Strategy for the Spectral Filtering of Myo-Inositol andOther Strongly Coupled Spins

Hyeonjin Kim, James M. Wild, and Peter S. Allen*

A multiple quantum filter strategy is presented for spectrallydiscriminating metabolites with strongly coupled spins fromthose whose spins are either uncoupled or weakly coupled. Thestrategy also includes a means for selectively suppressing thebackground multiplets of metabolites that also have stronglycoupled spins. As a demonstration of its efficacy at 3.0 T, thestrategy is shown to enhance by a factor of �5 the signal-to-background ratio of the myo-inositol band at 3.6 ppm relative tothat in response to a PRESS sequence with the same sequencetimings. This is done by eliminating the uncoupled resonance ofglycine and the weakly coupled multiplets of glutamate andglutamine, and by selectively suppressing the strongly coupledtaurine multiplet 3-fold. The macromolecular background waseffectively removed through its transverse decay over 105 ms.The associated cost of gaining the signal to background en-hancement is a drop in signal yield by a factor of 0.75 relative toPRESS at the same timings. The myo-inositol signal to noiseratio was nevertheless maintained by the filter at �12. MagnReson Med 51:263–272, 2004. © 2004 Wiley-Liss, Inc.

Key words: Proton brain spectra; spectral editing; strong cou-pling; Myo-Inositol

Proton NMR spectroscopy provides a noninvasive methodof extracting biochemical information from the brain.However, the proton spins of many of the key brain me-tabolites are strongly coupled, as, for example, in gluta-mate (Glu), glutamine (Gln), and myo-inositol (mI). Thisstrong coupling gives rise to complex multiplet spectrawhich, at field strengths acceptable for clinical use, canoverlap, change with sequence timing, make target metab-olite discrimination from background difficult, and there-fore degrade quantification.

Spectral-editing methods offer a realistic opportunity tosuppress the background and mitigate the overlap, but indoing so they also introduce their own difficulties. Forexample, based on their ability to differentiate betweencoupled and uncoupled spins, double quantum filters(DQF) have frequently been proposed as a means of clari-fying spectral complexity in in vivo NMR (1–12). None-theless, the outcome has often been disappointing. Onereason for the disappointment arises when the targetedcoupled-spin metabolite and its overlapping backgroundare both coupled-spin multiplets. Both target and back-ground are therefore likely to pass through the filter, which

then fails to isolate the target. The principal goal of thisarticle is to demonstrate the selective suppression of cou-pled-spin multiplets.

A second difficulty with a DQF is its low intrinsic signalyield (the signal intensity stripped of its transverse decay).The yield of a DQF is routinely assumed to be lower thanthat of the unedited single-voxel methods, such as thedouble-spin-echo (PRESS) (13,14) or the stimulated echo(STEAM) (15). This is not, however, always the case, be-cause coupled-spin coherence proliferation also occurswith PRESS and STEAM sequences. In previous work wehave demonstrated that in the [TE1, TE2] space for PRESS(16) and the [TE, TM] space for STEAM (17), the yield ofstrongly coupled resonances can be a very irregular func-tion that can sink below that of a DQF (9). Before beingable to make a choice for a filter strategy over the unfilteredPRESS or STEAM, it is therefore essential to know therelative target yields from all sequences, as well as theirefficacy for background suppression. Moreover, if the ir-regular yield behavior is not known prospectively for botha target metabolite and its background, the choice of se-quence parameters may be markedly suboptimal for thediscrimination and measurement of the target metabolite.The ability to calculate the yield (and the lineshape) weretherefore instrumental in the prospective optimization ofthe filter design presented here.

The purpose of the article is therefore to demonstratetools that not only facilitate the elimination from the spec-trum of weakly coupled, as well as uncoupled spins, butwhich also provide the flexibility for partially suppressingone strongly coupled spin species relative to another. Inshort, it significantly enhances target to background isola-tion. Such isolation is only valuable, however, if, as dem-onstrated below in the example of mI, the signal-to-noiseratio (S/N) of the isolated target is maintained, in spite ofreduced yield and transverse relaxation.

