wiley InterScience (www.interscience.wiley.com).

JOURNAL OF MAGNETIC RESONANCE IMAGING 18:1–15 (2003)

© 2003 Wiley-Liss, Inc. 1

The current main competitor for EPI is spiral imaging.Spiral imaging has been known for many years (8).Recently, it has found new use in a variety of applica-tions, including BOLD-based fMRI (9,10). The primaryreason for reintroducing spiral imaging was the factthat it distributes the load on the gradient power sup-plies homogeneously over the data acquisition time. Incontrast, EPI requires an alternation of fast-gradientreversal at the end of each acquired k-space line, fol-lowed by a high-gradient amplitude in order to traverseto the other side as fast as possible. For a given gradienthardware, spiral imaging is therefore faster than EPI.This argument has meanwhile shifted somewhat due tothe fact that current gradient power supplies are suffi-ciently powerful, such that imaging acquisition timesare no longer limited by hardware constraints, butrather by limitations imposed by peripheral nerve stim-ulation or, ultimately, by signal-to-noise ratio (SNR)considerations. As a consequence, the assessment ofspiral imaging vs. EPI has shifted toward a comparisonof the inherent imaging properties of both sequences.Table 1 shows a comparison of the merits and pitfalls ofsome relevant properties of both techniques.

The inherent self-compensation against motion inspiral acquisition has been reported as a clear benefitcompared to EPI (9). Bulk motion of the whole head

during the scan is not a problem in either techniquedue to the short overall acquisition time. EPI has beendemonstrated to produce artifact-free images even dur-ing severe voluntary head motion. More relevant forfMRI are motion artifacts produced by blood flow. Forlarger pulsatile vessels, these may produce artifacts inEPI images that can appear superimposed on corticalareas of interest. Noise along the temporal axis of theexperiment is then increased, leading to false negativeresults. When the occurrence of noise coincides withthe timing of the stimulation paradigm, false positivefindings may also occur. Even more important may bethe effect of the self-compensating trajectories on phys-iological noise. The temporal noise along the time axisin a measurement in humans is considerably higherthan the temporal noise in phantom measurements(11). This is attributed to different factors, includingthermal noise by the volunteer, but also to signal fluc-tuations caused by variable regional flow in the brainand by long-range effects of respiratory motion (12,13).In comparative studies, this physiological noise hasbeen found to be lower in spiral imaging than in EPI,and the motional self-compensation of the flow-relatedfluctuations has been discussed as the main contribu-tion to this improvement (9,10,14–16). Reduction of themotional-dependent signal fluctuations in successivescans has also been achieved for EPI by using the signalencoding for the center of k-space and by additionalnavigator echoes incorporated into the sequence. Thisdynamic off-resonance in k-space (DORK) correctionhas been demonstrated successfully at 7 T (17). Aftercorrection, residual signal fluctuations were identicalin EPI and spiral images.

High-resolution BOLD imaging requires data acqui-sition with multiple excitations using segmented scans.Since interleaved spiral scans always start at the centerof k-space, the initial data points can be used as self-navigators for corrections of phase fluctuations (18).Navigator approaches have also been shown to be fea-sible in EPI by adding a non-phase-encoded signal tothe beginning and/or end of the echo train (17,19–21).Inherently, spiral scans should be more robust againstresidual fluctuations, which translate into a cloudybackground signal, which is not necessarily conspicu-ous in the final images. Residual nonreproducibilitiesin EPI will produce local ghosting artifacts, which mightaffect the fMRI data evaluation.

After so many advantages of spiral imaging, a fewdisadvantages should also be mentioned: the T2* sen-sitivity necessary to achieve the desired BOLD contrast

Figure 1. Numbers of publications referenced by MedLine forthe keyword phrase “fMRI AND brain” and extrapolated curvesfor continued linear growth (a), saturation (b), or eventualdecline (c).

Table 1Comparison of EPI and Spiral Imaging for fMRI

EPI Spiral

Imaging speed Fast Very fastField inhomogeneities Distortions BlurringIntra-acquisition motion Even-echo refocusing 180°-artifact, signal loss Self-compensatingSegmented scans Prone to artifacts by motional displacement Self-navigatingT2*-sensitivity Natural T2*-contrast Requires modificationsImage reconstruction Fast Somewhat slowerAcoustic noise Very noisy Moderately noisy

2 Hennig et al.

comes natural in an EPI experiment using linear phaseencoding (see Fig. 2). In a straightforward spiral exper-iment (“spiral out” in Fig. 2), however, the center ofk-space is acquired immediately at the beginning ofdata acquisition. Therefore, spiral fMRI requires a shiftof the data acquisition window. Alternatively, a spi-ral-in experiment can be performed, where data acqui-sition starts in the periphery of k-space (22). In eithercase, only half of the BOLD response is sampled, andthe sampling efficiency compared to EPI is reduced. Athigher fields, the optimum readout time for BOLD im-aging is shorter due to the increased BOLD effect. Forvery short TEs, spiral imaging may be preferred overEPI.

The current main obstacle for the introduction ofspiral imaging on a broader scale is image reconstruc-tion. Although very sophisticated reconstruction algo-rithms are known and available, spiral imaging is so farnot part of the standard scanner software in any sys-tem. The necessity for regridding prior to fast Fouriertransform (FFT) poses some time constraints leading toinherently longer reconstruction times, although itshould be mentioned that EPI with ramp sampling(continuous data acquisition during the reversal of thereadout gradient) also requires some, but considerablyless, regridding effort.

The 100 images per second and more that can bereconstructed with FFT are hard to achieve for spiralreconstruction on comparable computer hardware.Currently, the trend is to use the available computerpower for tasks like on-the-fly motion correction or real-time calculation of functional maps (23,24). With the

many thousands of images produced in a single fMRIsetting, the time constraints of image reconstructionare by no means academic, especially with the currentfast proliferation of sophisticated coil arrays, which re-quires an increase in computation power that is at leastproportional to the number of coils.

