A novel method of chemical shift imaging utilizing echoplanar ... times of conventional double phase-encoding CSI tech- ... School, Boston, Massachusetts.
Magnetic Resonance in Medicine 41:877–882 (1999)
Echoplanar Chemical Shift Imaging A.R. Guimaraes,1,2,3 J.R. Baker,1,2 B.G. Jenkins,2,3 P.L. Lee,2,3 R.M. Weisskoff,1,2,3 B.R. Rosen,1,2,3 and R.G. Gonza´lez2,3,4* A novel method of chemical shift imaging utilizing echoplanar imaging (EPI) has been developed for the purpose of improving the spatial resolution of metabolite images for the specific goal of high spatial resolution mapping of neuronal content. An EPI sequence was modified to allow temporal offsets of the 180° refocusing pulse that encode the chemical shift information into the phase of the signal. Implementation of this method on 1.5 and 3 T human imagers has resulted in images of N-acetyl aspartate in humans with spatial resolution of 360µl and signalto-noise ratio D7:1 in less than 13 min. Magn Reson Med 41:877–882, 1999. r 1999 Wiley-Liss, Inc. Key words: echoplanar imaging; chemical shift imaging; Nacetyl aspartate; neurodegeneration
This paper presents the development of a novel approach to chemical shift imaging (CSI) that applies the capability of echoplanar imaging (EPI) to traverse k-space rapidly for improving the spatial resolution of metabolite images. While conventional phase-encoded chemical shift imaging (1,2) produces metabolic images with superior spectral resolution, improvements in spatial resolution are limited by the need for multidimensional phase encoding and the subsequent long acquisition times. High-speed image acquisition sequences, such as EPI and rapid acquisition and relaxation enhancement (RARE) imaging, may significantly redefine chemical shift imaging. This derives from their ability to acquire individual images very rapidly, thus allowing a quick sampling of three-dimensional (3D) or 4D CSI data sets at high temporal and spatial resolution. The capability of these high-speed sequences to traverse kspace rapidly allows them to explore spatial, spectral, and temporal resolution tradeoffs. Recently, Mulkern et al (3) and Duyn and Moonen (4) have explored the use of RARE-like sequences for performing CSI (3,4), and Posse et al (5,6) have demonstrated successfully a novel spectroscopic imaging technique that utilized echoplanar technology for both spatial and spectral encoding, based on a method originally proposed by Mansfield (7). In this communication we present an alternative scheme for using EPI to perform CSI based on our previous work 1Division of Health, Sciences and Technology, Harvard Medical School, Boston, Massachusetts. 2MGH-NMR Center, Massachusetts General Hospital, Harvard Medical School, Charlestown, Massachusetts. 3Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts. 4Division of Neuroradiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts. Grant sponsor: National Institute of Neurological Disorders and Stroke, NIH; Grant number: NS34626; Grant sponsor: National Center for Research Resources, NIH; Grant number: RR13213; Grant sponsor: NIH: grant numbers: 5 R01 CA40303 and 5R01 AG10679. *Correspondence to: R.G. Gonza´lez, Division of Neuroradiology, MGH-NMR Center, 149 13th St., Charlestown, MA 02129. Received 12 January 1998; revised 31 January 1999; accepted 2 February 1999.
r 1999 Wiley-Liss, Inc.
(8). Our method is essentially an EPI version of the CSI sequence presented by Sepponen et al (9) or Dixon (10), which are versions of a 2D (11) experiment in which the 1807 pulse is stepped off incrementally to encode the spectral information into the phase of the signal. The objective of the present research was to acquire rapidly the 3D (two spatial and one frequency dimension) data sets necessary for spectral characterization and high spatial resolution. For high concentration moieties such as water, high intrinsic signal-to-noise ratio (SNR) permits high temporal and spatial resolution. For metabolite mapping of species with in vivo concentrations ⬍10 mM, however, low intrinsic SNR precludes rapid imaging. Of equal concern, long acquisition times themselves become a critical, practical challenge. EP CSI offers a unique solution to some of the problems associated with the long encoding times of conventional double phase-encoding CSI techniques. By sacrificing some spectral resolution, EP CSI can sample k-space rapidly and thereby produce metabolite maps with superior spatial resolution (⬍500l voxel volumes). In this paper we demonstrate the implementation of EP CSI on both phantoms and humans, to test the hypothesis that EP CSI can provide high spatial resolution maps of the distribution of N-acetyl aspartate (NAA) in the human brain. Our results indicate that this technique can yield CSI data over an entire slice with high SNR and spatial resolution, and that the tradeoff in spectral resolution still yields adequate separation between moieties such as creatine and choline, especially at high field strengths.
MATERIALS AND METHODS To acquire EP CSI data, we modified an echoplanar spinecho imaging sequence to allow multiple, sequential () offsets of the 1807 refocusing pulse. This sequence, shown in Fig. 1, is essentially an echoplanar version of the CSI technique first described by Sepponen and colleagues (9,10). In this technique, each radiofrequency (RF) excitation is fully encoded in two spatial directions with an echoplanar acquisition. The k-space trajectory of this sequence is demonstrated in Fig. 2. The 1807 pulse is moved temporally on sequential acquisitions to encode the chemical shift into the phase of the signal. This offset produces a phase shift () that results from signals that are spectrally off-resonance by the amount ⫽ /2, where is the temporal offset of the 1807 pulse. The spectral frequency resolution, ⌬f, is determined by the maximum relative displacement of the 1807 pulse, ⌬f ⫽ 2/ max - min (where max is the maximum offset of the echo, and min is the minimum offset of the echo), and the spectral width is thus f ⫽1/2*⌬.
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shimming on nine slices encompassing the volume of interest. Imaging parameters include the following: TR/TE 3000/80 msec; 128 ⫻ 64 matrix with a 40 ⫻ 20 cm field of view (FOV), and offsets 2.2 and 0 msec. Imaging Protocol and Processing
FIG. 1. EP CSI sequence, which combines phase encoding of the frequency dimension with EPI for encoding the x and y spatial dimensions. The 180° pulse is shifted by ⌬ on successive excitations while the readout period is kept constant. Processing includes a Hamming window applied in the x and y dimensions to improve the signal-to-noise ratio of the images, and the data are zero-filled in the tau dimension prior to Fourier transformation (FT) with a 3D FT.
Water Suppression We used a frequency-selective, binomial 14641, 1807 pulse to provide water suppression in our metabolite images (12). This pulse is B0-insensitive, with less than 1% change in suppression ⫾1/4 ppm, and close to the transmitter frequency it is also insensitive to small variations in B1. At the carrier frequency the net flip angle is zero, irrespective of the RF field, while at small frequency offsets the compensation responsible for the flatness of the null is largely unaffected by expected changes in B1. We have optimized this pulse for maximal excitation of the methyl protons of NAA resonating at 2.0 ppm. B0 Compensation B0 compensation was performed by an automated shimming algorithm that fits ⌬B0(r), measured as a phase difference between asymmetric spin echoes, to a truncated orthonormal basis of spherical harmonics, and re-adjusts the shims to compensate for the calculated offset for each harmonic (13). This is done prior to each investigation by
FIG. 2. k-space trajectory of EP CSI sequence. Each 180° pulse encodes the chemical shift into the phase of the signal and encodes a full image by an EPI acquisition.