A pulse sequence, designed to differentiate betweenstrongly coupled and the weakly coupled spins was alsoproposed recently by Trabesinger et al. (18). Based on theisolation of strongly coupled single quantum coherences(SQC) it provided greater background suppression than thebasic DQF. However (as the authors themselves point out),the filtering mechanism of this sequence relies solely onthe phase of a 90° pulse and is vulnerable to instabilitiesand phase errors of the RF pulses. In contrast, the alterna-tive method proposed here is based on the isolation ofstrongly coupled zero quantum coherence (ZQC) and lon-gitudinal magnetization. Because it employs both RFphase orthogonality and gradient filtering, it is more robustat suppressing signals from uncoupled and weakly cou-pled spins. In addition, it also provides the flexibility toadjust the relative discrimination of different strongly cou-pled spin systems by adjustment of its timing parameters.

Department of Biomedical Engineering, University of Alberta, Edmonton,Alberta, Canada.Grant sponsor: Canadian Institutes for Health Research.Present address for James M. Wild, Dept. of Academic Radiology, Universityof Sheffield, Sheffield, UK.*Correspondence to: Peter S. Allen, Department of Biomedical Engineering,University of Alberta, Edmonton, Alberta, Canada.Received 17 June 2003; revised 8 September 2003; accepted 24 September2003.DOI 10.1002/mrm.10697Published online in Wiley InterScience (www.interscience.wiley.com).

Magnetic Resonance in Medicine 51:263–272 (2004)

© 2004 Wiley-Liss, Inc. 263

The isolation of the mI peak in the vicinity of 3.6 ppmprovides a particularly appropriate example for testing theproposed filter. This is because, in vivo, the quantificationof mI is hindered by the uncoupled resonance from glycine(Gly) at 3.55 ppm; the weakly coupled A multiplets of theAMNPQ spin systems of Glu and Gln (collectively referredto as Glx) at 3.78 ppm, and the strongly coupled A2B2

multiplet of taurine (Tau) at 3.35 ppm. The in vivo spec-trum in this region is also contaminated by a broad mac-romolecular signal (19–21) and the glucose (Glc) reso-nances between 3.4 and 3.8 ppm. Because its low concen-tration is distributed over several multiplets, the Glccontamination was neglected. Neither were the macromol-ecules prospectively included in the numerical evaluationof the optimum sequence design. The sequence parameterswere, nonetheless, chosen such as to minimize any mac-romolecular signal.

In the following we outline first the logic and opera-tional mechanisms of the sequence and, second, the meansof testing the sequence operation experimentally withphantoms is explained, prior to providing an in vivo dem-onstration of its efficacy. A preliminary report of this work(22) was presented recently.

THEORY

Sequence and the Multiple Quantum Filter Mechanism

When a generic multiple quantum filter (MQF) sequence ofthree coherent 90° pulses is applied to a weakly coupledmetabolite spin system, the sequence gives rise to the evenorders of multiple quantum coherence (MQC), each one ofwhich can be isolated by appropriate gradient filtering(23). This is the conventional sequence for observing ZQC.However, it is not adept at distinguishing the ZQC (or thegradient-insensitive longitudinal magnetization) from dif-ferent coupled-spin systems or from the longitudinal mag-netization of uncoupled spins. Alternatively, if the phaseof the second 90° pulse in the MQF is made orthogonal tothat of the first pulse, the sequence produces only oddorders of MQC from weakly coupled spins and might nottherefore be expected to produce ZQC. In contrast, how-

ever, the spins of strongly coupled metabolites experiencepolarization transfer in the first interpulse interval (18,24),which leads to additional terms in the density operatorthat can be turned into ZQC by the orthogonal phasedisposition of the first two pulses. The combination of RFphase orthogonality followed by a strong dephasing gradi-ent in the second interpulse (mixing) period, therefore,enables the proposed technique to suppress all uncoupledand weakly coupled spin coherences, while at the sametime maintaining ZQC and longitudinal magnetizationfrom strongly coupled spins only.

The proposed filter sequence is shown in Fig. 1, togetherwith a comparative illustration of the coherence evolutionthrough the sequence for an uncoupled spin, I; for the Aspin of a weakly coupled spin pair, AX; and for the A spinof a strongly coupled spin pair, designated AB (24). Thecorresponding and symmetric evolutions of the X spin andof the B spin are omitted for clarity. Although the coher-ence evolution of these simpler systems cannot be takenliterally for the larger spin systems of Glu, Gln, mI, andTau, it clearly illustrates the mechanism. The key illustra-tive point of Fig. 1 is that the strongly coupled A spintransverse terms, Ax and AyBz, prior to the second 90°pulse, are overwhelmingly brought about in the first inter-pulse interval by the strong-coupling Hamiltonian actingon the B spin transverse term By, which is created by the1H excitation pulse. They do not arise from Ay. Ax andAyBz are subsequently transformed by the second orthog-onal pulse into gradient-insensitive Az and [AyBx]ZQC, re-spectively. No gradient-insensitive terms arise from eitherweakly coupled or uncoupled spins following the second90° pulse, and therefore the application of a filter gradientduring the TM period will not only remove the uncoupledand weakly coupled terms, but it will also remove allhigher orders of MQC from the strongly coupled spins. Incontrast to a generic MQF, the absence of a second, refo-cusing filter gradient after the third 90° pulse in the se-quence proposed here prevents any terms other than thegradient-insensitive terms, i.e., the Az and [AyBx]ZQC of thestrongly coupled spins, leading to observable signal duringthe acquisition period.

