Advanced Hadamard-encoded editing of seven low-concentration brain metabolites: Principles of HERCULES

Abstract

Purpose: To demonstrate the framework of a novel Hadamard-encoded spectral editing approach for simultaneously detecting multiple low-concentration brain metabolites in vivo at 3T. Methods: HERCULES (Hadamard Editing Resolves Chemicals Using Linear-combination Estimation of Spectra) is a four-step Hadamard-encoded editing scheme. 20-ms editing pulses are applied at: (A) 4.58 and 1.9 ppm; (B) 4.18 and 1.9 ppm; (C) 4.58 ppm; and (D) 4.18 ppm. Edited signals from γ-aminobutyric acid (GABA), glutathione (GSH), ascorbate (Asc), Nacetylaspartate (NAA), N-acetylaspartylglutamate (NAAG), aspartate (Asp), lactate (Lac), and likely 2hydroxyglutarate (2-HG) are separated with reduced signal overlap into distinct Hadamard combinations: (A+B+C+D); (A+B-C-D); and (A-B+C-D). HERCULES uses a novel multiplexed linear-combination modeling approach, fitting all three Hadamard combinations at the same time, maximizing the amount of information used for model parameter estimation, in order to quantify the levels of these compounds. Fitting also allows estimation of the levels of total choline (tCho), myo-inositol (Ins), glutamate (Glu), and glutamine (Gln). Quantitative HERCULES results were compared between two grey-and white-matter-rich brain regions (11 min acquisition time each) in 10 healthy volunteers. Coefficients of variation (CV) of quantified measurements from the HERCULES fitting approach were compared against those from a single-spectrum fitting approach, and against estimates from short-TE PRESS data.

Correcting frequency and phase offsets in MRS data using robust spectral registration

“…A similar approach has been demonstrated previously for correcting offsets in GSH-edited MEGA-PRESS data. 17 For data acquired with more complex multiplexed editing schemes, such as the one used in HERCULES, 15 the challenge is to choose a portion of signal that has a similar signal profile in pairs of subspectra. Although not shown here, preliminary testing showed that rSR aligns HERCULES data well.…”

“…6 The time-domain-based spectral registration method 11 is a simple yet efficient algorithm that accurately aligns single transients and has excellent performance. 12 The challenge of correcting frequency and phase shifts in datasets acquired by multiplexed editing schemes such as HERMES (Hadamard encoding and reconstruction of MEGA-edited spectroscopy) 13,14 or HERCULES (Hadamard editing resolves chemicals using linear-combination estimation of spectra) 15 necessitates more sophisticated routines, which have been addressed recently with a multistep approach incorporating spectral registration. 16 Additional challenges that make FPC difficult include instabilities in the residual water, lipid, and baseline signals 11,17 and low SNR of individual transients.…”

Osprey: Open-Source Processing, Reconstruction & Estimation of Magnetic Resonance Spectroscopy Data

“…In addition to the paths to the raw data files, the job file must specify the type of sequence (with or without spectral editing, such as MEGA (Mescher et al, 1998;Rothman et al, 1993), HERMES Saleh et al, 2016), or HERCULES (Oeltzschner et al, 2019a)), the target molecules of spectral editing experiments, and options for the fitting process, which are explained in Section 2.4.…”

“…In this case, the amplitude, lineshape, phase and linebroadening parameters are shared between the models for each sub-spectrum, while each sub-spectrum maintains its own baseline parameters and is allowed an additional small frequency shift to account for small inconsistencies between sub-spectra. The simultaneous modelling approach incorporates all available spectral information to constrain the model in a way that is most consistent with the data, thereby reducing the variability of the quantification results compared to unconstrained separate modelling (Oeltzschner et al, 2019a). When the 'Separate' fitting style is selected, each difference spectrum is modeled separately -one for MEGA-edited data, two (or more) for…”

Local and Interregional Neurochemical Associations Measured by Magnetic Resonance Spectroscopy for Studying Brain Functions and Psychiatric Disorders

“…To facilitate measurement of the absolute strength of neurochemical associations, MRS techniques that result in flat baselines and isolated signals of interest would be ideal. Many existing single voxel spectral editing techniques generate flat or weak baselines while eliminating or minimizing overlapping resonances (74,(108)(109)(110)(111)(112)(113)(114)(115), which are likely suited for measuring local or intraregional neurochemical associations. Mapping macroscopic neurochemical associations across the human brain has the exciting potential to broadly impact studies of normal brain functions as well as neuropsychiatric disorders (32,116,117).…”