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In vivo macromolecule signals in rat brain 1 H‐MR spectra at 9.4T: Parametrization, spline baseline estimation, and T 2 relaxation times

Type of publication Peer-reviewed
Publikationsform Original article (peer-reviewed)
Author Simicic Dunja, Rackayova Veronika, Xin Lijing, Tkáč Ivan, Borbath Tamas, Starcuk Zenon, Starcukova Jana, Lanz Bernard, Cudalbu Cristina,
Project Translational Non-Invasive Metabolic Studies towards Novel Treatments of Chronic Hepatic Encephalopathy in Developing Brain, from 3D Organotypic Brain Cell Cultures to the In vivo Rat and Human Brain
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Original article (peer-reviewed)

Journal Magnetic Resonance in Medicine
Volume (Issue) 86(5)
Page(s) 2384 - 2401
Title of proceedings Magnetic Resonance in Medicine
DOI 10.1002/mrm.28910

Open Access

URL https://infoscience.epfl.ch/record/287462/files/mrm.28910.pdf
Type of Open Access Repository (Green Open Access)

Abstract

Purpose: Reliable detection and fitting of macromolecules (MM) are crucial for accurate quantification of brain short-echo time (TE) 1 H-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 1 H-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.
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