Imaging was performed by using a resonant gradient system (ANMR Systems) retrofitted to GE Signa 1.5 and 3 T whole-body systems. Imaging parameters were optimized for specific imaging experiments and are detailed in the results section. Imaging protocols consisted of T1-weighted sagittal localizers (TR/TE 600/20 msec); shimming using the imaging parameters as detailed above; and EP CSI. Complete 3D CSI data acquisition times were 17 and 68 min for 4 and 16 number of excitations (NEX). The images were reconstructed using a Hammingwindowed 3D Fourier transform (FT) (14). The data were windowed in the x and y dimensions to improve SNR and zero-filled in the tau dimension from 128 to 512 points prior to FT with a 3D FT. The spatial resolution of EP CSI is adequate to eliminate any spatial contamination of extraneous lipids that spectrally overlap the NAA resonance in vivo. The dynamic range is also adequate to resolve lipid signals from other less concentrated metabolites (i.e., NAA and choline). Therefore, lipid suppression was not used in the human experiments, and the extraneous lipid signal was masked after processing. The masking technique removed all pixels of intensity that corresponded to lipid. NAA maps were formed by averaging those images representing signals from 2.0 ⫾ 0.1 ppm. As result of encoding the spatial information in an entire image within 64 msec of acquisition time, EPI introduces chemical shift artifacts that arise because of the chemical shift. This was not corrected. It did not introduce an appreciable blurring of the NAA image because of the narrow frequency range over which the NAA images were averaged.
RESULTS To assess the capability of EP CSI to produce chemical shift images of metabolites at in vivo concentrations, phantoms of NAA and choline at 10 mM concentrations, doped with gadolinium to shorten the T1 to ⬃250 msec, were investigated at 1.5 T. The parameters of the experiment were as follows: TR/TE 500/115 ms;15 mm slice thickness; NEX 64; and offset ⫺17.6 to 16.5 in 1.1 mecs ⌬ increments relative to the 1807 pulses. Imaging time was ⬃17 min. In this case, the data were processed with a Hamming window in all three dimensions to reduce truncation artifacts from a limited number of tau encoding steps as well as for improvement of the SNR in the x and y dimensions. Figure 3a demonstrates the application of EP CSI on phantoms of NAA and choline. SNR values measured ⬃9:1 for NAA (2.0 ppm) and ⬃7:1 for NAA (2.6 ppm) and ⬃11:1 for choline (3.2 ppm). The binomial (14641) was optimized for resonances occurring at 2.6 ppm to allow for comparable excitation of both choline and NAA. The close proximity of the beta methylene protons of NAA to the optimal frequency results in the high SNR of this resonance. Figure 3b shows this same experiment done with a NEX of 16, reducing the imaging time to ⬃4 min. SNR values are ⬃5:1
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FIG. 3. Application of EP CSI at 1.5 T on phantoms of NAA and choline with 10 mM concentrations doped with gadolinium to shorten the T1 to ⬃250 msec. The parameters were as follows: TR/TE 500/115 ms;15 mm slice thickness; NEX 64; and offset ⫺17.6–16.5 in 1.1 msec ⌬ increments relative to the 180° pulses. Imaging time ⬃17 min. a: EP CSI on phantoms of NAA and choline. SNR values measured ⬃9:1 for NAA (2.0 ppm) and ⬃7:1 for NAA (2.9 ppm) and ⬃11:1 for choline (3.2 ppm). The close proximity of the beta methylene protons of NAA to the optimal frequency results in the high SNR of this resonance. b: Same experiment with NEX 16, imaging time ⬃4 min. SNR values are ⬃5:1 for NAA (2.0 ppm) and ⬃4:1 for NAA (3.0 ppm) and ⬃6:1 for choline (3.2 ppm).