A final point often neglected in discussions on thepitfalls and merits of both techniques is the fact that thesmooth trajectory of spiral imaging leads to a quitedramatic reduction in scanner noise (25). Spiral scansare not only less noisy in terms of the sound pressureamplitude, but the discrete buzz of a spiral scan is alsoconsiderably more pleasant to the ear compared to thehigh-frequency hammering of EPI. Even sinusoidal EPI,which has fallen somewhat in disregard over the lastfew years, may find a revival due to the much lessunpleasant noise characteristics compared to standardEPI with trapezoidal gradients.

Signal Behavior in BOLD fMRI

Although BOLD-based techniques have been shown towork reliably for a huge range of applications, straight-forward BOLD imaging has some inherent problems.Most important is the fact that the desired sensitivity toblood oxygenation-related susceptibility effects inher-ently and invariably renders BOLD fMRI sensitive tounwanted susceptibility effects caused by macroscopicfield inhomogeneity effects. Such effects especially oc-cur at the interface between soft tissue and air, forexample, in the frontal and supratemporal regions ofthe brain. The resulting field shifts can be in the orderof 3–4 ppm. Exact theoretical and experimental datahave been published in Li et al (26). The data clearlyshow the most problematic areas above the nasal cavityand the sphenoid sinus and in the lower part of thefrontotemporal lobes. fMRI examination of areas likehippocampus and amygdala or the olfactory cortex arethus feasible, but notoriously difficult. These effects arebecoming increasingly severe at higher field strength.Consequently, it is not surprising that an increasingnumber of papers have appeared in the recent pastpresenting new approaches to improve the imaging be-havior with respect to the various effects related to localsusceptibility gradients. Below, the main problems andcurrent approaches to their solutions are discussed.

The effect of local field inhomogeneities depends onthe orientation of the susceptibility gradient with re-spect to the orientations of the readout, phase-encod-ing, and slice selection gradients. From the susceptibil-ity-induced field maps in Li et al (26) it is clear that theeffects will always affect all three gradient orientations.The effects are minimized if the local field gradient isoriented along the direction of the readout gradient inEPI. A local gradient in the phase-encoding directionwill lead primarily to image distortions. After superpo-sition to a standard anatomical data set, a nonlinearmismatch will occur. The latter is typically acquiredwith an magnetization prepared rapid acquisition gra-dient echo (MPRAGE) sequence, which is used to iden-tify the neuroanatomical position of activated areas.The extent of this mismatch can be easily in the order of1–2 cm at 1.5 T even in quite innocent-looking areas

Figure 2. BOLD signal change �I as a function of the readouttime TE for an activation experiment with a BOLD change inR2* by 1 (1/s) for T2* � 60 msec (thick line) and T2* � 30 msec(dotted line). It is demonstrated that with a decrease in T2* theBOLD effect decreases and the maximum effect is achieved ata different TE, corresponding to the T2* of the tissue. Theschematic schemes on top of the graph represent the samplingorder of spiral-in, spiral-out, and EPI sequences; the thicknessof the bar represents the distance k to the k-space center. Formaximum effect, the center of k-space should be acquired atthe TE with maximum BOLD effect.

Methods and Clinical Applications of fMRI 3

(Fig. 3). Typical errors associated with this mismatchare a shift of observed areas of activation to the wrongside of a sulcus, which can severely compromise theallocation of activation. BOLD effects from veins, whichare located in the sulcus, can also appear to be shiftedinto the cortex, thus suggesting true cortical activation.EPI distortions very often are not easily discernible,since standard EPI normally places the phase-encodinggradient along the vertical axis. The resulting transver-sal images will still preserve their inherent bilateralsymmetry. The extent of the mismatch becomes appar-ent upon switching of the gradient orientations (Fig. 3).The problem becomes increasingly severe at higherfields; therefore, methods for distortion correctionshave found increasing interest (27–33,35). All of these

approaches are based on measurements of local fieldvariations by additional field map measurements inte-grated into the examination. Most often these fieldmaps are represented by an off-resonance frequencycharacterizing the field inhomogenity at a given loca-tion. This offset can then be used to transform the fMRIdata onto a true reference frame. A more recent andmore elaborate approach is to actually measure thepoint-spread function of each pixel along the phase-encoding direction. In a recent paper (33) it could bedemonstrated that this allows for correction in areas ofsevere distortions, where a simple field map will runinto ambiguity problems.

Many of the commonly used data evaluation pack-ages contain quite sophisticated procedures for nonlin-

Figure 3. Images representing EPI distortions. Arrows in each image represent the direction of the phase-encoding gradient. Themismatch of corresponding locations shows that activation may jump across hemispheres (a), move from a sulcus into graymatter (b), is totally misplaced across the temporal lobe (c), or moves from the cortical surface deep into a sulcus (d and e).

4 Hennig et al.

ear co-registration of fMRI images to a standard ana-tomical data set. It should be noted, however, that thesemap the MR data after merging the fMRI images to astandard anatomical data set, which is commonly ac-quired with MPRAGE for good gray/white-matter con-trast. Errors in the merging of fMRI images to theMPRAGE data will not be corrected.

Field maps have also been used for corrections ofspiral images. Since off-resonance effects in spiral im-aging will not lead to distortions, but rather to blurring,the corrections cannot be described by a simple pixelshift, and thus require correction of the raw data priorto image reconstruction. Consequently, such algo-rithms are already built into the image reconstructionprocess, which adds to the already high calculationload during the examination.