FIG. 1. A schematic illustration of a mul-tiple quantum filter sequence including(a) the pulses and the timing definitionsand (b) a representative listing made foreach coupling category of the evolutionof coherence terms during the individualtiming periods.

264 Kim et al.

Outline of Analysis to Optimize mI Observation at�3.6 ppm

Between 3.2 ppm and 3.9 ppm in the proton spectrumfrom brain, the principal background metabolite reso-nances interfering with the observation of mI arise fromthe uncoupled Gly (3.55 ppm), the weakly coupled Amultiplets of the Glx AMNPQ spin system (�3.78 ppm),and the strongly coupled A2B2 system of Tau (�3.35 ppm).In addition, there is a broad macromolecular baselinehump. The sequence proposed here is designed, first, toeliminate Gly and Glx signals using RF phase orthogonal-ity coupled to filtering with gradient dephasing; second, tosuppress Tau by optimizing the interpulse intervals; andthird to ensure a cumulative echo time sufficient to com-plete the decay of the macromolecular signal. The spec-trum of the six observable protons of mI, designated anAM2N2P spin system (25) at 3.0 T in Fig. 2, is dominatedby a band at �3.6 ppm, for which the M2N2 stronglycoupled, double pair is primarily responsible. For a fulldescription of the response of mI to an arbitrary pulsesequence, a total of 4096 coherence terms needs to befollowed. Even using a restricted set for the M2N2 sub-group, the still-large number of terms, together with thestrong-coupling, precludes manual, product-operator anal-ysis. Alternatively, numerical methods of solving theequation of motion of the density operator (9,16,17,26,27)provide a practical way of tracking the large number ofcoherence terms through a pulse sequence.

To calculate the spin system response, it is necessary tosolve the Liouville-von Neumann equation (28):

ddt

�(t) � �i[H (t),��t�] [1]

for the time-dependent density operator of the spin sys-tem, �(t), where H is the Hamiltonian under which theevolution takes place. For an N spin, I � 1/2, system thedensity operator �(t) can be expressed as a weighted sum ofthe complete set (22N) of product operator basis terms (28),the weighting coefficients reflecting the temporal evolu-tion of each term. The Hamiltonian used in our calcula-tions included, in addition to the Zeeman interaction, theRF pulses, the gradient pulses, the different chemicalshielding interactions, and the several scalar coupling in-teractions. No approximations were made for weak cou-pling. For time-independent Hamiltonians, Eq. [1] has asolution:

�(t) � U�t���0�U�1�t� [2]

where U(t) � exp(-i Ht). The solutions can therefore beobtained by matrix multiplication alone, if the exponentialoperators are expressed as matrices. When H correspondsto a diagonal matrix, U(t) can be expressed as a diagonalmatrix of exponential elements. Otherwise, H needs to bediagonalized by means of a unitary matrix, V, and theresulting exponential operator transformed with the sameunitary matrix, so that:

��t� � V exp(�i Hdiagt)V�1 ��0� V exp�i Hdiagt�V�1

[3]

where Hdiag � V�1 H V, and the unitary matrix V is formedfrom the eigenvectors of H. When H is not time-indepen-dent, for example, when shaped RF pulses are modeled, itstime evolution can be subdivided into short discrete timeelements, within each of which time independence of theHamiltonian can be assumed.

In the algorithm, each pulse sequence is treated as aseries of independent contiguous time segments, each hav-ing its own Hamiltonian. Terms in the density operatorcan be evaluated at any stage during the sequence, or theacquisition period, by successive matrix multiplicationaccording to Eq. [3]. For the gradient term in the Hamilto-nian there exists a spatial distribution as well as a tempo-ral evolution, giving rise to multiple evolution operatorsfor each time segment or subsegment in which the gradientis applied. The gradient evolution operators for each timesubsegment were collected in a storage matrix that enabledtheir effects to be combined efficiently irrespective ofwhether the ultimate FID or a mid-sequence density oper-ator term was required. For selective pulses, the RF enve-lope was divided into 7.5 �s time subsegments and thegradient-induced frequency distribution was typically in-cremented to give rise to a 0.1 mm spatial resolution. Sucha resolution enabled the 90% to 10% roll-off of the 90°pulse to be captured over 30–40 spatial intervals. Thetemporal evolution of any of the various coherences or ofthe ultimate transverse magnetization emerging from the

FIG. 2. A diagram illustrating the mI molecule together with sche-matic of the chemical shift values, � ppm, and the coupling config-uration, including individual interaction strengths, J Hz.

Spectral Filtering of Myo-Inositol 265

sequence can easily be evaluated from the trace of theproduct of the density operator with the correspondingcoherence or magnetization operator. Because the methodof solution accommodates Hamiltonians that change rela-tively slowly with time, the influence of practical sliceselective pulses can be calculated and contrasted with thatof a hard-pulse approximation.

A total of 384 SQC species can potentially contribute tothe overall mI spectrum through their time evolution inthe acquisition period. They are illustrated schematically

in Fig. 3a at the onset of the acquisition period followingthe proposed filter sequence. However, the target peak ofmI at �3.6 ppm is dominated by far fewer than this.Although the 3.6 ppm band of the mI spectrum arisesmainly from the four M and N spins, it is dominated bylittle more than 12% of their 256 SQC terms. For example,when the sequence has symmetric echo-times, Fig. 3b–gillustrates that of the 64 M1 SQC and the 64 N2 SQC (therealso exists a corresponding 128 SQC from the M2 and N1

spins) the echo-time dependence is dominated by the

FIG. 3. Specific-time snapshots of the relative amplitudes of various coherences of the mI spin system. These snapshots correspond tothe onset of acquisition in the symmetric echo-time filters where [TE1, TM, TE2] are, respectively [30 ms, 9 ms, 30 ms], [40 ms, 9 ms, 40 ms],and [60 ms, 9 ms, 60 ms]. The coherence number labels are arbitrary, but the important coherences are labeled by name. The fractionalamplitude scale represents for each coherence term the proportion of its maximum value.

266 Kim et al.

changes in no more than an eighth of these terms, namely,the terms actually labeled in Fig. 3b–g. It is also clear fromFig. 3b–g that significant changes of both the amplitudeand sign of the key terms can occur with small changes inecho time. It must also be kept in mind that the lineshapeof each of these SQC contributions differs one from an-other, and that the overall response can be represented bytheir weighted sum, where weighting factors correspond tothe amplitudes of the SQC terms at the onset of acquisi-tion, e.g., the amplitudes shown in Fig. 3. Using only theeight major terms for each of the four M and N spins, Fig.4 demonstrates the close agreement between the numeri-

cally calculated response to the proposed filter and thecorresponding experimental, phantom lineshape of the3.6 ppm band. Notwithstanding, this close agreement withexperiment arising from a restricted set of SQC terms, theultimate comparison of experiment and theory for theoptimized filter (shown in Fig 7., below) made use of thefull set of SQC terms.

