Zepeng Wang^1,2 and Fan Lam^1,2
1Department of Bioengineering, University of Illinois Urbana-Champaign, Urbana, IL, United States, ²Beckman Institute for Advanced Science and Technology, Urbana, IL, United States

Diffusion-weighted MRSI (DW-MRSI) promises to significantly expand the capability of in vivo tissue microstructural imaging by simultaneously measuring the diffusion properties of several molecules other than water. However, the applications of DW-MRSI have been mostly limited to either single voxels or 2D experiments with very low resolutions due to several fundamental technical challenges. We describe here a novel method to achieve 3D DW-MRSI with an unprecedented combination of speed, resolution and SNR, by synergizing a special fast sequence and subspace-based processing. We successfully demonstrated high-SNR DW-MRSI of the brain and metabolite-specific ADC maps with the highest ever resolution (3.4×3.4×5.3 mm³).

Gilbert Hangel^1,2, Benjamin Spurny³, Philipp Lazen², Cornelius Cadrien^1,2, Sukrit Sharma², Zoe Käfer², Nikolaus Doblinger², Lukas Hingerl², Eva Hečková², Bernhard Strasser², Stanislav Motyka², Alexandra Lipka², Stephan Gruber², Christoph Brandner⁴, Rupert Lanzenberger³, Karl Rössler¹, Siegfried Trattnig^2,5, and Wolfgang Bogner^2
1Department of Neurosurgery, Medical University of Vienna, Vienna, Austria, ²High Field MR Centre, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria, ³Division of General Psychiatry, Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria, ⁴High Field MR Centre, Centre for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna, Austria, ⁵Christian Doppler Laboratory for Clinical Molecular MR Imaging, Vienna, Austria

Applying a 3D-MRSI sequence with ~3 mm isotropic resolution and 15 min measurement time at 7T to a cohort of 24 healthy subjects, we successfully estimated the concentrations of 13 brain metabolites in 44 regions using internal water referencing. We established inter-subject coefficients of variation in the range of 10-20%. The resulting concentration estimates corresponded well to previous research except for GSH.

Johanna Dorst¹, Tamas Borbath¹, and Anke Henning^1,2
1High-Field MR Center, Max Planck Institute for Biological Cybernetics, Tübingen, Germany, ²Advanced Imaging Research Center, UT Southwestern Medical Center, Dallas, TX, United States

Previous studies investigated relationships between the BOLD signal and metabolite concentration changes during visual stimulation by sequential or interleaved fMRI/fMRS measurements. The purpose of this study was to simultaneously investigate the dynamics of BOLD signal and metabolite levels in the activated human brain at 9.4T using the metabolite-cycling (MC) technique. A correlation between the MC water dynamics and concentration increases of lactate and glutamate during activation could be verified. Besides, it could be shown that the high spectral quality of fMRS at 9.4T facilitates separate fitting of creatine and phosphocreatine thereby enabling the calculation of pH dynamics during visual stimulation.

Li An¹, Shizhe Li¹, Maria Ferraris Araneta¹, Milalynn Victorino¹, Christopher Johnson¹, and Jun Shen^1
1National Institute of Mental Health, National Institutes of Health, Bethesda, MD, United States

A recently developed single-step spectral editing ¹H MRS technique that induces intense Glu and Gln H4 singlets at TE = 56 ms was used to measure fractional enrichments of glutamate and glutamine in the dorsal anterior cingulate cortex (dACC) of five healthy volunteers after oral administration of [U-¹³C]glucose. This technique offers the ability to measure glutamate neurotransmission in the human brain with the high sensitivity and spatial resolution of ¹H MRS using standard commercial equipment.  

Yibo Zhao^1,2, T. Kevin Hitchens^3,4, Michele Herneisey⁵, Jelena M. Janjic⁵, Rong Guo^1,2, Yudu Li^1,2, and Zhi-Pei Liang^1,2
1Department of Electrical and Computer Engineering, University of Illinois, Urbana-Champaign, Urbana, IL, United States, ²Beckman Institute for Advanced Science and Technology, University of Illinois, Urbana-Champaign, Urbana, IL, United States, ³Animal Imaging Center, University of Pittsburgh, Pittsburgh, PA, United States, ⁴Department of Neurobiology, University of Pittsburgh, Pittsburgh, PA, United States, ⁵Graduate School of Pharmaceutical Sciences, Duquesne University, Pittsburgh, PA, United States

¹⁹F-MRSI has the potential to track multiple perfluorocarbon  nanoemulsions simultaneously, but existing ¹⁹F-MRSI schemes have been limited to CSI, which provides a poor tradeoff between resolution and scan time. In this work, a novel method is proposed to enable fast high-resolution ¹⁹F-MRSI. In the proposed method, (k,t)-space is sampled rapidly in EPSI trajectories; data processing is accomplished using a union-of-subspaces model with pre-learned spectral basis. The proposed method has been evaluated using simulation and experimental data, producing encouraging results. The proposed method may open up new opportunities for simultaneous tracking of different labeled cell populations in vivo.

