Comparison between Short and Long Echo Time Magnetic Resonance Spectroscopic Imaging at 3T and 7T for Evaluating Brain Metabolites in Patients with Glioma.

Three-dimensional proton magnetic resonance spectroscopic imaging (MRSI) is a powerful non-invasive tool for characterizing spatial variations in metabolic profiles for patients with glioma. Metabolic parameters obtained using this technique have been shown to predict treatment response, disease progression, and transformation to a more malignant phenotype. The availability of ultra-high-field MR systems has the potential to improve the characterization of metabolites. The purpose of this study was to compare the metabolite profiles acquired with conventional long echo time (TE) MRSI at 3T with those obtained with short TE MRSI at 3T and 7T in patients with glioma. The data acquisition parameters were optimized separately for each echo time and field strength to obtain volumetric coverage within clinically feasible data acquisition times of 5-10 min. While a higher field strength did provide better detection of metabolites with overlapping peaks, spatial coverage was reduced and the use of inversion recovery to reduce lipid precluded the detection of lipid in regions of necrosis. For serial evaluation of large, heterogeneous lesions, the use of 3T short TE MRSI may thus be preferred. Despite the limited number of metabolites that it is able to detect, the use of 3T long TE MRSI gives the best contrast in choline/N-acetyl aspartate between normal appearing brain and tumor and also allows the separate detection of lactate and lipid. It may therefore be preferred for serial evaluation of patients with high-grade glioma and for detection of malignant transformation in patients with low-grade glioma.

[1]  Peter Jezzard,et al.  Noninvasive Quantification of 2-Hydroxyglutarate in Human Gliomas with IDH1 and IDH2 Mutations. , 2016, Cancer research.

[2]  R. Mirimanoff,et al.  Radiotherapy plus concomitant and adjuvant temozolomide for glioblastoma. , 2005, The New England journal of medicine.

[3]  Susan M. Chang,et al.  Volume MRI and MRSI techniques for the quantitation of treatment response in brain tumors: Presentation of a detailed case study , 1997, Journal of magnetic resonance imaging : JMRI.

[4]  Yan Li,et al.  Fully automated atlas‐based method for prescribing 3D PRESS MR spectroscopic imaging: Toward robust and reproducible metabolite measurements in human brain , 2018, Magnetic resonance in medicine.

[5]  J. Barnholtz-Sloan,et al.  CBTRUS statistical report: Primary brain and central nervous system tumors diagnosed in the United States in 2006-2010. , 2013, Neuro-oncology.

[6]  Jill S. Barnholtz-Sloan,et al.  CBTRUS Statistical Report: Primary Brain and Central Nervous System Tumors Diagnosed in the United States in 2008-2012 , 2015, Neuro-oncology.

[7]  Hoby P Hetherington,et al.  Role of very high order and degree B0 shimming for spectroscopic imaging of the human brain at 7 tesla , 2012, Magnetic resonance in medicine.

[8]  Rolf Gruetter,et al.  MR spectroscopy of the human brain with enhanced signal intensity at ultrashort echo times on a clinical platform at 3T and 7T , 2009, Magnetic resonance in medicine.

[9]  S. Nelson Analysis of volume MRI and MR spectroscopic imaging data for the evaluation of patients with brain tumors , 2001, Magnetic resonance in medicine.

[10]  Jason C. Crane,et al.  Association of early changes in 1H MRSI parameters with survival for patients with newly diagnosed glioblastoma receiving a multimodality treatment regimen , 2016, Neuro-oncology.

[11]  F. Ducray,et al.  IDH1 and IDH2 mutations in gliomas. , 2009, The New England journal of medicine.

[12]  Ilwoo Park,et al.  Patterns of recurrence analysis in newly diagnosed glioblastoma multiforme after three-dimensional conformal radiation therapy with respect to pre-radiation therapy magnetic resonance spectroscopic findings. , 2007, International journal of radiation oncology, biology, physics.

[13]  Susan M. Chang,et al.  Survival analysis in patients with newly diagnosed glioblastoma using pre- and postradiotherapy MR spectroscopic imaging. , 2013, Neuro-oncology.

[14]  V. Govindaraju,et al.  Proton NMR chemical shifts and coupling constants for brain metabolites , 2000, NMR in biomedicine.

[15]  D. Rothman,et al.  Improvements on an in Vivo automatic shimming method (FASTERMAP) , 1997, Magnetic resonance in medicine.

[16]  N. Voets,et al.  Improved Localization for 2-Hydroxyglutarate Detection at 3 T Using Long-TE Semi-LASER , 2016, Tomography.

[17]  Priti Balchandani,et al.  Fat suppression for 1H MRSI at 7T using spectrally selective adiabatic inversion recovery , 2008, Magnetic resonance in medicine.

[18]  D. Busam,et al.  An Integrated Genomic Analysis of Human Glioblastoma Multiforme , 2008, Science.

