Two 3T whole-body Siemens Tim Trio (Siemens Medical Solutions, Erlangen, Germany) scanners were used in this study; one located at the Center for Magnetic Resonance Research (CMRR) in Minnesota and the other one at the Institut du Cerveau et de la Moelle (ICM) in Paris. Age- and BMI-matched healthy subjects (Table 1 ) were enrolled after giving informed consent according to procedures approved by the Institutional Review Board at CMRR and by the local ethics committee at ICM. The standard body RF coil was used for radiofrequency transmission and the 32-channel phased-array Siemens head coil was used for signal reception. Soft pads were used to hold each subject’s head in place to minimize head movement in the MR system. T1-weighted MPRAGE images (repetition time (TR) = 2530ms, echo time (TE) = 3.65 ms, flip angle = 7°, slice thickness = 1 mm, 224 slices, field-of-view = 256×176 mm2, matrix size = 256×256) were acquired to position the volume-of-interest (VOI) for MRS measurements. B0 shimming was achieved using an adiabatic version of FAST(EST)MAP (16 (link)), which is available as a work-in-progress (WIP) package on the Siemens system.
Proton spectra were acquired using a modified semi-LASER sequence (TE = 28 ms, TR = 5 s, 64 averages) (14 (link)) from two VOIs: cerebellar vermis (10×25×25 mm3) and pons (16×16×16 mm3). Voxel placement was based on anatomical landmarks. The fourth ventricle, cervical spinal cord and the brainstem were used to separate the cerebellum. The surfaces, lobes, lobules and fissures of the cerebellum were then used as landmarks in positioning the voxel in the vermis. For pons VOI placement, the midbrain, fourth ventricle and the medulla were used as landmarks.
The semi-LASER sequence (14 (link)) used in this study is a more compact version of the originally published semi-LASER sequence (17 (link)). Briefly, the sequence consisted of a 2 ms asymmetric slice-selective 90° pulse (18 (link)) followed by two pairs of slice selective adiabatic full passage (AFP) pulses (4 ms duration, HS4 modulation, R25) (19 ), which were interleaved, rather than applied sequentially, to improve suppression of unwanted coherences with shorter spoiler gradient pulses. Water suppression was achieved with VAPOR, which was interleaved with outer volume suppression (OVS) to suppress unwanted coherences (18 (link)). A substantially lower chemical shift displacement error is obtained with the semi-LASER sequence (3.6% /ppm for the slice-selective 90° pulse and 2% /ppm for the AFP pulses) compared to the standard PRESS sequence provided on the Siemens platform (12–13% /ppm).
B1 levels required for localization pulses and for water suppression were adjusted for each voxel. Specifically, the RF power magnitude for the 90° asymmetric pulse was calibrated by monitoring the signal intensity whilst increasing the RF power and choosing the RF power setting that produced the maximum signal. The power for the AFP pulses was automatically set relative to the 90° pulse. A similar procedure was carried out for the water suppression calibration.
On the scanner, signals from individual coil elements were combined after correcting for phase shifts between elements and weighting them based on the coil sensitivities (20 (link)) to generate a free induction decay (FID). Each FID was then individually saved for shot-to-shot frequency and phase correction before averaging. Two non-suppressed water spectra were acquired: one for eddy current correction (the RF pulses of the VAPOR scheme were turned off) and one for use as reference for metabolite quantification (VAPOR and OVS schemes turned off in order to eliminate magnetization transfer effects). To evaluate the cerebrospinal fluid (CSF) contribution to each VOI, fully relaxed unsuppressed water signals were acquired at different TE’s ranging from 28–4000 ms (TR = 15 s) with the entire VAPOR and OVS scheme turned off (21 ).
All spectral processing was performed in Matlab by the same person prior to LCModel fitting. Eddy current correction was carried out first to correct for distorted line shapes and zero-order phase. Individual shots affected by subject motion (based on water suppression efficiency) were removed. Single-shot frequency correction was performed using a cross-correlation algorithm and phase correction was performed using a least-square fit algorithm. All steps were completely automated except for the removal of FIDs affected by motion. Finally the summed spectrum was referenced based on NAA resonance at 2.01 ppm.
Spectra were then analyzed with LCModel (22 (link)) with the water scaling option (version 6.3-0G). The model basis set was generated based on density matrix formalism as described before (23 (link)). The basis set also included macromolecule spectra, which were acquired using inversion-recovery technique in 4 healthy subjects (total averages = 928, TR = 2.5 s, inversion time, TI = 0.75 s, VOI = 15.6 mL, 5 ms duration HS5 inversion pulse, occipital cortex). Due to the shorter T1 relaxation time of the methylene protons of tCr at 3.93 ppm relative to other metabolite protons (24 (link)), this resonance was present in the metabolite-nulled macromolecule spectra and was removed using a Hankel singular value decomposition (HSVD) algorithm in Matlab. A 12.5 Hz Gaussian line broadening was also applied to the macromolecule spectra after incorporating a reference peak at 0 ppm (seesupplementary material ). No baseline correction, zero-filling or apodization functions were applied to the in vivo data prior to the analysis. LCModel fitting (supplementary material ) was performed over the spectral range from 0.5–4.2 ppm.
