Proton MR spectra of the brain, especially those measured at short and intermediate echo times, contain signals from mobile macromolecules (MM). A description of the main MM is provided in this consensus paper. These broad peaks of MM underlie the narrower peaks of metabolites and often complicate their quantification but they also may have potential importance as biomarkers in specific diseases. Thus, separation of broad MM signals from low molecular weight metabolites enables accurate determination of metabolite concentrations and is of primary interest in many studies. Other studies attempt to understand the origin of the MM spectrum, to decompose it into individual spectral regions or peaks and to use the components of the MM spectrum as markers of various physiological or pathological conditions in biomedical research or clinical practice. The aim of this consensus paper is to provide an overview and some recommendations on how to handle the MM signals in different types of studies together with a list of open issues in the field, which are all summarized at the end of the paper.

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Purpose Reliable detection and fitting of macromolecules (MM) are crucial for accurate quantification of brain short‐echo time (TE) 1H‐MR spectra. An experimentally acquired single MM spectrum is commonly used. Higher spectral resolution at ultra‐high field (UHF) led to increased interest in using a parametrized MM spectrum together with flexible spline baselines to address unpredicted spectroscopic components. Herein, we aimed to: (1) implement an advanced methodological approach for post‐processing, fitting, and parametrization of 9.4T rat brain MM spectra; (2) assess the concomitant impact of the LCModel baseline and MM model (ie, single vs parametrized); and (3) estimate the apparent T2 relaxation times for seven MM components. Methods A single inversion recovery sequence combined with advanced AMARES prior knowledge was used to eliminate the metabolite residuals, fit, and parametrize 10 MM components directly from 9.4T rat brain in vivo 1H‐MR spectra at different TEs. Monte Carlo simulations were also used to assess the concomitant influence of parametrized MM and DKNTMN parameter in LCModel. Results A very stiff baseline (DKNTMN ≥ 1 ppm) in combination with a single MM spectrum led to deviations in metabolite concentrations. For some metabolites the parametrized MM showed deviations from the ground truth for all DKNTMN values. Adding prior knowledge on parametrized MM improved MM and metabolite quantification. The apparent T2 ranged between 12 and 24 ms for seven MM peaks. Conclusion Moderate flexibility in the spline baseline was required for reliable quantification of real/experimental spectra based on in vivo and Monte Carlo data. Prior knowledge on parametrized MM improved MM and metabolite quantification.

The steady-state free-precession (SSFP) acquisition mode may be found useful for fast in vivo proton magnetic resonance spectroscopic imaging in high-field MR systems because of the achievable signal-to-noise ratio and the avoidance of RF pulses with large flip angles. Detection of signals from metabolites with coupled-spin systems under SSFP has not yet been accomplished, but should be possible in high field, albeit with substantial signal truncation. It must be expected that the spin system evolution and the spectra will be affected by the steady-state conditions, which prevent the spin systems from returning to the Boltzmann equilibrium. Computer simulation is needed for the experiment design and spectrum quantification. This work outlines a suitable simulation method (QuaM-EPG), which combines and extends two pre-existing approaches: the density matrix calculation, used in high-resolution NMR, and the extended phase graph method, used to describe cyclic excitation in fast MRI of water protons. The method is illustrated by its application to model molecules and myo-inositol, which is one of the clinically relevant target molecules. It is shown that antiphase and multiple-quantum coherences may represent a considerable portion of the steady-state magnetization in a quantum-mechanical sense and that the spectral patterns are affected thereby.

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