To predict the optimal filter timings that suppressstrongly coupled Tau (but not mI), one must also evaluate,in response to the filter, and relative to mI, the dominatingcoherences for producing the Tau signal during acquisi-tion. Because of symmetries in the A2B2 spin system justone of the four Tau spins, i.e., the A1 spin, is sufficient toillustrate how these timing choices minimize the relativeTau signal. Three periods, namely, TE1, TM, and TE2, areavailable for manipulating the relative strengths of the Tauand the mI signals. A key characteristic of the filter is thatit specifically limits the terms that survive TM to longitu-dinal magnetization and to ZQC. The first step in suppress-ing Tau was therefore to minimize at the end of TE1 theprecursors of the Tau TM survivors. The left side of Fig. 5illustrates the evolution, during TE1, of the precursorterms of TM survivors that could ultimately give rise to theemergence of the principal four of the 16 A1 spin SQCterms, namely, A1x, A1y, 2A1xB1z, and 2A1yB1z at the onsetof acquisition. Clearly, TE1 �75 ms emerges as a candidatefor minimizing the TM survivors of Tau that is also con-sistent with the length of time needed for a significantdecay of the macromolecular signal. However, as empha-sized below, these evolution curves are only a guide, andthe acid test of suppression is the weighted summing ofthe basis lineshapes during acquisition. TM itself givesrise to very little evolutionary change and it was made justlong enough (9 ms) to accommodate the selective pulseand the filter gradient. The second active step was toexplore the adjustment of TE2 to minimize the emergenceof Tau SQC relative to mI SQC in the second echo period.The TE2 period of Fig. 5 illustrates the proliferation ofcoherences after the third 90° pulse, emphasizing thatdue to the strong-coupling interaction transverse A mag-netization can even arise from transverse B terms, e.g.,A1x and 2A1xB1z from either B1y or 2A1zB1x. However, incontrast to the TE1 evolution, no clear minimum in theevolution of Tau SQC arises at acceptably short TE2. ThemI SQC are similarly slowly varying functions of TE2.For example, if TE2 varies from 30 –50 ms, the mI inten-sity declines by �30%, whereas Tau increases by�10%. We therefore chose to maximize mI SQC at theonset of acquisition and at the shortest TE2 consistentwith this. During acquisition, each of the Tau SQC termspresent at the onset will contribute its own basis line-shape to the overall Tau response, and it will do so inproportion to the amplitude of that term at the onset.The amplitude of each term at the onset is the sum overall its source pathways. The basis lineshapes for therepresentative SQC of the A1 spin are shown in Fig. 5.The weighted sum of all major contributing Tau SQC,when compared to the corresponding sum for mI, leadsto the prediction for optimum editing discrimination ofan asymmetric filter with timings [TE1, TM, TE2] �[75 ms, 9 ms, 30 ms].

FIG. 4. A comparison of the experimental phantom lineshapes of mI(solid lines) with the corresponding lineshapes (dashed lines) calcu-lated using only the eight principal SQC terms of the M and N spinsof mI. The comparisons are illustrated for three symmetric filterswith TE1 � TE2 � 30 ms, 40 ms, and 60 ms, respectively. Mixingtime TM � 9 ms for all three filters.

Spectral Filtering of Myo-Inositol 267

MATERIALS AND METHODS

Pulse Sequence

The first 90° pulse was a spatially selective sinc pulse(3 ms long and �3900 Hz in bandwidth) which was opti-mized to minimize the spatial extent of the tip-angle tran-sition region (29). Because of its crucial role in generatingMQCs, the second 90° pulse was chosen to be a rectangu-lar, hard pulse, with as short a duration as possible (250�s), thereby minimizing intrapulse coherence evolution.This was made possible at 128 MHz using an 8 kW RFamplifier (Herley Industries, Lancaster, PA). The impor-tance of keeping this pulse short increases when stronglycoupled spins are involved because of their rapid coher-ence transfer (16,17). The third 90° pulse (the read pulse)was a frequency selective sinc-Gaussian pulse, optimizedto uniformly excite all metabolite peaks upfield from thewater resonance. The two 180° chemical shift refocusingpulses were also spatially selective (3.5 ms duration and

1200 Hz bandwidth) and similar in design to the initial90° pulse. The phases of both the second and the third90° pulses were carefully calibrated relative to that ofthe excitation pulse. The length and amplitude of eachslice-selection gradient was set to give rise to an excitedvoxel of 3 3 3 cm3 for both phantom and in vivoexperiments. To remove unwanted signals resultingfrom the incomplete refocusing that stems from the tip-angle profile of the nominal 180° pulses, these pulseswere encapsulated within a pair of spoiler gradients of2 ms duration and 20 mTm�1 amplitude. The filtergradient during TM (5 ms, 20 mTm�1) was applied at themagic angle to enhance the suppression of residual wa-ter signal arising from the demagnetizing dipole– dipoleinteraction between water molecules (30). All RF pulseswere phase-cycled (16 steps) to eliminate unwanted co-herences which may have arisen from outside the vol-ume of interest (31).

FIG. 5. An evolutionary chart of representative coherence pathways for defining the Tau spectral response to the filter sequence. Thetemporal variation shown for TE1 illustrates the most appropriate value of TE1 for minimizing the gradient-insensitive terms in the mixingtime, TM, e.g., the longitudinal magnetization and the imaginary zero quantum coherence. The pathways shown under TE2 illustrate theproliferation of coherences due to the strong-coupling interaction and emphasize the multisource nature of the SQC giving rise to thelineshape components.

