Rebecca Birch1,2, Andrew C Peet2,3, Theodoros N Arvanitis2,4, Martin Wilson2,3. 1. PSIBS Doctoral Training Centre, University of Birmingham, United Kingdom. 2. Department of Oncology, Birmingham Children's Hospital NHS Foundation Trust, Birmingham, United Kingdom. 3. School of Cancer Sciences, University of Birmingham, United Kingdom. 4. Institute of Digital Healthcare, WMG, University of Warwick, Coventry, United Kingdom.
Abstract
PURPOSE: Accurate and fast (1) H MR spectroscopic imaging (MRSI) water reference scans are important for absolute quantification of metabolites. However, the additional acquisition time required often precludes the water reference quantitation method for MRSI studies. