Role of TR (Repetition Time) and TE (ECHO Time) in Optimization of Magnetic Resonance Spectroscopy in the Brain Protocol

Sumit Tyagi; Ashok Sharma; Subhash Chand Sylonia; Lalit Gupta

doi:10.55489/njmr.150220251050

Authors

Sumit Tyagi Radiology and imaging technology, Santosh deemed to be University, Gaziabad, India
Ashok Sharma Radio diagnosis, Santosh deemed to be University, Gaziabad, India
Subhash Chand Sylonia Radio diagnosis, Saraswati institute of Medical sciences Anwarpur Hapur, Hapur, India
Lalit Gupta Radiology and imaging technology, Santosh deemed to be University, Gaziabad, India

DOI:

https://doi.org/10.55489/njmr.150220251050

Keywords:

Magnetic Resonance Spectroscopy, Repetition Time, Echo Time, Metabolite Detection, Neurological Disorders, Signal-to-Noise Ratio

Abstract

Introduction: Magnetic Resonance Spectroscopy (MRS) is a non-invasive imaging modality used to quantify brain metabolites, aiding in the diagnosis of neurological disorders. Optimization of acquisition parameters, especially Repetition Time (TR) and Echo Time (TE), is critical for enhancing signal-to-noise ratio (SNR) and metabolite detection.

Method: This six-month study involved 100 participants undergoing brain MRS at two tertiary care centers. MRS examinations were performed using a 1.5 Tesla scanner with single-voxel PRESS sequences. TR values (1500–2000 ms) and TE values (30 ms, 144 ms) were varied systematically to assess their impact on SNR, spectral resolution (FWHM), and metabolite detection. Statistical analysis included ANOVA and correlation studies.

Results: Longer TR values significantly improved SNR (12.3 ± 1.8 at TR = 1500 ms vs. 14.7 ± 2.1 at TR = 2000 ms; p <0.001). Higher TE values enhanced spectral resolution (FWHM: 0.050 ± 0.005 ppm at TE = 30 ms vs. 0.045 ± 0.004 ppm at TE = 144 ms; p <0.01). Diagnostic accuracy was highest for brain tumors (90%). TR and SNR showed a strong positive correlation (r = 0.851; p <0.001).

Conclusion: Optimized TR and TE values significantly enhance metabolite quantification and diagnostic accuracy in MRS, particularly for brain tumors and neurodegenerative diseases.

References

Gujar SK, Maheshwari S, Björkman-Burtscher I, Sundgren PC. Magnetic resonance spectroscopy. J Neuroophthalmol 2005;25:217-26. DOI: https://doi.org/10.1097/01.wno.0000177307.21081.81 PMid:16148633 DOI: https://doi.org/10.1097/01.wno.0000177307.21081.81

Lally N, An L, Banerjee D, Niciu MJ, Luckenbaugh DA, Richards EM, et al. Reliability of 7T 1H-MRS measured human prefrontal cortex glutamate, glutamine, and glutathione signals using an adapted echo time optimized PRESS sequence: A between- and within-sessions investigation. Journal of Magnetic Resonance Imaging 2016;43:88-98. DOI: https://doi.org/10.1002/jmri.24970 PMid:26059603 PMCid:PMC4671833 DOI: https://doi.org/10.1002/jmri.24970

Wilson M, Andronesi O, Barker PB, Bartha R, Bizzi A, Bolan PJ, et al. A Methodological Consensus on Clinical Proton MR Spectroscopy of the Brain: Review and Recommendations. MagnReson Med 2019;82:527. DOI: https://doi.org/10.1002/mrm.27742 PMid:30919510 PMCid:PMC7179569 DOI: https://doi.org/10.1002/mrm.27742

Kellman P, Derbyshire JA, Agyeman KO, McVeigh ER, Arai AE. Extended coverage first-pass perfusion imaging using slice-interleaved TSENSE. MagnReson Med 2004;51:200-4. DOI: https://doi.org/10.1002/mrm.10663 PMid:14705062 PMCid:PMC1939887 DOI: https://doi.org/10.1002/mrm.10663

Ebel A, Maudsley AA. Improved spectral quality for 3D MR spectroscopic imaging using a high spatial resolution acquisition strategy. MagnReson Imaging 2003;21:113-20. DOI: https://doi.org/10.1016/S0730-725X(02)00645-8 PMid:12670597 DOI: https://doi.org/10.1016/S0730-725X(02)00645-8