268 Kim et al.

Spectroscopy

Four 6-cm diameter spherical aqueous phantoms wereused to evaluate the sequence design. The first, (phantom1) contained only mI (50 mM) and was used to confirm thenumerically determined timing variability of the mI re-sponse (Fig. 4). To verify the sequence discrimination ofstrongly coupled spins from uncoupled and weakly cou-pled spins (Fig. 6), phantom 2 was prepared containing mI(with both strongly and weakly coupled spins) and creat-ine (Cre), in a 5:1 concentration ratio, with mI again at50 mM. Third, to represent the coupled-spin metabolitesappearing in the proton spectrum of normal brain between3.0 ppm and 4.0 ppm, phantom 3 was manufactured withmI, Glu, Gln, Gly, Tau, and Cre in the relative concentra-tions, 1: 1.3:0.6:0.2:0.5:1.1, respectively (20,32,33), andwith mI at 50 mM to maintain consistency with phantoms1 and 2. The experimental performance of the filter wasinitially evaluated by comparing the responses of thephantoms to PRESS and to a series of three, symmetric-echo-time sequences, namely, [30 ms, 9 ms, 30 ms],[40 ms, 9 ms, 40 ms], and [60 ms, 9 ms, 60 ms] in [TE1, TM,TE2] space. A fourth phantom, identical to phantom 3 inall respects except that Gly was removed, was used todemonstrate that the presence of Gly is clearly observablein the PRESS spectrum.

The in vivo performance was confirmed on a 30-year-oldfemale volunteer. The spectrum was acquired from a 3 3 3 cm3 volume of the occipital lobe, over which a 6 Hzshim was obtained.

All experiments were carried out at 3.0 T in an 80-cmbore magnet (Magnex Scientific, Abingdon, UK), using ahome-built 28-cm i.d. quadrature birdcage coil for bothtransmission and reception. The spectrometer control wasprovided by an SMIS console (Surrey Medical ImagingSystems, Guilford, UK). All phantom spectra were ac-quired with 32 averages (scan time 2 min) and subjectedto a line broadening of �6 Hz to produce correspondencewith in vivo spectra. In vivo, the number of averages andscan time were increased to 256 and 13 min, respec-tively.

RESULTS

The first objective was to demonstrate that the theoreticalmodel correctly predicted the response of both coupledand uncoupled metabolite spin systems to the proposedfilter. The second was to optimize this filter for the dis-crimination of mI from its contaminating background ofstrongly coupled, weakly coupled, and uncoupled spins.

The multiplet resonances of mI close to 3.6 ppm can beroughly grouped into two closely neighboring bands, onedesignated � at �3.54 ppm and the other, �, at �3.62 ppm.These bands, which are resolvable at 3.0 T, display signif-icantly different echo time dependences, not only in re-sponse to either the STEAM or the PRESS sequence, butalso in response to the proposed filter sequence. Thisdifference in response gives rise to lineshape and peakfrequency variations in single voxel spectroscopy at 1.5 T

FIG. 6. A comparison of the experimental phan-tom responses to a symmetric PRESS sequence[TE1 � TE2 �30 ms] and to three symmetric filterswith TE1 � TE2 � 30 ms, 40 ms, and 60 ms,respectively, and with mixing time TM � 9 ms forall three filters. The column of spectra of the firstphantom illustrated, namely, phantom 2, demon-strates the elimination of uncoupled and weaklycoupled resonances by the filter, as well as thenonsingular TE dependence of the lineshape andits intensity. The second column, illustrating thespectra of phantom 3, demonstrates the elimina-tion of uncoupled and weakly coupled backgroundresonances of metabolites found in brain, as wellas the suppression of Tau relative to mI. In com-parison with the dashed spectrum of the supple-mental phantom 3 (not containing Gly), the spec-trum of the original phantom 3 strikingly illustratesthe marked addition of the Gly resonance to theresonance of mI.

Spectral Filtering of Myo-Inositol 269

which have not to our knowledge been reported. With theproposed filter at 3.0 T they provide a critical test of thenumerical modeling, the efficacy of which is demonstratedin Fig. 4.

The ability of the filter to remove uncoupled and weaklycoupled resonances is shown in Fig. 6, where the responseof phantom 2 to both PRESS and the proposed filter isillustrated. In phantom 2, Cre provides two uncoupledresonances, one at 3.0 ppm (methyl) and one at 3.9 ppm(methylene), whereas mI provides both a weakly coupledresonance (A spin) at 4.06 ppm, as well as the band ofstrongly coupled resonances around 3.6 ppm. Although allthese resonances are present in the PRESS spectrum, allbut the strongly coupled signals are shown by Fig. 6 to beeliminated at all the echo-time combinations of the pro-posed filter.

