Ke Dai¹, Hao Chen¹, Hongda Shao², Jianjun Liu², and Zhiyong Zhang^1
1School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China, ²Departments of Nuclear Medicine, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China

xSPEN is a single-shot echo-planar imaging-based MRI approach with exceptional resilience to chemical shifts and field inhomogeneities. We introduce a time increasing (t₁) evolution as chemical shift encoding to fast obtain multiple-voxel spectroscopy. The new method endows a 2D self-navigated motion correction and a unique J-decoupled spectrum by splitting the t₁ evolution into τ-t₁/2 and t₁/2 on two sides of π pulse, which results a constant-τ J coupling evolution. We present in vitro results, demonstrating an alternative fast MRSI and increasing chemical shift separation and detection with the robustness to the in-plane motion and the unique J-decoupled spectrum capability.

Antoine Klauser^1,2, Sebastien Courvoisier^1,2, Michel Kocher^1,2, and François Lazeyras^1,2
1Radiology and Medical Informatics, University of Geneva, Geneva, Switzerland, ²CIBM Center for Biomedical Imaging, Geneva, Switzerland

A fast 1H 3D Adiabatic Spin-Echo (ADISE) MRSI sequence was implemented to measure metabolite distributions over the whole brain with 5mm isotropic resolution. MRSI data were measured on volunteers and compared with FID-MRSI sequence. ADISE-MRSI and FID-MRSI acquisitions were accelerated with compressed-sensing and reconstructed with a Low-Rank TGV-constrained model.

Manoj Kumar Sarma^1,2, Andres Saucedo³, and M. Albert Albert Thomas^3
1Advanced Imaging Research Center, UT Southwestern Medical Center, Dallas, TX, United States, ²Radiology, UT Southwestern Medical Center, Dallas, TX, United States, ³Radiology, UCLA School of Medicine, Los Angeles, CA, United States

Diffusion-weighted spectroscopy (DW-MRS) is an excellent tool to explore the compartment specific assessment of tissue microstructure. Although there has been growing interest in DW-MRS for clinical applications, most of the studies involving human brain metabolites so far have used single-voxel methods, which limit its application to specific white matter tracts or arbitrarily selected regions of interest. There has been only a few attempts to evaluate the diffusion properties of brain metabolites with DW-MRSI. Here, we propose an echo planar-based diffusion-weighted spectroscopic imaging using semi-LASER localization and bipolar diffusion gradients. Initial results show good spectral quality and spatial localization.

Saipavitra Murali-Manohar^1,2, Tamas Borbath^1,2, Andrew Martin Wright^1,3, and Anke Henning^1,4
1High Field Magentic Resonance, Max Planck Institute for Biological Cybernetics, Tuebingen, Germany, ²Faculty of Science, University of Tuebingen, Tuebingen, Germany, ³IMPRS for Cognitive Neuroscience, Tuebingen, Germany, ⁴Advanced Imaging Research Center, UT Southwestern Medical Center, Dallas, TX, United States

Crowded proton spectra with severely overlapped J-coupled resonances pose a challenge in the reliable quantification of metabolites in the human brain. Several advanced techniques such as editing methods, multi-dimensional spectroscopy methods, sophisticated processing or quantification pipelines were proposed in the past. In this work, we present a two-dimensional metabolite-cycled semiLASER technique at 9.4 T with maximum echo sampling scheme. This method helps well resolve the J-coupled peaks and clearly distinguish them. 2D spectral fitting is performed using ProFit2.0 and the metabolites are quantified using internal water referencing after correcting the fitted concentration for tissue content and relaxation effects.

Song-I Lim^1,2 and Lijing Xin^1,2
1CIBM Center for Biomedical Imaging, Lausanne, Switzerland, ²Animal Imaging and Technology, EPFL, Lausanne, Switzerland

The purpose of the study is to compare short-TE and MEGA editing methods and verify reproducibility of GABA measurement in the motor cortex at 7T. The measured average GABA/Cr and GABA/NAA ratios were 0.121 ± 0.034 and 0.057 ± 0.019 respectively for short-TE sSPECIAL measurement and 0.083 ± 0.014 and 0.052 ± 0.008 respectively for MEGA-sSPECIAL sequence. 6 healthy volunteers were scanned two times and average coefficient of variances were 21.2 ± 11.8 % for short-TE measurement and 4.5 ± 3.9 for MEGA-sSPECIAL sequence.

Eloïse Mougel¹, Sophie Malaquin¹, Melissa Vincent¹, and Julien Valette^1
1Université Paris-Saclay, Commissariat à l'Energie Atomique et aux Energies Alternatives (CEA), Centre National de la Recherche Scientifique (CNRS), Molecular Imaging Research Center (MIRCen), Laboratoire des Maladies Neurodégénératives, Fontenay aux Roses, France

Brain lactate compartmentation is an important but debated neuroscience question. By assessing local microstructure where lactate is diffusing in, diffusion-weighted MRS has unique potential to non-invasively assess lactate compartmentation. We propose to increase lactate signal using selective pulses (SP) to cancel J-modulation. We compare lactate signal behavior in diffusion-weighted experiments performed in vivo, using either spin echo or stimulated echo sequence relying on selective pulses. We verify here that the signal increases in both cases, compared to conventional cases using broad pulses. Spin echo using SP appears the most valuable option to measure lactate diffusion at high b-values.