Jahanian H, Holdsworth S, Christen T, Wu H, Zhu K, Kerr AB, et al. Advantages of short repetition time resting-state functional MRI enabled by simultaneous multi-slice imaging. J Neurosci Methods 2019;311:122-32. DOI: https://doi.org/10.1016/j.jneumeth.2018.09.033 PMid:30300699 DOI: https://doi.org/10.1016/j.jneumeth.2018.09.033

Serdyuchenko A, Gorshelev V, Weber M, Chehade W, Burrows JP. High spectral resolution ozone absorption cross-sections – Part 2: Temperature dependence. Atmos Meas Tech 2014;7:625-36. DOI: https://doi.org/10.5194/amt-7-625-2014 DOI: https://doi.org/10.5194/amt-7-625-2014

Xu Z, Zhang L, Cheng Y, Morita S, Li L, Zhang W, et al. An extreme ultraviolet spectrometer working at 10-130 Å for tungsten spectra observation with high spectral resolution and fast-time response in Experimental Advanced Superconducting Tokamak. NuclInstrum Methods Phys Res A 2021;1010:165545. DOI: https://doi.org/10.1016/j.nima.2021.165545 DOI: https://doi.org/10.1016/j.nima.2021.165545

Jing B, Lindsey BD. Phase Modulation Beamforming for Ultrafast Plane-Wave Imaging. IEEE Trans UltrasonFerroelectr Freq Control 2020;67:2003-11. DOI: https://doi.org/10.1109/TUFFC.2020.2993763 PMid:32396082 PMCid:PMC7539262 DOI: https://doi.org/10.1109/TUFFC.2020.2993763

Schirmer T, Auer DP. On the reliability of quantitative clinical magnetic resonance spectroscopy of the human brain. NMR Biomed 2000;13:28-36. DOI: https://doi.org/10.1002/(SICI)1099-1492(200002)13:1<28::AID-NBM606>3.0.CO;2-L DOI: https://doi.org/10.1002/(SICI)1099-1492(200002)13:1<28::AID-NBM606>3.0.CO;2-L

Chiu PW, Mak HKF, Yau KKW, Chan Q, Chang RCC, Chu LW. Metabolic changes in the anterior and posterior cingulate cortices of the normal aging brain: proton magnetic resonance spectroscopy study at 3 T. Age (Dordr) 2014;36:251-64. DOI: https://doi.org/10.1007/s11357-013-9545-8 PMid:23709317 PMCid:PMC3889884 DOI: https://doi.org/10.1007/s11357-013-9545-8

Wiedermann D, Schuff N, Matson GB, Soher BJ, Du AT, Maudsley AA, et al. Short echo time multislice proton magnetic resonance spectroscopic imaging in human brain: Metabolite distributions and reliability. MagnReson Imaging 2001;19:1073-80. DOI: https://doi.org/10.1016/S0730-725X(01)00441-6 PMid:11711231 DOI: https://doi.org/10.1016/S0730-725X(01)00441-6

Duijn JH, Matson GB, Maudsley AA, Hugg JW, Weiner MW. Human brain infarction: proton MR spectroscopy. Radiology 1992;183:711-8. DOI: https://doi.org/10.1148/radiology.183.3.1584925 PMid:1584925 DOI: https://doi.org/10.1148/radiology.183.3.1584925

Sutton LN, Wang Z, Gusnard D, Lange B, Perilongo G, Bogdan AR, et al. Proton magnetic resonance spectroscopy of pediatric brain tumors. Neurosurgery 1992;31:195-202. DOI: https://doi.org/10.1227/00006123-199208000-00004 PMid:1513425 DOI: https://doi.org/10.1097/00006123-199208000-00004

Alkan A, Kutlu R, Hallac T, Sigirci A, Emul M, Pala N, et al. Occupational prolonged organic solvent exposure in shoemakers: brain MR spectroscopy findings. MagnReson Imaging 2004;22:707-13. DOI: https://doi.org/10.1016/j.mri.2004.01.070 PMid:15172065 DOI: https://doi.org/10.1016/j.mri.2004.01.070