The response of a portfolio of brain metabolites in theappropriate relative concentrations (20,32,33) both to asymmetric version of the proposed filter and to a symmet-ric PRESS sequence is also illustrated in Fig. 6. There aretwo PRESS spectra shown in the right column of Fig. 6.They are presented to emphasize the clear demonstrationat 3.0 T of Gly adding to the � band of mI. Moreover, in the3.0 T PRESS spectra the substantial spectral overlap of allresonances is clearly apparent, whereas only the stronglycoupled resonances of mI, Glx (at �2.3 ppm), and Tau areable to penetrate the filter. The weakly coupled A spins ofGlx at �3.75 pm are suppressed by the filter. The differ-ences in echo-time sensitivities of the different stronglycoupled spins are also demonstrated in Fig. 6.

The performance of the optimized asymmetric filter,both on phantoms and in vivo, is demonstrated in Fig. 7,

by comparison with the corresponding asymmetric PRESSsequence. The phantom response to PRESS is quite differ-ent from that shown in Fig. 6 because of the difference andasymmetry of the echo times between the two figures. Theclose correspondence of both the lineshape and the spec-tral discrimination, between the calculated filter perfor-mance, that using phantoms, and that obtained in vivofrom the occipital cortex of a human brain is well demon-strated by Fig. 7.

DISCUSSION

The prospective design of sequence parameters for boththe preservation and the isolation of signal from a targetmetabolite is a valuable asset in brain spectroscopy. This isbecause many key brain metabolites contain strongly cou-pled proton spins that give rise to an overlapping multipletspectrum. The sequence proposed herein is superior toconventional DQFs, not only because it has the ability tosuppress weakly coupled spins along with uncoupledspins, but because it can also selectively discriminate be-tween species of strongly coupled spins by suppressingone relative to another. It is also more robust than a pre-viously proposed filter for strongly coupled spins (18) dueto the reinforcement of phase-sensitive coherence selec-tion with gradient filtering. The design strategy was dem-onstrated with a sequence whose goal was the isolation ofmI at �3.6 ppm. In vivo, mI gives rise to a large resonanceband at �3.6 ppm that is severely corrupted, both byneighboring metabolite resonances (particularly co-reso-nant Gly) and also by a broad macromolecular band thateffectively produces a sloping baseline (19–21). As a result

FIG. 7. A comparison of spectral responses intended to es-tablish the efficacy of the optimized filter in vivo. As a base-line spectrum, the response of the phantom of brain metab-olites, namely, phantom 3, to a PRESS sequence corre-spondingly timed to the optimized filter is used. Because thetimings are changed, this PRESS spectrum is different fromthat of Fig. 6. Tabulated below the PRESS spectrum are theresponses to the optimized filter. First is that calculated for mIitself, second is that from phantom 3, and third is the in vivospectrum. The in vivo spectrum between 3.5 ppm and2.5 ppm displays residual background signals from metabo-lites with strongly coupled spins, most notably the aspartategroup of NAA, that were not included in phantom 3. The truenoise level is represented by an insert panel of the baselinebetween –2 ppm and –3 ppm.

270 Kim et al.

of this sloping baseline, short echo-time PRESS or STEAMat 3.0 T show an adjacent Glx peak at �3.8 ppm of com-parable height to that of mI at 3.6 ppm, and the Cre meth-ylene peak comparable in height to its methyl peak insteadof in a 2:3 ratio. The sequence proposed here avoids themacromolecular baseline artifact by extending the overallecho time beyond 100 ms. It eliminates background signalfrom uncoupled (Gly) and weakly coupled (Glx) protonspins by coherence filtering and it differentially sup-presses background signal from metabolites with stronglycoupled protons, e.g. (Tau), by using appropriate echotimes identified from the calculated coherence evolutionsof the respective metabolites.