Misregistration will also occur in the slice selectiondirection, producing more or less severe dents in theselected slice. Areas that are perfectly visible in thecorresponding anatomical image can disappear in EPIfor this reason alone. The size of the dent will decreasewhen the pulse bandwidth is increased; therefore, it isprudent to use rather hard pulses. Spectral-spatial wa-ter excitation pulses used to suppress fat signal inher-ently require pulses with high bandwidths; therefore,this effect is only of minor importance at 1.5 T. At higherfields, however, the pulse power is more and more lim-ited by SAR considerations, but also by hardware con-straints regarding the radio-frequency (RF) peak power;therefore, this problem is expected to be increasinglysevere.

In addition to misregistration artifacts, susceptibilityeffects will also cause signal attenuation, especially if itoccurs in the direction of the slice selection gradient.This not only will reduce the overall signal intensity, butalso may lead to systematic errors in quantitative mea-surements (34). Dephasing in a susceptibility-inducedgradient will not only lead to a reduced signal ampli-tude, but also to a shorter T2*: with the echo timescommonly used for BOLD fMRI in homogeneous re-gions, the signal in these areas will also be sampled ata suboptimal TE. The observed BOLD effect will thus befurther reduced (see Fig. 2). The attenuation as a func-tion of the dephasing gradient is given by a sinc func-tion. Using thinner slices has been shown to lead to atremendous improvement of this problem (36); there-fore, 5 mm should not be exceeded already at 1.5 T,with 2-mm slice thickness even quite problematicareas like the amygdala suddenly become easily visible.

A rather subtle effect, which has only recently beenpublished, occurs when the susceptibility gradient isoriented in the phase-encoding direction (37). Superpo-sition with the gradient used for image encoding willthen lead to a shift of the effective time of the phase-encoding zero point. The effective TE will thus be pro-longed or shortened depending on the relative sign ofthe susceptibility gradient with respect to the phase-encoding gradient order. This can also lead to a reduc-tion in the observed BOLD effect.

Comparing the severity of susceptibility effects in thephase-encoding vs. the slice selection gradient, itshould be noted that susceptibility effects in the phase-encoding direction will only lead to a mismatch of the

effective echo time. No additional signal attenuationcomparable to the through-slice dephasing will takeplace at least as long as the susceptibility-dependentgradient does not lead to a shift of the signal out of theacquisition window. For otherwise identical conditions,the additional signal attenuation occurring in the sliceselection direction is thus avoided. In addition, the sus-ceptibility-dependent dephasing will scale with thevoxel size. Typically, the slice thickness is larger thanthe in-plane resolution; therefore, susceptibility effectswill be most severe across the slice.

Least problematic are susceptibility effects in the di-rection of the readout gradient, where they will lead tosome echo shifting, resulting in a so-called 180° arti-fact, which can be corrected for by appropriate postpro-cessing algorithms.

Signal attenuation alone will compromise the sensi-tivity of BOLD experiments in affected regions. Theproblem is worsened by the fact that the strong localsignal variation caused by these gradients will lead toan extreme sensitivity to motion in these areas: evensmall and weakly stimulus-correlated motion can thuslead to false positive activation effects (40). The noise ofthe data along the time axis will be considerably in-creased in these areas, which may also lead to falsenegative results.

In addition to the parameter variations used to im-prove the standard sequences (thin slices, short echotrains), several methodological approaches have beenproposed recently to improve fMRI in regions withstrong susceptibility effects. The most commonly usedapproach is the so-called z-shim technique to compen-sate for susceptibility effects by addition of appropriatebalancing gradients in the direction of the slice selec-tion gradient (41,42). In its generic form it uses severalconsecutive data acquisitions where the compensationgradient is varied around its nominal value by anamount dependent on the steepness of the expectedsusceptibility gradient. Although z-shimming leads to aprolongation of the total acquisition time by the neces-sity to acquire multiple images, it has shown to consid-erably improve fMRI examinations in problematic ar-eas. Recently the MESBAC sequence has beenproposed, in which multiple data with four differentz-shim values are acquired in a single data acquisition(43).

In a comparison of using thin-slice EPI vs. z-shim, ithas been demonstrated that the use of thinner slicesmay be the preferred option to maximize sampling effi-ciency for fMRI in problematic areas (38). Using thinslices and coronal orientation has thus been demon-strated to allow functional studies of the amydala, anarea that has been notoriously difficult to examine byBOLD-based fMRI (44).

Z-shimming has also been used to deal with inhomo-geneities in the direction of the phase-encoding gradi-ent, where acquisitions with three different compensa-tion values have been demonstrated to lead toconsiderable improvements of the measured activationsignals in pertinent areas (37).

A slightly different concept to deal with susceptibilityeffects is to acquire images with more than one echotime. Single-shot multi-image EPI allows the measure-

Methods and Clinical Applications of fMRI 5

ment of T2* decay directly (45). This can be used forabsolute quantitation of the BOLD effect. Susceptibilty-dependent changes in T2* can be accounted for byoptimized data analysis on a pixel-by-pixel basis. Para-metric mapping has thus shown to be more sensitivethan conventional EPI (46). Parametric T2* mappingwith multiple spiral readouts after a single excitationhas also been demonstrated (47)

A similar approach uses the spiral-out, spiral-intechnique (48), which combines two measurementswith complementary trajectories but identical echotimes. With appropriate postprocessing this is demon-strated to retrieve BOLD signals in areas of high sus-ceptibility-dependent signal loss.

Even when quantitative T2* measurements are per-formed, the BOLD signal alone is still difficult to trans-late into a measure of neuronal activity. An effectivemeasurement strategy to calibrate the BOLD responseis to use hypercapnia (49–51). This has been demon-strated in several studies to give a much more robustmeasure of cortical activity than the direct value of theBOLD effect (52–54).

