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Diffusion‐Weighted Spectroscopy Magnetic Resonance in Medicine 64:939–946 (2010) Diffusion-Weighted Spectroscopy: A Novel Approach to Determine Macromolecule Resonances in Short-Echo Time 1H-MRS N. Kunz,1,2 C. Cudalbu,1 V. Mlynarik,1 P. S. Hu¨ ppi,2 S. V. Sizonenko,2 and R. Gruetter1,3,4* Quantification of short-echo time proton magnetic resonance (composing the neurochemical profile) in the rodent spectroscopy results in >18 metabolite concentrations (neuro- brain (1). chemical profile). Their quantification accuracy depends on The accuracy of the quantification of the neurochemi- the assessment of the contribution of macromolecule (MM) cal profile is critically dependent on the estimation of resonances, previously experimentally achieved by exploiting the contribution of macromolecule (MM) resonances to the several fold difference in T . To minimize effects of hetero- 1 the spectrum, overlapping with the metabolite’s resonan- geneities in metabolites T1, the aim of the study was to assess MM signal contributions by combining inversion re- ces. Therefore, an accurate assessment of the MM contri- covery (IR) and diffusion-weighted proton spectroscopy at bution is important since a biased estimation of the MM high-magnetic field (14.1 T) and short echo time (58 msec) in can lead to errors in the obtained metabolite concentra- the rat brain. IR combined with diffusion weighting experi- tions (1,2). Since the MM resonances linewidth, in con- ments (with d/D51.5/200 msec and b-value 5 11.8 msec/ trast to that of metabolites, does not increase substan- 2 mm ) showed that the metabolite nulled spectrum (inversion tially with B , it renders the distinction of MM signals 5 0 time 740 msec) was affected by residuals attributed to cre- from those of coupled spin systems more difficult. Fur- atine, inositol, taurine, choline, N-acetylaspartate as well as thermore, the absolute quantification of the MM concen- glutamine and glutamate. While the metabolite residuals were significantly attenuated by 50%, the MM signals were almost trations may provide relevant information as a disease not affected (<8%). The combination of metabolite-nulled IR marker (3,4). spectra with diffusion weighting allows a specific characteri- Different techniques to estimate the MM signals have zation of MM resonances with minimal metabolite signal con- been developed during the past years. When treating the tributions and is expected to lead to a more precise MM as a mathematical unknown, a least-square fit using quantification of the neurochemical profile. Magn Reson a sum of splines, wavelets, sinusoids, or polynomials V Med 64:939–946, 2010. C 2010 Wiley-Liss, Inc. with adjustable parameters to approximate the MM sig- Key words: proton magnetic resonance spectroscopy; nals have been used (5–11). The MM baseline has also macromolecules; ultra-high field of 14.1 T; LCModel; been assessed in a mathematical preprocessing step by quantification accuracy modeling of the MM signals in the frequency domain with wavelets (1,7) or in the time-domain using singular INTRODUCTION value decomposition (2,4) and subsequent subtraction; truncation of initial data points (8,9); and ‘‘subtract’’ (5) In vivo short echo time (TE) proton magnetic reso- 1 or numerical filter approach (10). However, all the meth- nance spectroscopy ( H-MRS) at high-magnetic field benefits from increased signal-to-noise ratio (SNR) and ods based on such mathematical modeling provide only spectral dispersion, which improve quantification ac- an approximation of the true in vivo MM spectra (10– curacy and precision, resulting in the direct measure- 12). Although such mathematical approaches may allow ment of the concentrations of about 18 metabolites a reasonably reliable estimation of the in vivo MM spec- tra at high-magnetic fields, where the MM spectrum includes relatively narrow resonances, additional prior knowledge is necessary for an accurate estimation of brain metabolite concentrations. 1Laboratory of Functional and Metabolic Imaging (LIFMET), Ecole Polytechnique Fe´de´ rale de Lausanne, Lausanne, Switzerland. Therefore, to provide the necessary prior knowledge, 2Division of Child Growth and Development, Department of Pediatrics, an experimental assessment of the MM contributions, University of Geneva, Geneva, Switzerland. based on the separate acquisition of the in vivo MM 3 Department of Radiology, University of Geneva, Geneva, Switzerland. spectra using the inversion recovery (IR) method (metab- 4 Department of Radiology, University of Lausanne, Lausanne, Switzerland. olite-nulled spectrum) has been used (13). However, Grant sponsor: SNSF; Grant numbers: 31003A-112233, 3100-067164, 405040-108713; Grant sponsor: EU Grant; Grant number: MRTN-CT-2006- using this experimental approach, small metabolite 035801; Grant sponsors: Centre d’Imagerie BioMedicale (CIBM) (of the residuals are still present in the metabolite-nulled spec- UNIL, UNIGE, HUG, CHUV, EPFL), Leenaards and Jeantet Foundations. T tra due to variability