The principal justification for the filter is the suppres-sion of background resonances sufficiently to enable targetmetabolite quantification to take place unambiguously. Toassess the filter design and performance critically it wasnecessary, first, to use experimental phantom spectra(Figs. 4, 6, 7), because the density matrix calculationsincluded only metabolite spins and not the macromolec-ular spins that can also contribute to the spectral back-ground in vivo. In anticipation of a macromolecular signal,the filter timings were chosen to ensure that the macromo-lecular transverse decay ran its course. To quantify back-ground metabolite contamination, the calculated spectracorresponding to phantom 3 predict a signal to back-ground area ratio, S/B, of �4.2 between 3.4 ppm and3.75 ppm for the optimized filter, whereas for the corre-spondingly timed PRESS sequence S/B �0.8, i.e., a gain ofa factor of 5 in favor of the filter. The optimization of thefilter, which itself eliminated Glx and Gly, reduced theTau intensity to 30% of that returned by the equivalentlytimed PRESS sequence. At these longer echo times, wherethe macromolecular background has decayed, calculatedspectra, phantom spectra, and in vivo spectra are all inclose agreement (Fig. 7) and the numerical values of S/Bfrom calculated spectra hold in vivo. Although there isalso close agreement at short echo-times between calcu-lated and phantom spectra for both PRESS and STEAMsequences, it would not be meaningful to compare calcu-lated and phantom measures of S/B with in vivo measuresof S/B. This is because in vivo, at short echo times, themajor distortion arises from the macromolecular signal,notwithstanding the �10% contribution from uneditedGly (its much greater at longer echo times) to the intensityof the � peak of the mI band in normal brain.

Of comparable importance to the minimization of back-ground is an understanding of the actual yield of the targetmetabolite itself, in response to the pulse sequence em-ployed. Yield (the signal intensity stripped of its trans-verse decay) is an essential (but sometimes neglected)element in the accurate determination of metabolite con-centration from the spectrum. For coupled spins, the sig-nal intensity evolution is not governed by T2 alone, as it isfor uncoupled spins satisfying the vector model. It is alsogoverned by the proliferation of coherences that originatewith the spin-system coupling and that give rise to varia-tions in yield that can be sensitive and irregular functionsof sequence parameters. Irregular variations in yield occurindependently of whether the signals arise from PRESS, orSTEAM, or a filter sequence. This difference in the deter-minants of signal-intensity evolution between coupled

and uncoupled spins can lead to quite misleading concen-tration estimates if a direct ratio of coupled to uncoupledsignal intensities is used, e.g., mI with the acetyl resonanceof N-acetyl aspartate (NAA). Only if the mI to NAA yieldratio is known can the concentration be determined fromthe signal intensity ratio. The inability to calculate yieldfor a PRESS or STEAM acquisition is therefore no less animpediment to representative concentration estimatesthan is the absence of the internal “standard” singlet res-onances in a multiple quantum filter spectrum. To quan-tify metabolites when multiple quantum filters are used, atleast two options are available. The first, if a singlet reso-nance is preferred as an internal “standard,” would be totrack the evolution of the uncoupled spins through thefilter sequence and then, following the filtered-signal ac-quisition, add a supplementary sequence to bring back theuncoupled-spin signal. Such a strategy was published sev-eral years ago (34). Alternatively, the intensity of a coupledresonance, not thought to be involved in the pathology andthat has not been suppressed as part of the contaminatingbackground of the target metabolite, could be used so longas all relative yields and lineshapes in the filtered spec-trum were calculated. A similar strategy was adopted toestimate GABA concentration changes due to vigabatrinadministration in normal volunteers (35).

To put into perspective the price paid in target-signalyield to achieve the optimum S/B, we note first that theshort-echo-time PRESS sequence [TE1, TE2] � [18 ms,16 ms] has an mI yield of only 70% of that of a 90° –Acquire sequence (36). When the PRESS timing corre-sponds to that of the optimized filter proposed here, theyield is reduced to �20%. By comparison, the maximumsignal yield of mI for the proposed filter occurs at [TE1,TM, TE2] � [50 ms, 9 ms, 30 ms] and is calculated to be�25%. For optimal background suppression, however,i.e., [TE1, TM, TE2] � [75 ms, 9 ms, 30 ms], the yield dropsto 15%. Thus, in terms of yield and S/B the optimizedfilter produces 75% of the equivalent PRESS sequence, butis five times better in background discrimination. Viewingthis result in the light of S/N considerations, the optimizedfilter gives a peak signal that is �5 times the peak-to-peaknoise at 3.0 T (S/N �12, using the SD of the noise). Onecan therefore have confidence in quantifying mI changes of�10% of normal on both S/B and S/N grounds.

The result and optimal sequence parameters presentedin this article are clearly dependent on the field strength.Deviations from the weak-coupling limit will be moremarked at lower field strengths, and although this willprovide a better signal yield for a strongly coupled targetresonance at 1.5 T, it will also impede the suppression ofthe resonances from metabolites whose proton couplingmight be a better approximation to the weak-couplinglimit at 3.0 T.

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