Perfusion-Based fMRI

BOLD-based fMRI uses deoxyhemoglobin as an intrin-sic contrast agent. The susceptibility effect induced bythe magnetic iron complex affects multiple protons inthe microscopic environment around the erythrocytesand thus acts as a multiplicator. Even very subtlechanges in oxygenation will thus lead to signal varia-tions by several percent. BOLD techniques are thusinherently more sensitive than techniques for directmeasurement of activation-dependent changes in bloodvolume and blood flow.

A disadvantage of BOLD-based techniques is theirrather complex dependence on changes in regional ce-rebral blood flow (rCBF), regional cerebral blood volume(rCBV), and regional cerebral metabolic rate of oxygenconsumption (rCMRO2). An increase in rCBF alone willlead to an increase in the BOLD signal; an increase inrCBV alone will lead to a signal reduction. The BOLDeffect therefore will measure the residual of these an-tiphasic effects. In the healthy, often young volunteersused in most fMRI studies, the BOLD effect has beenfound to be rather ubiquitous and consistent. TheBOLD response has been demonstrated, however, to bemodulated or even inverted by sedatives like pentobar-bital (55). A negative BOLD effect has also been ob-served in early infants (56). The BOLD effect seems alsoto decrease with age (57). In patients with internal ca-rotid artery (ICA) steno-occlusive disease, a reductionor even total loss of the BOLD signal has been observedas a consequence of a decreased vasodilatory reservecapacity (58). Especially for patient examinations theBOLD effect alone is thus not necessarily a reliableindicator of neuronal activation.

Direct measures of the activation-dependent changesin blood flow have therefore found increasing interest inorder to distinguish between signal changes caused byflow changes from BOLD effects. A wide variety of tech-niques based on arterial spin labeling (ASL) have beenproposed and are discussed in recent review articles

(59,60). A common problem of ASL techniques is thefact that the perfusion-dependent signal attenuationcritically depends on the spatial and temporal relationbetween the tagging area and the image position. Theeffect of arterial tagging is optimized when the timedelay between tagging and data acquisition is in theorder of the T1 of blood (�1 second). The experimentwill therefore be optimized only for some particular sec-tion of the brain. Although various approaches for mul-tislice applications have been suggested, the quality ofthe flow estimates will depend on the slice position. Thevolume coverage will thus be compromised. Typically,measurements are performed for a single representa-tive slice or for a few slices, for which the tagging delayis within a reasonable range. Whole-brain applicationof perfusion MRI has so far been unfeasible. In additionto the reduced volume coverage, perfusion-based MRIis also much less sensitive compared to BOLD-basedtechniques. Consequently, flow-based fMRI measure-ments have been performed so far primarily for physi-ological studies on the mechanism of the coupling be-tween neuronal activity and the hemodynamicresponse. Especially for comparison of the temporalrelation between the BOLD signal and the changes inblood flow, dual-acquisition schemes have been pro-posed, which allow a simultaneous measurement ofboth effects (61,62).

ASL techniques benefit from the increased SNR athigher field strength (63,64), although the overall effectseems to be somewhat compromised by increasedphysiological noise (63).

Other Mechanisms

Neuronal activation is known to produce a variety ofreactions on a metabolic and physiological level. Theunique sensitivity of MR to a wide range of pertinentparameters has led to a number of recent studies toexamine other aspects of cortical activation apart fromthe hemodynamic response. New results of MR spec-troscopy (MRS) acquired at higher fields have signifi-cantly improved the understanding of the metabolicpathways covering the sudden increase in energy de-mand (65).

The very indirect nature of the BOLD effect and thelimitations of perfusion imaging techniques have led toa number of studies, in which the response of otherpotentially interesting parameters to cortical activationhas been examined. Changes in the apparent diffusioncoefficient during activation have been reported andinterpreted as consequences of neuronal swelling(66,67). However, the observed effect is very small interms of noise, a problem that has so far limited theapplication of such measurements. Measurements ofintravoxel incoherent motion (IVIM) using the sameStejskal-Tanner technique, but with reduced b-factor,have recently been shown to also lead to observableeffects (68). The problem of such an approach is givenby the fact that even at best, the signal change inducedby dephasing gradients is limited by the partial volumeof blood. In addition, the IVIM gradients need to beextremely well tuned to the actual flow velocities. If theb-factor is too low, no effect will be seen; if it is too

6 Hennig et al.

strong, the blood signal will have vanished already atrest.

A variety of other MR-sensitive parameters have alsobeen used to detect activation-dependent signalchanges. Measurements with the so-called CRAZED se-quence have been demonstrated to also be sensitive tocortical activation (69), although it remains unclearwhether the observed effects are due to changes in themultiquantum coherences or a side effect of othermechanisms of a classical nature, which are alsoknown to produce signals when measured by theCRAZED sequence. The relative signal changes havebeen reported to be rather large and in the order of 10%.Since the CRAZED signals are very small to start with,the effect-to-noise ratio is still poor and makes the ex-periment rather insensitive for use in fMRI.

A very interesting area of research is the direct obser-vation of the effect of the electrophysiological corticalsignals. The currents induced around neuron bundleslead to changes in the local magnetic field. Recent sim-ulations and phantom experiments have shown thatthe resulting effects may be at the border of detectabil-ity by appropriate MR techniques (70,71). A practicalproblem to verify such direct field modulations may bethe difficulty to distinguish the effect from a conven-tional BOLD effect: both rely on local field variationsand, consequently, will require similar measurementtechniques.

Earlier studies have shown an improvement of fMRIeffects when magnetization transfer contrast is applied(72). Since the intravascular MT effect is low andsince—at least at 1.5 T—the intravascular signal dom-inates the BOLD response, one would indeed expectsuch an improvement. For the same reason the MTeffect itself should also be sensitive to CBV changes.This could, however, not be confirmed in later studies,indicating that the proton exchange between blood andtissue may be sufficiently fast to mix the T1 relaxationrates of blood and tissue (73).