for NAA (2.0 ppm) and ⬃4:1 for NAA (2.6 ppm) and ⬃6:1 for choline (3.2 ppm). Figure 4 represents a magnitude spectrum from a 1.2 ml voxel taken at 3.0 T within the GE ‘‘Spectroscopy Head’’ phantom that contains in vivo concentrations of brain metabolites (i.e., [NAA] ⬃12.5 mM with a T2 ⬃400 msec; [Cr] 10 mM with a T2 ⬃265 msec; and [Chol] 3 mM with a T2 ⬃175 msec) and shows that the spectral resolution is adequate to separate the major metabolites of close proximity (i.e., choline and creatine). Parameters included the following: TR/TE 2000/160 msec; 128 1807 pulse offsets (tau ⫺35.2–34.7 msec in 0.55 msec increments); 64 ⫻ 64 matrix with 40 ⫻ 40 cm FOV and 10 mm slice thickness; and a NEX of 4. Voxel sizes were 360l. Complete 3D CSI data acquisition times were ⬃8 min. Data were zero-filled to 512 points prior to FT. SNR values were ⬃11 for NAA (2.0 ppm), and ⬃4 for creatine (3.2 ppm). In this case, the
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binomial was optimized for resonances occurring at 2.4 ppm to allow for comparable excitation of both creatine and NAA. We compared EP CSI (with 128 1807 pulse offsets; tau ⫺35.2–34.7 msec in 0.55 msec increments; 64 ⫻ 64 matrix with 40 ⫻ 40 cm FOV and 10 mm slice thickness; and a NEX of 8) with a conventional experiment (with 1024 spectral points and a spectral bandwidth of 2500 Hz; 32 ⫻ 32 matrix with a 20 ⫻ 20 cm FOV) using the GE ‘‘spectroscopy’’ head phantom. Both experiments had the following constant parameters: TR/TE 2000/160 msec and voxel size 360l. Complete 3D CSI data acquisition times were ⬃16 min. For EP CSI the binomial (14641) was optimized for resonances occurring at 2.0 ppm to allow for comparable comparison of SNR for NAA between EP CSI and conventional techniques, and post-processing included zerofilling to 512 points prior to FT. A region of interest comprising 4 voxels (⬃1.2 ml) was taken from the center of the phantom, and SNR values were ⬃27 for NAA (2.0 ppm) for EP CSI and ⬃45 for NAA for conventional CSI. Figure 5 is a representative image of the application of this technique on normal human volunteers at 3.0 T. Parameters included the following: TR/TE 1500/130 msec; tau offset ⫺17.6–16.5 msec in 0.55 msec increments (64 tau encoding steps); 128 ⫻ 128 matrix with 40 ⫻ 40 cm FOV (3 ⫻ 3 mm pixel size); a slice thickness of 10 mm; and a NEX of 32. Complete 3D CSI data acquisition times were 51 min. Equivalent voxel sizes were 360l. In this case the binomial pulse was optimized for the NAA resonance at 2.0 ppm. Figure 5a demonstrates metabolite images from the NAA resonance with and without fat masking. Figure 5b represents a spectrum taken from a 1.2 ml voxel within the parietal lobe. Metabolite images of NAA (SNR ⬃13:1) demonstrate clear discrimination of the ventricles in the NAA image and intercerebral fissure. The technique was applied again to a normal human volunteer with a variant in the following parameters:
FIG. 4. Spectrum obtained from a 1.2 ml region of interest from an EP CSI experiment on a GE ‘‘Spectroscopy Head’’ phantom with in vivo concentrations of metabolites (see text for concentrations and relaxation times for specific metabolites). Parameters included the following: 128 180° pulse offsets (tau ⫺35.2–34.7 msec in 0.55 msec increments); 64 ⫻ 64 matrix with 40 ⫻ 40 cm FOV and 10 mm slice thickness; and NEX 4. Voxel sizes were 360µl. Complete 3D CSI data acquisition time was ⬃8 min for a NEX of 4.
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FIG. 5. Application of EP CSI on a normal human volunteer. Parameters included the following: TR/TE 1500/130 msec; tau offset ⫺17.6–16.5 msec in 0.55 msec increments (64 tau encoding steps); 128 ⫻ 128 matrix with 40 ⫻ 40 cm FOV (3 ⫻ 3 mm pixel size); slice thickness of 10 mm; and NEX of 32. Complete 3D CSI data acquisition times were 51 min. In this case the binomial pulse was optimized for the NAA resonance at 2.0 ppm. a: Water image on the left and metabolite images from the NAA resonance with and without masking of the extraneous lipid signal. Metabolite images of NAA (SNR ⬃13:1) demonstrate clear discrimination of the ventricles in the NAA image and intercerebral fissure. b: Spectrum taken from a 1.2 ml voxel within the parietal lobe. Processing included zero-filling the data in the tau dimension to 256 points prior to Fourier transformation.