[19]  Albert P. Chen,et al.  Implementation of 3 T Lactate-Edited 3D 1H MR Spectroscopic Imaging with Flyback Echo-Planar Readout for Gliomas Patients , 2010, Annals of Biomedical Engineering.

[20]  Susan M. Chang,et al.  Ex vivo MR spectroscopic measure differentiates tumor from treatment effects in GBM. , 2010, Neuro-oncology.

[21]  Annette M Molinaro,et al.  Characterization of metabolites in infiltrating gliomas using ex vivo 1H high-resolution magic angle spinning spectroscopy , 2014, NMR in biomedicine.

[22]  B. Mueller,et al.  Signal‐to‐noise ratio and spectral linewidth improvements between 1.5 and 7 Tesla in proton echo‐planar spectroscopic imaging , 2006, Magnetic resonance in medicine.

[23]  Susan M. Chang,et al.  Updated response assessment criteria for high-grade gliomas: response assessment in neuro-oncology working group. , 2010, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[24]  R. McLendon,et al.  IDH1 and IDH2 mutations in gliomas. , 2009, The New England journal of medicine.

[25]  D. Arnold,et al.  Using pattern analysis of in vivo proton MRSI data to improve the diagnosis and surgical management of patients with brain tumors , 1998, NMR in biomedicine.

[26]  Yan Li,et al.  T1 and T2 Metabolite Relaxation Times in Normal Brain at 3T and 7T , 2013 .

[27]  Eugene Ozhinsky,et al.  Short‐echo three‐dimensional H‐1 MR spectroscopic imaging of patients with glioma at 7 tesla for characterization of differences in metabolite levels , 2015, Journal of magnetic resonance imaging : JMRI.

[28]  John M Pauly,et al.  Design of flyback echo‐planar readout gradients for magnetic resonance spectroscopic imaging , 2005, Magnetic resonance in medicine.

[29]  L Junck,et al.  Response assessment in neuro-oncology (a report of the RANO group): assessment of outcome in trials of diffuse low-grade gliomas. , 2011, The Lancet. Oncology.

[30]  J. Zhang,et al.  The Effect of Age and Cerebral Ischemia on Diffusion-Weighted Proton MR Spectroscopy of the Human Brain , 2012, American Journal of Neuroradiology.

[31]  Eugene Ozhinsky,et al.  Automated prescription of oblique brain 3D magnetic resonance spectroscopic imaging , 2013, Magnetic resonance in medicine.

[32]  N. Voets,et al.  Non-invasive quantification of 2-hydroxyglutarate in human gliomas with IDH 1 and IDH 2 mutations , 2017 .

[33]  Lynn E Eberly,et al.  Test‐retest reproducibility of neurochemical profiles with short‐echo, single‐voxel MR spectroscopy at 3T and 7T , 2016, Magnetic resonance in medicine.

[34]  Stephen M. Smith,et al.  Segmentation of brain MR images through a hidden Markov random field model and the expectation-maximization algorithm , 2001, IEEE Transactions on Medical Imaging.

[35]  Ying Lu,et al.  Comparison of T1 and T2 metabolite relaxation times in glioma and normal brain at 3T , 2008, Journal of magnetic resonance imaging : JMRI.

[36]  L. Liau,et al.  Cancer-associated IDH1 mutations produce 2-hydroxyglutarate , 2009, Nature.

[37]  Yan Li,et al.  Serial analysis of 3D H-1 MRSI for patients with newly diagnosed GBM treated with combination therapy that includes bevacizumab , 2016, Journal of Neuro-Oncology.

[38]  Esin Ozturk-Isik,et al.  Considerations in applying 3D PRESS H-1 brain MRSI with an eight-channel phased-array coil at 3 T. , 2006, Magnetic resonance imaging.

[39]  Eugene Ozhinsky,et al.  Improved spatial coverage for brain 3D PRESS MRSI by automatic placement of outer‐volume suppression saturation bands , 2011, Journal of magnetic resonance imaging : JMRI.

[40]  J A Frank,et al.  Mapping of brain tumor metabolites with proton MR spectroscopic imaging: clinical relevance. , 1992, Radiology.

[41]  J. Kurhanewicz,et al.  Very selective suppression pulses for clinical MRSI studies of brain and prostate cancer , 2000, Magnetic resonance in medicine.

[42]  Susan M. Chang,et al.  Metabolic Profiling of IDH Mutation and Malignant Progression in Infiltrating Glioma , 2017, Scientific Reports.

[43]  S. Provencher Estimation of metabolite concentrations from localized in vivo proton NMR spectra , 1993, Magnetic resonance in medicine.

[44]  P. Wen,et al.  Response Assessment in Neuro-Oncology , 2011, Current oncology reports.

[45]  B. Rosen,et al.  Detection of oncogenic IDH1 mutations using magnetic resonance spectroscopy of 2-hydroxyglutarate. , 2013, The Journal of clinical investigation.