ISMRM 24th Annual Meeting & Exhibition • 07-13 May 2016 • Singapore

Scientific Session: MRS Methods: What's New?

Monday, May 9, 2016
Room 300-302
10:45 - 12:45
Moderators: Graham Galloway, Naranamangalam Jagannathan

Characterization of the macromolecular baseline with a metabolite-cycled double-inversion recovery sequence in the human brain at 9.4T
Ioannis Angelos Giapitzakis1,2, Roland Kreis 3, and Anke Henning 1,4
1Max Planck Institute for Biological Cybernetics, Tübingen, Germany, 2IMPRS for Cognitive and Systems Neuroscience, University of Tuebingen, Tuebingen, Germany, 3Depts. Radiology and Clinical Research, University of Bern, Bern, Switzerland, 4Institute of Biomedical Engineering, University and ETH, Zürich, Switzerland
Macromolecular resonances (MM) overlap with metabolites resulting in inaccurate quantification of the metabolites due to baseline distortion. This effect becomes even more severe in case of short echo times (TE). The purpose of this study was the development of an adiabatic pulse for double inversion recovery and investigation of impact to include MM into quantification of 9.4T MRS data of human brain. This is the first study where MC-STEAM is combined with a double inversion technique. The results showed the advantages of UHF and MC as well as the necessity of the inclusion of MM baseline in the basis set.

Evidence for regional and spectral differences of macromolecule signals in human brain using a crusher coil at 7 Tesla
Nicolas Geades1, Carrie Wismans2, Mariska Damen2, Penny Gowland1, Hans Hoogduin2, Vincent Boer2, Dennis Klomp2, and Jannie Wijnen2
1Sir Peter Mansfield Imaging Centre, University of Nottingham, Nottingham, United Kingdom, 2Department of Radiology, University Medical Centre Utrecht, Utrecht, Netherlands
The regional, spectral and relaxation differences of macromolecules (MM) in the human brain were investigated using T1 mapping, metabolite nulling and high resolution MRSI with a crusher coil at 7T. Differences between macromolecular signal of GM and WM were observed by all three methods. The T1 mapping showed different T1 relaxation time of MM in GM and WM. Metabolic maps created by fitting an averaged WM spectrum showed differences in M1 and M2. The macromolecules in the metabolite nulled data showed a different M4 in GM and WM. Some of these differences can be explained by differences in T1 relaxation.

Improvement of 2-hydroxyglutarate detectability using optimized triple-refocusing difference editing at 7T in vivo
Sandeep K Ganji1, Zhongxu An1, Vivek Tiwari1, Marco Pinho2, Edward Pan3, Bruce Mickey4, Elizabeth Maher5, and Changho Choi1
1Advanced Imaging Research Center, UT Southwestern Medical Center, Dallas, TX, United States, 2Radiology, UT Southwestern Medical Center, Dallas, TX, United States, 3Neurology and Neurotherapeutic, UT Southwestern Medical Center, Dallas, TX, United States, 4Neurological Surgery, UT Southwestern Medical Center, Dallas, TX, United States, 5Internal Medicine, UT Southwestern Medical Center, Dallas, TX, United States
2-hydroxyglutarate (2HG) has become an important biomarker in the diagnosis and management of glioma patients as well as in the workup of an undiagnosed mass. The 1H MRS signals of 2HG are extensively overlapped with other metabolite signals. Specifically, uncertainty in 2HG evaluation arising from the spectral overlap of the 2HG 2.25-ppm signal with the GABA 2.29-ppm resonance may be a major obstacle when the 2HG level is relatively low. Here we report a novel triple-refocusing difference editing that provides complete differentiation between 2HG and GABA signals at 7T. 

Indirectly-Detected and Spin-Amplified Heteronuclear MRS and MRI - Permission Withheld
Chencai Wang1, Chaohsiung Hsu1, Stephanie Wolohan1, and Yung-Ya Lin1
1Department of Chemistry and Biochemistry, UCLA, Los Angeles, CA, United States
A general indirect-detection and spin-amplification scheme has been developed to enhance the sensitivity of heteronuclear MRS and MRI based on dynamic instability of the solvent proton magnetization under collective feedback fields of radiation damping and the distant dipolar field. The heteronuclear solute spins are first detected by the solvent proton spins through various magnetization transfer mechanisms and serve as small “input” signals to perturb the solvent proton magnetization, which is prepared in an unstable state. The weakly detected signal is then amplified through subsequent nonlinear evolution of the solvent proton magnetization to achieve 10x SNR improvement for 13C MRS and MRI.