Jessie Mosso^1,2,3, Julien Valette⁴, Katarzyna Pierzchala^1,2, Dunja Simicic^1,2,3, Ileana Ozana Jelescu^1,2, and Cristina Cudalbu^1,2
1CIBM Center for Biomedical Imaging, Lausanne, Switzerland, ²Animal Imaging and Technology, EPFL, Lausanne, Switzerland, ³LIFMET, EPFL, Lausanne, Switzerland, ⁴Commissariat à l'Energie Atomique (CEA), Institut d'Imagerie Biomédicale (I2BM), Molecular Imaging Research Center (MIRCen), Fontenay-aux-Roses, France

Chronic hepatic encephalopathy (cHE) is a severe brain condition arising from chronic liver disease. Microstructural changes occurring due to toxins accumulation in the brain are still unexplored in vivo, especially in cerebellum, and of key interest for disease early detection. Using the STE-LASER sequence, we measured a decreased diffusion coefficient for glutamine and increased for taurine and glutamate in the cerebellum of a rat model of cHE, associated with cell-specific morphological changes measured ex vivo. These preliminary results need to be confirmed by increasing the sample size but they shed light on new aspects in the pathophysiology of HE.

Claudius Sebastian Mathy^1,2,3, Monique A. Thomas¹, Graeme F. Mason^1,4,5, Robin A. de Graaf^1,5, and Henk M. De Feyter^1
1Department of Radiology and Biomedical Imaging, Magnetic Resonance Research Center, Yale University, New Haven, CT, United States, ²Institute of Physical and Theoretical Chemistry, University of Bonn, Bonn, Germany, ³Department of Diagnostic and Interventional Radiology, RWTH Aachen, Aachen, Germany, ⁴Department of Psychiatry, Yale University, New Haven, CT, United States, ⁵Department of Biomedical Engineering, Yale University, New Haven, CT, United States

Deuterium metabolic imaging (DMI) is a novel metabolic imaging technique where ²H MRSI is combined with administration of ²H-labeled substrates. DMI data acquired at metabolic steady-state reveal the relative activities of metabolic pathways, whereas dynamically acquired DMI also provides the metabolic pathway activity rates. The analysis of dynamic DMI data is complicated by the presence of deuterium label loss between deuterated products and water. Here we validated metabolic rates obtained with dynamic DMI with those established using more traditional, ¹³C-based MR methods.

Abigail T.J. Cember¹, Laurie J. Rich¹, Puneet Bagga¹, Neil E. Wilson², Ravi Prakash Reddy Nanga¹, Deepa Thakuri¹, Mark Elliott¹, Mitchell D. Schnall³, John A. Detre⁴, and Ravinder Reddy^1
1Center for Magnetic Resonance and Optical Imaging, Department of Radiology, University of Pennsylvania, Philadelphia, PA, United States, ²Siemens Medical Solutions, USA, Malvern, PA, United States, ³Department of Radiology, University of Pennsylvania, Philadelphia, PA, United States, ⁴Department of Neurology, University of Pennsylvania, Philadelphia, PA, United States

Here we present spectroscopic and chemical shift imaging data from the brains of healthy human subjects acquired using a novel method termed qMRS, which enables tracking of metabolic turnover with the inherent sensitivity of ¹H MRS and widespread applicability using standard ¹H-based clinical MRI scanners. We demonstrate the feasibility of using qMRS and its corollary chemical shift imaging technique (qCSI) to monitor the temporal and spatial dynamics of metabolite labelling in the human brain following oral consumption of deuterium-labeled glucose. Unlike the related technique of deuterium metabolic imaging (DMI), qMRS does not require implementation of multinuclear MR spectroscopy. 

Steve C.N. Hui^1,2, Tao Gong³, Helge J. Zöllner^1,2, Yulu Song³, Yufan Chen³, Muhammad G. Saleh⁴, Mark Mikkelsen^1,2, Georg Oeltzschner^1,2, Sofie Tapper^1,2, Weibo Chen⁵, Richard A.E. Edden^1,2, and Guangbin Wang^3
1Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, United States, ²F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States, ³Department of Imaging and Nuclear Medicine, Shandong Medical Imaging Research Institute, Cheeloo College of Medicine, Shandong University, Jinan, China, ⁴Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, MD, United States, ⁵Philips Healthcare, Shanghai, China

The aim of this project was to investigate the time course of macromolecular (MM) background spectrum during healthy aging. Recruiting a structured, cross-sectional cohort of 100 participants (10 male and 10 female subject per decade: 20s; 30s; 40s; 50s; and 60s), we acquired metabolite-nulled short-TE PRESS data and modeled the MM spectrum as a series of Gaussian signals at literature-defined chemical shifts. Linear regression of water-scaled MM signal areas revealed no significant relationship between age and MM signal areas, suggesting the MM spectrum may be more stable than has been suggested in the literature.

Yan Li¹, Huawei Liu¹, Angela Jakary¹, Sivakami Avadiappan¹, Melanie Morrison¹, Ralph Noeske², Peder E.Z. Larson¹, Alexandra Nelson³, Katherine Possin³, Michael Geschwind³, Christopher Hess¹, and Janine M Lupo^1
1Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, United States, ²GE Healthcare, Munich, Germany, ³Department of Neurology, University of California San Francisco, San Francisco, CA, United States

In this study of Huntington's Disease (HD), we evaluated brain metabolites from pre-manifest HD (PM) and early-manifest HD (EM), as well as their relationship to disease burden and motor disturbances. We used multi-voxel MRS at ultra-high field strength (7T), in order to improve the reliability and sensitivity of detecting focal metabolic changes that are related to HD. We found metabolic alterations in the thalamus and insula and changes in choline, mI, glutathione and glutamate that were correlated with clinical measures of disease severity.