Field Strength Issues

BOLD Effect vs. B0

The current development in high-field MR has been to alarge extend due to the success of BOLD-based fMRI.Susceptibility effects are increasing with fieldstrengths; therefore, it has been expected already in theearly days of fMRI that the BOLD change in �R2* willincrease with increasing field strength. As shown inTable 2, this increase is indeed reflected in the mea-sured data. Especially at higher fields between 4 and 7T the increase in �R2* has been reported to be morethan linear.

Table 2 shows an overview of literature data on fieldstrength comparisons. Comparing the reported valuesof �R2* for each study pairwise, an increase in theBOLD-dependent T2* change is clearly apparent. The

Figure 4. R2* vs. field strength based on data from the liter-ature.

Table 2Literature Data on Field Strength Comparisons for Parameters Relevant for fMRI [�S represents the size of the BOLD-effectcorresponding to �S�exp(�R2*/R2*), �E is the percentage signal change upon activation, (v) and (t) represent the vessel- and tissue-parameters respectively.]

T2(blood)T2(*)

(tissue)�R2* �S �E Reference

4T 15 Turner et al (74)1.5T 4–73T 1.76 � 0.05 (7.6) 10.1–11.5 Bandettini et al (75)1.5T 0.84 � 0.05 (5.46) 6.5–8.24T 20.2 31.7 5.02 � 0.4 (v) 3.52 15.1 (v) Gati et al (76)

1.09 � 0.07 (t) 3.3(t)1.5T 54.6 69.4 3.06 � 0.3 (v) 2.25 18.4 (v)

0.32 � 0.05 (t) 1.9(t)9.4T Arterial 40.8 � 3.4 38.6 � 2.1 Lee et al (77)

Venous 9.2 � 2.37 T Venous 6.8–13.1 25.1 � 3.5 1.46 � 0.32 3.73 �15 Yacoub et al (78)4 T T2*�23.5 41.4 � 5.5 0.68 � 0.09 2.86 �63T 49 2.9 Kruger et al (79)1.5T 65 2.83T 41.6 � 4 0.9 � 0.1 3.81 Speck et al (80)1.5T 63.3 � 6 0.54 � 0.07 3.48

Methods and Clinical Applications of fMRI 7

variation of �R2* values themselves between the stud-ies is to be expected due to the different stimulationparadigms used. Figure 4 shows a plot of the R2* valuesvs. field strength. Although a direct comparison of theseliterature values has to be taken with a grain of salt dueto the difference in experimental conditions for the var-ious measurements, the values show a quite nice linearfield dependence corresponding to

R2*(1/s) � 8.5(�1.8) � 4.6(�0.5)*B0

Converting the reported parameter changes into aBOLD effect, the reduction of T2* will lead to a reducedincrease in the BOLD effect. The maximum BOLD effectwill be observed when TE is equal to T2* of the tissue.Under this condition, the relative signal change will begiven by �S � exp(�R2*/R2*)�1. For field strengths upto 3 T, no significant increase in �R2*/R2* was found(79,80), in contrast to earlier reports (75). Even at veryhigh fields, the reduction in T2* will lead to only amoderate increase in �S, which is somewhat in dis-agreement with the quite substantial differences in theobserved maximum BOLD effect (78). In any case, theincrease in SNR at the higher field is demonstrated tolead to a substantially increased BOLD sensitivity.

More important than the absolute size of the BOLDeffect is the change in mechanism observed at higherfields. At 1.5 T it has been demonstrated that the maincontribution to the observed BOLD effect is due to in-travascular signals (61). At higher fields, the T2* ofblood is dramatically reduced (77,78). The low T2* val-ues in predominantly vascular regions observed in Leeet al (77) demonstrate indeed that the observed BOLDsignal at higher fields will be more and more dominatedby parenchymal signal contributions.

The dramatic reduction of T2 of blood is a conse-quence of the dynamic susceptibility effect, which leadsto irrecoverable signal loss for spins diffusing arounddeoxygenated erythrocytes. This effect therefore scaleswith (1 – Y), where Y is the blood oxygenation and thesquare of the field strength. T2 (and T2*) will thus bereduced by a factor of more than 20 when going from1.5 to 7 T at a constant Y.

The increased BOLD sensitivity afforded by thehigher field will only lead to an increased detectionpower when the noise along the time axis remains con-stant. Already at 1.5 T, and even more so at higherfields, it has been demonstrated that the noise alongthe time axis is considerably higher than the in-planeSNR and dominated by physiological noise contribu-tions. The published data suggest that the physiologicalnoise will increase with field strength (12,15–17).

In conclusion, there are still a large number of unan-swered questions about the field dependence of theBOLD effect. Nevertheless, the data presented so farclearly indicate a significant increase in BOLD sensitiv-ity, as well as in the specificity of the effect to the actuallocation of the activated cortex.

Methodological Challenges at Higher Fields

The discussion above has shown that the reduced T2*at higher fields necessitates a reduction in the effectiveecho times necessary to optimize the CNR. In a way,

this is fortunate, since the macroscopic susceptibilityeffects described previously scale linearly with fieldstrength. Signal attenuation and image distortion,which is quite tolerable at 1.5 T and 40- to 50-msececho times, will become dramatic at higher fields withidentical TE. Lowering TE reduces these artifacts, but ofcourse will lead to quite severe requirements with re-spect to gradient amplitudes and switching times. At 3T, standard single-shot EPI can still be realized withoutoverly severe artifacts. At 7 T, however, the dramaticallyreduced T2* requires the use of segmented data acqui-sition. Reducing susceptibility artifacts by faster andstronger gradients will eventually be limited not only byhardware considerations, but also by the tolerable lim-its of neuronal stimulation. In addition, faster data ac-quisition will lead to increased acquisition bandwidth,and thus a reduction in SNR. Therefore, a brute-forceapproach to reduce artifacts by faster data acquisitionis invariably accompanied by a sacrifice of a more orless substantial part of the higher SNR afforded by thehigher fields. These considerations alone should illus-trate that fMRI at higher fields requires a more subtleapproach than a mere scaling up of the pertinent mea-surement parameters.