TR/TE 1000/160 msec; tau offset ⫺35.2–33 msec in 0.55 msec increments (128 tau encoding steps); 128 ⫻ 128 matrix with 40 ⫻ 40 cm FOV (3 ⫻ 3 mm pixel size); a slice thickness of 10 mm; and a NEX of 16. Complete 3D CSI data acquisition times were 34 min. The SNR measured approximately 8:1.
DISCUSSION These data demonstrate the feasibility of EP CSI to produce high spatial resolution metabolite maps with spectral resolution adequate to produce representative metabolite images. EP CSI offers certain advantages that are not available to the other conventional techniques. Because each pulse acquires a complete 2D image, in-plane motion can be corrected by re-registration of each image prior to FT
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in the spectral domain. In this regard our technique is different from other, previously described echoplanarbased CSI techniques (5,6), which require multiple excitation for each spatial encoding step. Furthermore, the chemical shift artifact seen in standard EPI is essentially eliminated with this technique because each image comes from a specific frequency and has a uniform pixel shift. With this knowledge, each specific frequency bin can be shifted the appropriate number of pixels as a postprocessing step. The superior spatial resolution (3 mm in-plane) of EP CSI results from its rapid traversal through k-space. The capability to encode spatially 128 ⫻ 128 matrices in two or three dimensions within clinically reasonable times separates EP CSI from other conventional techniques that rely on phase encoding each spatial dimension per excitation. At a TR of 1.5 sec, conventional double phase-encoded CSI would take ⬃6 hr to encode a 128 ⫻ 128 matrix, or 1 hr and 42 min to encode a 64 ⫻ 64 matrix, which reproduces the equivalent voxel dimensions of Fig. 5. The tradeoff between spatial and spectral resolution inherent in our technique implies that EP CSI is not ideal for distinctly imaging closely adjacent peaks; Fig. 4 suggests that resolving creatine and choline is close to the spectral resolution limit practical at field strengths of 3.0 T and under. Furthermore, EP CSI offers no distinct advantage in imaging very low concentration moieties, since spatial resolution of such CSI data is limited by SNR constraints, rather than image encoding time. However, for metabolites with relatively high concentration and long T2s, EP CSI should confer significant advantages, especially at higher field strengths with the attendant greater SNR and spectral dispersion. One application that we have placed particular emphasis on is mapping of neuronal content using NAA as a neuronal marker. NAA is a neuron-specific brain metabolite evident from biochemical, immunocytochemical, and spectroscopic data (15–18). NAA is quite prominent in the in vivo proton spectrum, which suggests that utilizing EP CSI to study neurodegenerative disease by imaging the putative, concordant decrease of NAA in these disorders would provide an in vivo index of neuronal loss (19–28). As with previous comparisons of EPI to conventional imaging (see, for instance, Chapter 5 in ref. 29), our results obtained from SNR measurements of the NAA images indicate that the SNR, per unit time and voxel size, is smaller with EP CSI (but potentially greater in an optimized version [29,30]) compared with conventional CSI. The difference in SNR, per unit time, comes from the difference in acquisition times between EP CSI and conventional CSI. A simple example may clarify this matter. Keeping the pixel dimensions and FOV constant, we can simplify the comparison of EP CSI to conventional CSI as a ratio of the total time encoding the spectral information. For conventional CSI a reasonable experimental design would entail a 2000 Hz spectral width with a collection of 512 points. To encode spatially the same pixel dimensions as we obtain in EP CSI, a conventional CSI experiment would encode a matrix of 128 points in each dimension. The SNR for this
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experiment is proportional to the relationship shown below in Eq. [1]: SNR (conventional CSI) ⬃ (128*128*512/(2000))1/2 ⫽ 64.76
Eq[1]
Assuming a TR of 1 sec, we could encode this information in 16,384 sec. For EP CSI the rapid sampling required to traverse k-space broadens the bandwidth to 256 kHz. Using an identical FOV as above and encoding 128 points in each spatial dimension, we collect our spectral information in 128 tau encoding steps. Using Eq. [1], we obtain the following relationship: SNR (EP CSI) ⬃ (128*128*128/(256000))1/2 ⫽ 2.87