Remodeling of energy metabolism revealed by 31P magnetization transfer in a transgenic rat model of Huntington’s disease
Brice Tiret1,2, Maria-Angeles Carrillo-de Sauvage1,2, Huu Phuc Nguyen3,4, Nicole El Massioui5,6, Valérie Doyère5,6, Vincent Lebon1,2, Emmanuel Brouillet1,2, and Julien Valette1,2
1CEA/DSV/I2BM/MIRCen, Fontenay-aux-Roses, France, 2CNRS Université Paris-Saclay UMR 9199, Fontenay-aux-Roses, France, 3Institute of Medical Genetics and Applied Genomics, University of Tuebingen, Tuebingen, Germany, 4Centre for Rare Diseases, University of Tuebingen, Tuebingen, Germany, 5Paris-Saclay Institute of Neuroscience, Université Paris-Sud, UMR 9197, Orsay, France, 6Centre National de la Recherche Scientifique, Orsay, France
Localized 31P MRS with progressive magnetization transfer (MT) is performed in the BACHD transgenic rat model of Huntington’s disease to assess energy metabolism. Localized measurements of the ATP formation rate through creatine kinase and oxidative phosphorylation (ATPsynthase) are performed in the rat brain for the first time. Results show that ATPsynthase rate is reduced by a factor 2, which is partly compensated by higher cerebral concentrations of phosphocreatine to generate ATP via creatine kinase.

Investigating machine learning approaches for quality control of brain tumor spectra
Sreenath P Kyathanahally1, Victor Mocioiu2, Nuno Miguel Pedrosa de Barros3, Johannes Slotboom3, Alan J Wright4, Margarida Julià-Sapé 2, Carles Arús2, and Roland Kreis1
1Depts. Radiology and Clinical Research, University of Bern, Bern, Switzerland, 2Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Universitat Autònoma de Barcelona, Barcelona, Spain, 3DRNN, Institute of Diagnostic and Interventional Neuroradiology/SCAN, University Hospital Bern, Bern, Switzerland, 4CRUK Cambridge Institute, University of Cambridge, Cambridge, United Kingdom
Despite many potential applications of MR spectroscopy in the clinic, its usage is limited – and the need for human experts to identify bad quality spectra may contribute to this. Previous studies have shown that machine learning methods can be developed to accept or reject a spectrum automatically. In this study, we extend this to different machine learning methods on 1916 spectra from the eTUMOUR and INTERPRET databases. The RUSBoost classifier, which handles unbalanced data, improved specificity and accuracy compared to other classifiers, in particular in combination with an extended feature set and multi-class labels.

Automatic quality assessment of short and long-TE brain tumour MRSI data using novel Spectral Features
Nuno Miguel Pedrosa de Barros1,2, Urspeter Knecht1, Richard McKinley1, Jonathan Giezendanner1, Roland Wiest1, and Johannes Slotboom1
1Institute for Diagnostic and Interventional Neuroradiology, Inselspital, Bern, Switzerland, 2University of Bern, Bern, Switzerland
MRSI-data frequently contains bad-quality spectra which strongly limits its clinical-use. Current clinical practice in our institute is that these bad-quality spectra are filtered out by an MRS-expert, at the expense of long processing times. In this work we present a new method for automatic quality assessment of both long and short-TE MRSI brain tumour data. This method is based upon a novel set of spectral features, and it is as accurate as an expert but considerably faster (3/4 minutes vs 3seconds).

Fast frequency–sweep spectroscopic imaging with an ultra-low flip angle
Junyu Guo1, Zoltan Patay1, and Wilbrun E. Reddick1
1St Jude Children's Research Hospital, Memphis, TN, United States
We present a novel, simple and fast MR spectroscopic imaging technique and show its conceptual validation with simulations and demonstrate proof-of-principle with phantom and human studies. First, compared to the conventional spectroscopic imaging in the time-domain, our method acquires data in the frequency domain, allowing flexible non-uniform sampling to speed up the acquisition. Second, using ultra-small RF pulses offers intrinsic water and fat suppression, greatly simplifying the scanning procedures. Third, this new technique has hundreds of times lower energy deposition than conventional MRI scans. We believe our method could allow spectroscopic imaging to play a larger role in clinical applications.

Parameterization of measured macromolecular background in ultra-short acquisition delay 1H MRSI in the brain at 7T
Michal Považan1,2, Gilbert Hangel1, Bernhard Strasser1, Eva Heckova1, Lukas Hingerl1, Stephan Gruber1, Siegfried Trattnig1,2, and Wolfgang Bogner1
1High Field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University Vienna, Vienna, Austria, 2Christian Doppler Laboratory for Clinical Molecular MR Imaging, Vienna, Austria
Ultra-short echo/acquisition delay MRS spectra have a strong characteristic background consisting of macromolecule (MM) resonances superimposed on the signal of metabolites. Typically a single metabolite-nulled MM spectrum is included into quantification routine to account for this. To detect  more prominent regional and pathologic changes, we replaced this single MM spectrum by individual MM peaks. We found that the MM peaks in a 2.3-0.5 ppm region are higher in gray matter compared to white matter, whereas the MM peaks from 2.9 to 3.2 ppm were significantly higher in white matter of healthy volunteers and one MS patient.

Stochastic excitation scheme for estimating longitudinal relaxation and radiofrequency transmit inhomogeneity in single voxel spectroscopy
Assaf Tal1
1Chemical Physics, Weizmann Institute of Science, Rehovot, Israel
A stochastic excitation and corresponding dictionary matching  scheme is presented for  quantifying metabolite concentrations, longitudinal relaxation times and transmit inhomogeneity in single voxel proton magnetic resonance spectroscopy in the human brain.

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