Metabolite concentrations were determined after correcting for tissue water content and CSF contributions in the selected VOI using the water-scaling option in LCModel. The transverse relaxation times (T2) of tissue water and % CSF contribution to the VOI were obtained by fitting the integrals of the unsuppressed water spectra acquired in each VOI at different TE values with a bi-exponential fit (21 ), with the T2 of CSF fixed at 740 ms based on measurement of T2 of water in a small voxel located in ventricles with the same semi-LASER sequence (4 healthy subjects, TR = 15 s, VOI = 0.125–0.360 mL, twelve TE values ranging from 28–4000 ms), and three free parameters: T2 of tissue water, amplitude of tissue water, and amplitude of CSF water.
In order to obtain accurate metabolite concentrations, corrections must be made for T2 relaxation of both water and metabolites. In the case of semi-LASER, T2 relaxation is slowed due to the Carr-Purcell (CP) conditions, and T2 values under CP conditions must be used for quantification. For water, these values can be estimated by correcting the free precession T2 value measured for the tissue water signal at different echo-times by a fixed factor to account for CP effects. A previous study compared water T2 values measured with LASER and CP-LASER sequences at 4T and 7T (25 (link)). Extrapolating from that study, we assumed that the T2 of water under CP conditions is 1.5× longer than the measured free precession T2 at 3T. Signal loss due to T2 relaxation of metabolites was neglected since the apparent T2 is sequence-dependent. This assumption is justified by the fact that metabolites have longer T2 such that correction factors would be small at TE = 28 ms. Nonetheless this choice will result in somewhat underestimated metabolite concentrations relative to the true concentrations in tissue. A water content of 82% and 72% was used for vermis and pons, respectively (26 ,27 ).
Metabolites that were quantified with Cramér-Rao lower bounds (CRLB) ≤ 50% from at least half of the spectra from a particular brain region were included in the neurochemical profile. In addition, if the correlation between two metabolites was very high (i.e. correlation coefficient r more negative than −0.7) in the majority of the spectra from a region, then only their sum was reported, e.g. tCr (creatine + phosphocreatine) and tCho (glycerophosphorylcholine + phosphorylcholine). If there was indication for pairwise correlation with r from −0.5 to −0.7, then the concentration sum of the pair was reported in addition to the individual metabolites’ concentrations, e.g. NAA, NAAG and total NAA (tNAA, NAA + NAAG), as recommended by the LCModel manual, Jan 2013 (22 (link)). Moreover, spectra with the associated water reference linewidth greater than 10 Hz were excluded due to trends observed in overestimating aspartate and ascorbate and underestimating glutamate in these spectra. Water linewidths > 10 Hz only occurred for spectra acquired from the pons region.
Proton spectra were acquired using a modified semi-LASER sequence (TE = 28 ms, TR = 5 s, 64 averages) (14 (link)) from two VOIs: cerebellar vermis (10×25×25 mm3) and pons (16×16×16 mm3). Voxel placement was based on anatomical landmarks. The fourth ventricle, cervical spinal cord and the brainstem were used to separate the cerebellum. The surfaces, lobes, lobules and fissures of the cerebellum were then used as landmarks in positioning the voxel in the vermis. For pons VOI placement, the midbrain, fourth ventricle and the medulla were used as landmarks.
The semi-LASER sequence (14 (link)) used in this study is a more compact version of the originally published semi-LASER sequence (17 (link)). Briefly, the sequence consisted of a 2 ms asymmetric slice-selective 90° pulse (18 (link)) followed by two pairs of slice selective adiabatic full passage (AFP) pulses (4 ms duration, HS4 modulation, R25) (19 ), which were interleaved, rather than applied sequentially, to improve suppression of unwanted coherences with shorter spoiler gradient pulses. Water suppression was achieved with VAPOR, which was interleaved with outer volume suppression (OVS) to suppress unwanted coherences (18 (link)). A substantially lower chemical shift displacement error is obtained with the semi-LASER sequence (3.6% /ppm for the slice-selective 90° pulse and 2% /ppm for the AFP pulses) compared to the standard PRESS sequence provided on the Siemens platform (12–13% /ppm).
B1 levels required for localization pulses and for water suppression were adjusted for each voxel. Specifically, the RF power magnitude for the 90° asymmetric pulse was calibrated by monitoring the signal intensity whilst increasing the RF power and choosing the RF power setting that produced the maximum signal. The power for the AFP pulses was automatically set relative to the 90° pulse. A similar procedure was carried out for the water suppression calibration.