An additional consideration follows from the in-creased dominance of the dynamic susceptibility effectat higher field strength (81). This effect will lead to areduction in T2 as well as in T2*. Therefore, BOLDeffects have been measured with spin echo sequences,which avoid the susceptibility artifacts inherently ac-companying T2*-based techniques (39,82).

A further problem at higher fields is the increased B1inhomogeneity caused by the fact that the wavelengthis in the order of the size of the anatomical structures.This leads to dark spots due to dielectrical absorptionas well as hot spots due to dielectrical resonances. Thesignal intensity will thus show considerable variationsacross the head, with signal variations by a factor of 2.5and more (83). The signal variations caused by these B1inhomogeneities considerably hamper a straightfor-ward statistical analysis and have so far severely lim-ited the feasibility of whole-brain studies at fieldstrengths exceeding 4 T. The future development ofultrahigh field will consequently be dependent on fur-ther technical developments leading to a more homoge-neous image quality across the brain. This may beachieved using multiple coil arrays, which at least the-oretically should be feasible at higher fields (84).

Clinical Applications of fMRI

fMRI covers all domains of systemic neurosciences. It isjust about to enter the domain of clinical applications.Leaving aside the impact of diffusion and perfusion MRIin everyday stroke care in the triage for thrombolysis,fMRI’s role in clinical application ranges from under-standing of diseases and disorders to presurgical eval-uation and assessment of therapeutic strategies andprognosis. Characteristic for the recent development offMRI in clinical applications is the integration of activa-tion measurements with BOLD-based fMRI with othertechniques in order to get a comprehensive functional,morphological, and microstructural assessment of the

8 Hennig et al.

pathologies under study. In particular, fiber tract map-ping on the basis of diffusion anisotropy measurementsis becoming increasingly important for an assessmentof the function and malfunction of cortical networks.

Without attempting to give a comprehensive over-view, we highlight some interesting aspects.

The rapid rise of functional imaging has greatly facil-itated the study of the brain mechanisms underlyingrecovery of lost function after damage. Some aspects ofthe organization of the normal human brain are essen-tial for understanding its reorganization after damage:brain functions may occasionally be localized in dis-tinct brain regions (e.g., visual perception of motion inV5 or MT ( 85)). However, more complicated abilities canonly be understood if they are regarded to be repre-sented in widespread bilateral and parallel working net-works, depending on a highly coordinated timely inter-action for a proficient level of performance (86). In acurrent hypothesis, functional loss as in the case ofstroke can be seen as a disconnection phenomenon.Recovery may mean reconnection or better recoordina-tion of a whole set of areas, each of which may subservea certain aspect of the function but requires the coher-ent support of the others to reach a high degree ofproficiency (87). Although there are remarkable inter-individual differences (88), a common pattern in theanatomy of recovery after a brain lesion can be identi-fied (89–91). In fully recovered patients, the primaryrepresentation areas (e.g., M1, the motor cortex) remainthe first line of activation, as long as they are spared,even if their efferent fiber tracts (e.g., the corticospinaltract within the internal capsule) are undercut. De-pending on the site of the lesion, a lateral extension ofM1 into the face representation area is noted whenmoving the recovered hand. In addition, patients acti-vate the entire sensorimotor system in both hemi-spheres more than healthy subjects, including second-ary motor areas in the premotor cortex (SMA and PmD),additional motor-related areas in the parietal cortexand the frontal operculum, and additional supramodalareas in the dorsolateral prefrontal cortex and the an-terior cingulate cortex. Longitudinal studies point to aninitial stronger activation (recruitment) of the intacthemisphere with a gradual normalization of the activa-tion pattern over time (92–96). One way of assessing thefunctional significance of these reorganizationalchanges is the use of correlational designs in longitu-dinal studies. An intense physiotherapeutic/behavior-istic treatment (constraint-induced movement therapy)over a fortnight in chronic stroke patients reduces dis-ability and use of the affected hand, which sustainsafter the treatment has stopped at least for the next 6months. This functional improvement is accompaniedby an increased excitability of primary motor cortex,due to a focal disinhibition (97–99) by transcranialmagnetic stimulation. Musso et al (100) investigatedcorrelations between the training-induced improve-ment of comprehension in stroke patients with chronicaphasia and changes in the activation pattern. Theyfound a significant correlation of the improvement offunction with an increase of activation over time in theright-sided homologue of Wernicke’s area in the lefthemisphere. This still is just correlational evidence. Jo-

hansen-Berg et al (101) used repetitive magnetic stim-ulation in stroke patients to interfere with the action ofbrain regions, which beforehand were identified byfMRI as active during movement of the recovered hand.Magnetic stimulation of the ipsilateral dorsal premotorcortex (PmD) impaired the function of the recoveredhand in their set of patients to a higher degree than innormal subjects, illustrating a functional importance ofthis area in the recovery. Thus, fMRI is able to illustratethe changes in the brain during rehabilitation. But alsothe effects of drugs can be studied. Application of asingle dose or a 1-week treatment with a selective sero-tonin-reuptake inhibitor increases the activeability ofthe motor system, including M1, measured with fMRI innormal subjects (102), as well as in stroke patientscorrelating with improvement of function (103).