Eq[2]
Assuming a TR of 1 sec, we could encode this information in 128 sec. If we signal average with EP CSI for the same 16,384 sec, we obtain a ratio of SNR (conventional CSI)/ SNR (EP CSI) of ⬃2:1. This difference comes as a result of the shorter total data collection time. We performed an experiment on a head phantom to compare SNR between EP CSI and conventional CSI directly. These comparisons demonstrated a ratio of conventional CSI/EP CSI of ⬃1.67:1. These differences are better than our theoretical calculations. Furthermore, in an estimate of the reproducibility of the technique in vivo, we demonstrated in two subjects an average SNR of ⬃8.5 in 17 min of averaging with a variance of ⬃1.4 for comparable averaging times taking T2 and T1 effects into account for the different TE/TR from the different experiments. However, EPI is very flexible, and the use of multiecho acquisition strategies applied to EP CSI sequences would provide significantly improved SNR. For example, we estimate that the implementation of a four-echo CPMG would provide an additional ⬃50% improvement in SNR for long T2 species such as NAA (T2 300 msec). This estimate comes from theoretically averaging additional echo trains (maximum of 4) that are each completely spatially encoded. The problems that are inherent with this include properly centering each echo in k-space in addition to the problems of keeping the phase of each chemical shift moiety uniform through these perturbations. The flexibility of EP CSI allows for these improvements in SNR to be directly translated into increased spatial or temporal resolution, as is fitting the specific biological application. Other areas of improvement will include implementation of improved water suppression and implementation of volumetric coverage. We are presently using frequencyselective 1807 pulses to provide water suppression in our EP CSI images. The binomial 14641 provided ⬎2000:1 suppression of the water signal in our EP CSI images. However, the excitation profile of this pulse is narrow and precludes EP CSI in its present version from providing quantitative information about metabolites other than NAA. Although adequate for the purposes of high spatial resolution NAA mapping, other pulses (i.e., palindromic [31], and other composite pulses) may offer broader excitation profiles without any decrease in water suppression. Other
water suppression techniques are presently being implemented and tried, and in future versions, the best technique for each specific application will be utilized. Because we presently use a binomial 1807 pulse for water suppression, which eliminates the possibility of ‘‘multislice’’ data, we are constrained to utilize 3D acquisitions for volumetric coverage. Unlike other conventional techniques, EP CSI lends itself easily to full 3D spatial encoding without a loss in temporal resolution because of the multiple NEX required to obtain useful SNR. In summary, a robust echoplanar chemical shift imaging method has been developed. Application of this technique on normal human volunteers has produced chemical shift images of NAA with spatial resolution that is improved relative to existing CSI. This technique offers a unique tradeoff in spatial and spectral resolution, lying at one end of a spectrum of CSI techniques that has conventional CSI at the other extreme (very high spectral, low spatial), with other novel encoding schemes between them (e.g., refs. 5 and 6). Since multiple NEX are required for useful metabolite SNR, full 3D spatial encoding should provide volumetric images in the same time. Multiple echo acquisitions, high field imaging, and improvements in coil design, including phased arrays, should in theory decrease imaging times to 10 min or less, making it feasible for highresolution metabolic maps to be routinely acquired as part of a comprehensive functional imaging examination.
ACKNOWLEDGMENTS This work was supported in part by NIH grants NS34626 from the National Institute of Neurological Disorders and Stroke (to R.G.G.) and RR13213 from the National Center for Research Resources (to R.G.G.), as well as 5 R01 CA40303 and 5R01 AG10679. The authors gratefully thank Dr. Timothy Reese for assistance in pulse sequence development and Dr. Joseph Mandeville for assistance in data processing.
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