in the 1 relaxation times of metab- *Correspondence to: R. Gruetter, Ecole Polytechnique Fe´de´ rale de Lausanne, SB - IPMC - LIFMET, Station 6, 1015 Lausanne, Switzerland. olites (1,14). The identification of these metabolite resid- T E-mail: [email protected] uals is mainly based on knowledge of the metabolites 1 Received 4 September 2009; revised 9 March 2010; accepted 31 March relaxation times and the consequent removal has been 2010. based on postprocessing techniques. Such a postpro- DOI 10.1002/mrm.22490 Published online 17 June 2010 in Wiley Online Library (wileyonlinelibrary. cessed in vivo MM spectrum was either added to the com). VC 2010 Wiley-Liss, Inc. 939 940 Kunz et al. basis-set (15–19) during the quantification procedure or using a nonselective full-passage hyperbolic secant RF subtracted from the in vivo signal (11,20,21). pulse (pulse length ¼ 4 msec, bandwidth ¼ 5 kHz) at dif- As described previously (1), MMs differ from metabo- ferent inversion times (TIs, ranging from 520 to 1000 T lites by their 1, which are ascribed to their larger molec- msec). For the DW module, gradients were added in the ular size. Consequently, the MM mobility as well as their TE/2 periods and applied simultaneously along the three diffusivity is more hindered. A previous study (22) has gradient directions [1, 1, 1] (22) with a d/D ¼ 1.5/200 shown than MM have an apparent diffusion coefficient msec. The gradient strength ranged from 0 to 370 mT/m (ADC) 10–20 times lower than that of metabolites. There- resulting in b-values ranging from 0 to 13.19 msec/mm2. fore, the use of diffusion weighting techniques could To compensate for magnetic field drift spectra were improve the MM baseline estimation by attenuating the acquired in blocks of 16 averages, which were stored metabolites signal without altering that of MM’s. separately and were corrected for relative shift in fre- Therefore, the aim of this study was to determine MM quency before summation. resonances without any postprocessing by combining To validate the DW-MRS protocols, the sequence was metabolite-nulled spectra with diffusion weighting. tested into two separate phantoms filled with water with a corrected pH of 7.4 and with respectively Cr and Glu, MATERIALS AND METHODS or NAA, Gln and Ins dissolve at a concentration of 30 mM. To assess the phase stability during acquisition, the Animals spectra were acquired on a scan by scan basis for a total In vivo experiments were performed on adult Sprague– of 32 spectra for each b-values. The experience was per- 2 Dawley (Charles-Rivers, France) rats (n ¼ 5, 350 g). The formed for b-values up to 2 msec/mm . To investigate animals were anesthetized with a mixture of pure oxygen higher b-values, a set of in vivo data was also acquired 2 with 1.5–2% isoflurane administrated through a nose for b-values up to 13.9 msec/mm . Each individual spec- cone mask. Animals were restrained with a home-made trum was analyzed by LCModel and the phase output holder with ear and tooth bars. Body temperature was was used to evaluate the experiments stability. measured by a rectal thermosensor and maintained at 37.5 In addition to the in vivo MM spectra, in vivo brain 6 1C by circulating warm water. Respiration and body spectra were acquired from five adult rats using the temperature were monitored during the whole experiment ultrashort TE spin echo full intensity acquired localiza- by a small-animal monitor (SA Instruments, Inc., New tion (SPECIAL) sequence (TE¼2.8 msec) (23), which pro- York, NY). Animals were sacrificed at the end of the expe- vides spectra with higher SNR than STEAM. The VOI rience. All animal experiments were conducted according was identical with that from where the MM spectra were to federal and local ethical guidelines and the protocols acquired. Metabolite concentrations were estimated by were approved by the local regulatory body. LCModel. Quantification was performed using two dif- ferent basis-sets composed of metabolite spectra simu- lated at TE ¼ 2.8 msec, using a program written in MAT- Instruments and Pulse Sequences LAB (MathWorks, Natick, MA) based on the density All in vivo experiments were performed on a Varian matrix formalism (24), using published values of cou- INOVA console (Varian, Palo Alto, CA) connected to a pling constants and chemical shifts (25). The results pro- 14.1 T magnet with a 26-cm horizontal bore (Magnex vided the quantification of the following metabolite con- Scientific, Abingdon, UK), and with an actively shielded centrations: alanine (Ala), ascorbate (Asc), aspartate gradient coil allowing a maximum gradient of 400 mT/m (Asp), creatine (Cr), g-aminobuttyric acid (GABA), glu- with a fix rise time of 120 msec. A home-built quadrature cose (Glc), glutamate (Glu), glutamine (Gln), glutathione surface coil consisting of two geometrically decoupled (GSH), glycerophosphorylcholine (GPC), phosphorylcho- single loops of 14 mm of diameter was used as a line (PCho), myo-inositol (Ins), lactate (Lac), N-acetylas- transceiver.
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