Some studies are under way to assess the predictivevalue of early fMRI for the assessment of prognosis. Aproblem here (under many), as in all longitudinal pa-tient studies, is the dependency of the BOLD signal onthe performance rate of the patient, the latter of which(hopefully) improves during the recovery process. A wayof dealing with this is using a passive paradigm that ismore or less independent of the patients’ performance(e.g., passive movement, which activates almost identi-cal brain areas as the corresponding active movement(92,95,104)). In preliminary reports it looks as if a wide-spread activation induced by a passive movement of theparalytic limbs, which includes M1 of the damagedhemisphere, relates to a good recovery after 6 months(105).

Combination of BOLD-Based fMRI With Fiber Tracking

In recent times, fMRI has been amended by new meth-ods for assessing tissue structure. In tissues where thecells in a volume element of the order of 1 mm3 are notrandomly oriented, water diffusion can appear aniso-tropic, such that the diffusion process cannot be de-scribed by a scalar diffusion coefficient, but rather by atensor. This offers a unique opportunity to probe tissuestructure with diffusion tensor imaging (DTI)(106–108). A diffusion tensor map is calculated from anumber of diffusion-weighted images that differ by thedirection of the diffusion gradients. The most commonlyused rotationally invariant scalar measures derivedfrom the diffusion tensor are the direction-averageddiffusivity, trace(D)/3, and the fractional anisotropy(FA) index (109). If fiber orientations are to be assessed,the tensor is often expressed in terms of its eigenvaluesand eigenvectors. Various MRI techniques may be usedto acquire maps of the diffusion tensor of water. Themost widespread technique used for DTI measure-ments is EPI. Diffusion sensitivity is commonlyachieved by a magnetization preparation period thatcontains strong diffusion gradient pulses (110). How-ever, the incorporation of diffusion weighting gradientsin an imaging sequence can lead to image artifacts ormay render the sequence highly susceptible to patientmotion. DTI experiments are often time-consuming be-cause of the low SNR of diffusion-weighted images andthe necessity to acquire at least seven images with dif-ferent diffusion weighting. One type of application is the

Methods and Clinical Applications of fMRI 9

assessment of tissue microstructure at a given locationin the brain. Voxel-based morphometry is used to com-pare groups of patients or patients with a control groupto assess anatomic features of a disease (111). A newapproach is the use of FA maps as the basis for mor-phometry. Alterations in the diffusion tensor have suc-cessfully been related to schizophrenia (112–114), epi-lepsy (115,116), stuttering (117), dyslexia (118), anddemyelination disorders (119,120). In most of thesestudies, the anisotropy of diffusion is evaluated. The FAof diffusion reflects the coherence of the direction offibers within each voxel. Lower FA values can indicatedecreased fiber coherence or myelination defects(115,116,121). Voxel-based morphometry techniquesused to compare the diffusion tensor-derived tissueproperties between patient and control groups encoun-ter difficulties arising from normalization problems. Inaddition to common problems arising when normaliz-ing a pathologically changed brain onto a standard nor-mal brain, care has to be taken to preserve the tensorinformation in the normalization process (117,122).

A recent DTI study identified a disconnection betweenspeech-relevant brain areas as a mechanism in devel-opmental stuttering. The generation of fluent speech isdependent on the precise temporal synchronization of

phonatory and articulatory muscle groups. Develop-mental stuttering presents with involuntary repeti-tions, prolongations, or arrests of sounds in about4–5% of all children at three to five years old. Sponta-neous remission is frequent, but the impairment per-sists after puberty in about 1% of the population (123).A number of divergent theories could be reconciled by adisconnection of speech-related cortical areas in the lefthemisphere. Sommer et al (111) tested this hypothesiswith voxel-based morphometry on FA derived from DTIin 15 adults with persistent developmental stutteringand 14 closely matched controls. In the stuttering pop-ulation, the authors observed significantly lower FA inthe Rolandic operculum of the left hemisphere only (Fig.5). This region of reduced FA encompasses the whitematter immediately below the sensorimotor represen-tation of the oro-pharynx at the level of the centralsulcus (Brodmann’s area 43), the ventral extension ofthe central sulcus, and the inferior arcuate fasciclelinking speech motor areas with temporal and frontallanguage areas (124). It is thus conceivable that dis-turbed signal transmission through the left Rolandicoperculum impairs sensorimotor integration necessaryfor fluent speech production.

Figure 5. Voxels with significantly lower FA of diffusion in the persistent developmental stuttering (PDS) group than in the controlgroup, thresholded at P � 0.001 (uncorrected) for visualization purposes, superimposed on a normalized T1-weighted anatomicalimage of a representative volunteer. The lesion is situated at the Rolandic operculum, immediately above the Sylvian fissure.

10 Hennig et al.

Presurgical Mapping

The use of BOLD-based fMRI for presurgical mappinghas been one of the first clinical applications for fMRI.In spite of multiple efforts to develop standardized and

reproducible paradigms for routine use, there is a cer-tain reluctancy to use fMRI as a presurgical tool. We aretoo uncertain about the very nature of the signal andabout the physiological meaning of activation foci mea-sured with fMRI. In a careful pros and cons weighting

Figure 6. Fiber orientation map of the optic chiasm, derived from diffu-sion tensor data. The yellow lines show the projection of the directioncorresponding to the largest tensor eigenvalue onto the imaging plane.Tensor data were acquired using a turbo STEAM DTI sequence(46,47,130,131) and thresholded according to the intensity in the under-lying T1 image. Red, green, and blue colors represent the same directioninformation (magnitude of left-right, anterior-posterior, and superior-inferior component, respectively), but the color intensity is scaled with thesquare root of the FA index. The original image resolution, 2 � 2 � 3 mm3,was interpolated to 1.5 � 1.5 � 2 mm3. The optic nerves are shown at thetop.