On the scanner, signals from individual coil elements were combined after correcting for phase shifts between elements and weighting them based on the coil sensitivities (20 (link)) to generate a free induction decay (FID). Each FID was then individually saved for shot-to-shot frequency and phase correction before averaging. Two non-suppressed water spectra were acquired: one for eddy current correction (the RF pulses of the VAPOR scheme were turned off) and one for use as reference for metabolite quantification (VAPOR and OVS schemes turned off in order to eliminate magnetization transfer effects). To evaluate the cerebrospinal fluid (CSF) contribution to each VOI, fully relaxed unsuppressed water signals were acquired at different TE’s ranging from 28–4000 ms (TR = 15 s) with the entire VAPOR and OVS scheme turned off (21 ).
All spectral processing was performed in Matlab by the same person prior to LCModel fitting. Eddy current correction was carried out first to correct for distorted line shapes and zero-order phase. Individual shots affected by subject motion (based on water suppression efficiency) were removed. Single-shot frequency correction was performed using a cross-correlation algorithm and phase correction was performed using a least-square fit algorithm. All steps were completely automated except for the removal of FIDs affected by motion. Finally the summed spectrum was referenced based on NAA resonance at 2.01 ppm.
Spectra were then analyzed with LCModel (22 (link)) with the water scaling option (version 6.3-0G). The model basis set was generated based on density matrix formalism as described before (23 (link)). The basis set also included macromolecule spectra, which were acquired using inversion-recovery technique in 4 healthy subjects (total averages = 928, TR = 2.5 s, inversion time, TI = 0.75 s, VOI = 15.6 mL, 5 ms duration HS5 inversion pulse, occipital cortex). Due to the shorter T1 relaxation time of the methylene protons of tCr at 3.93 ppm relative to other metabolite protons (24 (link)), this resonance was present in the metabolite-nulled macromolecule spectra and was removed using a Hankel singular value decomposition (HSVD) algorithm in Matlab. A 12.5 Hz Gaussian line broadening was also applied to the macromolecule spectra after incorporating a reference peak at 0 ppm (see
Metabolite concentrations were determined after correcting for tissue water content and CSF contributions in the selected VOI using the water-scaling option in LCModel. The transverse relaxation times (T2) of tissue water and % CSF contribution to the VOI were obtained by fitting the integrals of the unsuppressed water spectra acquired in each VOI at different TE values with a bi-exponential fit (21 ), with the T2 of CSF fixed at 740 ms based on measurement of T2 of water in a small voxel located in ventricles with the same semi-LASER sequence (4 healthy subjects, TR = 15 s, VOI = 0.125–0.360 mL, twelve TE values ranging from 28–4000 ms), and three free parameters: T2 of tissue water, amplitude of tissue water, and amplitude of CSF water.
In order to obtain accurate metabolite concentrations, corrections must be made for T2 relaxation of both water and metabolites. In the case of semi-LASER, T2 relaxation is slowed due to the Carr-Purcell (CP) conditions, and T2 values under CP conditions must be used for quantification. For water, these values can be estimated by correcting the free precession T2 value measured for the tissue water signal at different echo-times by a fixed factor to account for CP effects. A previous study compared water T2 values measured with LASER and CP-LASER sequences at 4T and 7T (25 (link)). Extrapolating from that study, we assumed that the T2 of water under CP conditions is 1.5× longer than the measured free precession T2 at 3T. Signal loss due to T2 relaxation of metabolites was neglected since the apparent T2 is sequence-dependent. This assumption is justified by the fact that metabolites have longer T2 such that correction factors would be small at TE = 28 ms. Nonetheless this choice will result in somewhat underestimated metabolite concentrations relative to the true concentrations in tissue. A water content of 82% and 72% was used for vermis and pons, respectively (26 ,27 ).
Metabolites that were quantified with Cramér-Rao lower bounds (CRLB) ≤ 50% from at least half of the spectra from a particular brain region were included in the neurochemical profile. In addition, if the correlation between two metabolites was very high (i.e. correlation coefficient r more negative than −0.7) in the majority of the spectra from a region, then only their sum was reported, e.g. tCr (creatine + phosphocreatine) and tCho (glycerophosphorylcholine + phosphorylcholine). If there was indication for pairwise correlation with r from −0.5 to −0.7, then the concentration sum of the pair was reported in addition to the individual metabolites’ concentrations, e.g. NAA, NAAG and total NAA (tNAA, NAA + NAAG), as recommended by the LCModel manual, Jan 2013 (22 (link)). Moreover, spectra with the associated water reference linewidth greater than 10 Hz were excluded due to trends observed in overestimating aspartate and ascorbate and underestimating glutamate in these spectra. Water linewidths > 10 Hz only occurred for spectra acquired from the pons region.