Harris LM, Davies N, MacPherson L, Foster K, Lateef S, Natarajan K, et al. The use of short-echo-time 1H MRS for childhood cerebellar tumours prior to histopathological diagnosis. PediatrRadiol 2007;37:1101-9. DOI: https://doi.org/10.1007/s00247-007-0571-5 PMid:17823793 DOI: https://doi.org/10.1007/s00247-007-0571-5

Schott JM, Frost C, MacManus DG, Ibrahim F, Waldman AD, Fox NC. Short echo time proton magnetic resonance spectroscopy in Alzheimer's disease: a longitudinal multiple time point study. Brain 2010;133:3315-22. DOI: https://doi.org/10.1093/brain/awq208 PMid:20739347 PMCid:PMC2965422 DOI: https://doi.org/10.1093/brain/awq208

Julià-Sapé M, Acosta D, Majós C, Moreno-Torres À, Wesseling P, Acebes JJ, et al. Comparison between neuroimaging classifications and histopathological diagnoses using an international multicenter brain tumor magnetic resonance imaging database. J Neurosurg 2006;105:6-14. DOI: https://doi.org/10.3171/jns.2006.105.1.6 PMid:16874886 DOI: https://doi.org/10.3171/jns.2006.105.1.6

Guzmán-De-Villoria JA, Mateos-Pérez JM, Fernández-García P, Castro E, Desco M. Added value of advanced over conventional magnetic resonance imaging in grading gliomas and other primary brain tumors. Cancer Imaging 2014;14. DOI: https://doi.org/10.1186/s40644-014-0035-8 PMid:25608821 PMCid:PMC4300038 DOI: https://doi.org/10.1186/s40644-014-0035-8

Allen BC, Kapoor S, Anzalone A, Mayer KP, Wolfe SQ, Duncan P, et al. Transcranial ultrasonography to detect intracranial pathology: A systematic review and meta-analysis. J Neuroimaging 2023;33:333-58. DOI: https://doi.org/10.1111/jon.13087 PMid:36710079 DOI: https://doi.org/10.1111/jon.13087

Perani D, Della Rosa PA, Cerami C, Gallivanone F, Fallanca F, Vanoli EG, et al. Validation of an optimized SPM procedure for FDG-PET in dementia diagnosis in a clinical setting. Neuroimage Clin 2014;6:445-54. DOI: https://doi.org/10.1016/j.nicl.2014.10.009 PMid:25389519 PMCid:PMC4225527 DOI: https://doi.org/10.1016/j.nicl.2014.10.009

Tomasi D, Shokri-Kojori E, Volkow ND. High-Resolution Functional Connectivity Density: Hub Locations, Sensitivity, Specificity, Reproducibility, and Reliability. Cerebral Cortex 2016;26:3249-59. DOI: https://doi.org/10.1093/cercor/bhv171 PMid:26223259 PMCid:PMC4898675 DOI: https://doi.org/10.1093/cercor/bhv171

Rizzo R, Kreis R. Multi-echo single-shot spectroscopy combined with simultaneous 2D model fitting for fast and accurate measurement of metabolite-specific concentrations and T2 relaxation times. NMR Biomed 2023;36:e5016. DOI: https://doi.org/10.1002/nbm.5016 PMid:37587062 DOI: https://doi.org/10.1002/nbm.5016

Bartha R. Effect of signal-to-noise ratio and spectral linewidth on metabolite quantification at 4 T. NMR Biomed 2007;20:512-21. DOI: https://doi.org/10.1002/nbm.1122 PMid:17205487 DOI: https://doi.org/10.1002/nbm.1122

Nassirpour S, Chang P, Henning A. High and ultra-high resolution metabolite mapping of the human brain using 1H FID MRSI at 9.4T. Neuroimage 2018;168:211-21. DOI: https://doi.org/10.1016/j.neuroimage.2016.12.065 PMid:28025130 DOI: https://doi.org/10.1016/j.neuroimage.2016.12.065

Tsai SY, Posse S, Lin YR, Ko CW, Otazo R, Chung HW, et al. Fast mapping of the T2 relaxation time of cerebral metabolites using proton echo-planar spectroscopic imaging (PEPSI). MagnReson Med 2007;57:859-65. DOI: https://doi.org/10.1002/mrm.21225 PMid:17457864 DOI: https://doi.org/10.1002/mrm.21225