Figure 7. Composite figure of fMRIand DTI in a 71-year-old patient witha low-grade astrocytoma in the lefttemporal lobe, presenting with apha-sia and epileptic fits. The fMRI acti-vation during finger tapping is shownin green; DTI fiber-tracking resultsare shown in red (top row and bottomleft). In the bottom right image, thepredominant fiber direction (diffu-sion tensor eigenvector correspond-ing to largest eigenvalue) is visualizedwith a red-green-blue color scale(courtesy of Anna de Simone, Neurol-ogy, Hamburg, Germany).

Methods and Clinical Applications of fMRI 11

scientific environment, fMRI has been extremely help-ful. But is the technique foolproof enough for wide-spread use in clinical diagnostic and therapeutic deci-sion making? An absolute requirement is a profoundand detailed understanding of the potentials and pit-falls of this technique on the part of the treating physi-cian. As brain function is organized in networks, aspointed out above, sparing a focus of activation duringoperation does not necessarily mean preservation offunction and vice versa. Nevertheless, the potential useseems very attractive for clinicians, and we shouldmake every effort to improve the quality and interpre-tation of these measurements.

Standard procedures for presurgical mapping withfMRI (e.g., in epilepsy surgery) are being developed(125), which include fiber tracking as well as BOLD-based fMRI. An example of a fiber orientation map de-rived from DTI data is shown in Figure 6. Recent studieson tumor patients (126,127) concentrate on the assess-ment of the tumor position relative to white matterfibers. Robust fiber-tracking tools should significantlyfacilitate this application. A combined example usingfMRI and DTI fiber tracking in a presurgery tumor pa-tient is illustrated in Figure 7.

Moreover, maps of fiber connections in the humanbrain may be used as a priori knowledge for the inter-pretation of functional neuroimaging data. These ap-proaches are expected to contribute significantly to thedevelopment of models of brain function. Fiber map-ping might prove useful to specify the network modelsthat are required for effective connectivity studies(128,129).

CONCLUSIONS AND PERSPECTIVES

fMRI has gone a long way since its first introduction byOgawa in 1990 (1). In terms of methodological and tech-nical developments, the introduction of high-field scan-ners with field strengths of 3 T and beyond and opti-mized acquisition techniques are providing thegroundwork for conversion of fMRI from a research mo-dality for experienced experts to a more and more ro-bust tool for clinical applications. The possibility toobserve cortical activation in unprecedented temporaland spatial resolution has led to an explosive growth inneuroscientifc applications. The unique informationprovided by the technique has led to the creation ofwhole new fields of brain research. The very sameuniqueness has also led to the situation that most oftenthere is no gold standard against which the validity offMRI results can be verified. In this sense, every fMRIexperiment has to be taken at face value and is there-fore by definition a success. As long as the result ofsuch an experiment is only the confirmation of a scien-tific hypothesis, this situation is not likely to changevery rapidly. Even controversial results on apparentlyidentical paradigms can be explained by differences inexperimental conditions or heterogeneity between pa-tient groups. The human brain is not a mechanicalmachine; therefore, variations between experimentalresults are to be expected, especially when going be-yond the test of primary sensory activation. Controver-

sial results in neuroscientific applications therefore donot necessarily cast doubt on the validity of results, butare welcomed as a stimulating basis for discussions.

The requirements to validate the findings of fMRIstudies increase dramatically in clinical applications,where the results have a very clear and significant im-pact on patient management. When the health of apatient is at stake, pressure increases to make surethat a measured focus activation really is where andwhat it seems to be on the output of the fMRI postpro-cessing software. False negative results caused by achange in the coupling between neuronal activity andthe observed hemodynamic response need to be de-tected as such. The same applies to false positives re-lated to stimulus-correlated extrinsic signal modula-tions, which can be caused by motion, but also by moresubtle effects like homogeneity changes due to respira-tory motion. Susceptibility-dependent misregistrationhas to be corrected. Misplacement of a focus of activa-tion across a sulcus may lead neuroscientific theoriesastray for a while, which may be deplorable but notnecessarily dramatic. The same misplacement will havevery severe consequences when used as the basis forneurosurgical treatment. The good news is that solu-tions exist and have been published for many of therelevant issues related to the robustness and reliabilityof fMRI. Bringing these tools from the hands of themethodological experts into the day-to-day use in clin-ical and scientific applications is the next logical andnecessary step.

A key issue for clinical applications is a distinctionbetween effects caused by pathological changes of neu-ronal processing vs. changes in the hemodynamic re-sponse. The BOLD signal is sensitive to both; therefore,a BOLD-based activation experiment alone cannotmake the distinction. Treatment can and will be vastlydifferent between pathologies, which are regarded to beof neuronal origin vs. pathological hemodynamicchanges. Therefore, a separate assessment of the he-modynamic status using experiments with vasodilativeagents (49–53) appears to be mandatory in pertinentclinical applications. For pathologies with known he-modynamic contribution, such pharmacological activa-tion may indeed turn out to be more robust and reliablefor hemodynamic assessment (132), since it removesthe confounds from neuronal activity inherent in BOLDfMRI.

The combination of BOLD-based fMRI with othermeasurements, especially including diffusion anisotro-py-based tractography, is expected to play an increas-ingly important role in clinical applications of fMRI. Thecombined overall assessment of neuronal interactionsin the cortical network, the hemodynamic status, andthe morphological and microstructural characteriza-tion of the brain will allow a much more complete pic-ture of function and malfunction of the brain than themeasurement of any of these items alone. The one-stopshop—a buzzword much used in cardiac MR—with acombination of various techniques measuring differentaspects of morphology and function, may very well playan increasingly important role in fMRI of the brain.

12 Hennig et al.

ACKNOWLEDGMENTS

M.A.K. received financial support from Volkswagen-Stiftung; C.W. is supported by Deutsche Forschungs-gemeinschaft, BMBF, and the European Union.

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