Chathura Kumaragamage¹, Anastasia Coppoli¹, Peter B Brown¹, Scott McIntyre¹, Terence W Nixon¹, Henk M De Feyter¹, Graeme Mason¹, and Robin A de Graaf^1
1Department of Radiology and Biomedical Imaging, Magnetic Resonance Research Center, Yale University, New Haven, CT, United States

An ECLIPSE-IVS based MRSI method was developed utilizing 3 ms GOIA-WURST RF pulses (BW = 15 kHz), operating at an RF amplitude B_1(95%) = 0.87 kHz.  The ECLIPSE-IVS method was preceded with a water suppression module incorporating an optional inversion recovery (IR) component, to achieve macromolecule-nulled acquisitions. MRSI in vivo demonstrate robust extracranial lipid suppression with reliable, artifact-free metabolic maps generated with peak integration and LCModel fitting.

Chloé Najac¹, Marjolein Bulk¹, Hermien E. Kan¹, Andrew G. Webb¹, and Itamar Ronen^1
1C.J. Gorter Center for High Field MRI, Department of Radiology, Leiden University Medical Center, Leiden, Netherlands

We propose a method to calculate T2* values of brain metabolites from a series of time-shifted datasets obtained from a single ¹H magnetic resonance spectroscopy acquisition. T2* values from five brain metabolites were measured in the posterior cingulate cortex. Robust T2* values were obtained for all five metabolites, including J-coupled metabolites such as glutamate and myo-inositol, for which T2* estimation is otherwise not possible. We show in a subsequent reproducibility study that the water linewidth within the same volume can be used to account for variability in local B0 inhomogeneity and reduce the associated variability across measurements.

Frida Johansson^1,2, Helena Brisby^2,3, Hanna Hebelka^2,4, Maria Ljungberg^1,2, and Kerstin Lagerstrand^1,2
1Medical Physics and Biomedical Engineering, Sahlgrenska University Hospital, Gothenburg, Sweden, ²Institute of Clinical Sciences, Gothenburg University, Gothenburg, Sweden, ³Department of Orthopaedics, Sahlgrenska University Hospital, Gothenburg, Sweden, ⁴Department of Radiology, Sahlgrenska University Hospital, Gothenburg, Sweden

This study aimed to evaluate the effect of respiratory motion on disc MRS and propose an MRS-method that improves the signal-to-noise-ratio. Findings showed that the phase signal of the disc changes substantially between expiration and inspiration. With the proposed postprocessing method, all spectra gave a higher signal-to-noise-ratio (largest gain=30%). Present study shows that respiratory motion affects the disc phase signal and should be taken into consideration when evaluating the disc using MRS. The proposed method improved the quality of the MRS-spectrum and, thus, showed feasibility in measuring the molecular disc content non-invasively during normal breathing.

William T Clarke¹, Tiffany Bell^2,3,4, Uzay Emir^5,6, Mark Mikkelsen^7,8, Georg Oeltzschner^7,8, Benjamin C Rowland⁹, Amirmohammad Shamaei^10,11, Brian J Soher¹², Sofie Tapper^7,8, and Martin Wilson^13
1Wellcome Centre for Integrative Neuroimaging, NDCN, University of Oxford, Oxford, United Kingdom, ²Department of radiology, University of Calgary, Calgary, AB, Canada, ³Hotchkiss brain institute, University of Calgary, Calgary, AB, Canada, ⁴Alberta Children’s Hospital Research Institute, University of Calgary, Calgary, AB, Canada, ⁵School of Health Sciences, Purdue University, West Lafayette, IN, United States, ⁶Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN, United States, ⁷Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, United States, ⁸F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States, ⁹Division of Cancer Science, School of Medical Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, United Kingdom, ¹⁰Institute of Scientific Instruments of the CAS, Brno, Czech Republic, ¹¹Department of Biomedical Engineering, Faculty of Electrical Engineering and Communication, Brno University of Technology, Brno, Czech Republic, ¹²Center for Advanced MR Development, Department of Radiology, Duke University Medical Center, Durham, NC, United States, ¹³Centre for Human Brain Health and School of Psychology, University of Birmingham, Birmingham, United Kingdom

We propose a flexible data format for the storage of multidimensional MRS data. The lack of a single widely used data format in MRS hinders widespread use, consistent analyses, and open dissemination of data. Here, we adapt the widely adopted NIfTI format to store MRS data, extending NIfTI to include the additional meta-data required for MRS data interpretation. We present a pipeline for end-to-end analysis of MRS data and an open-source conversion tool. The community is encouraged to contribute to the format.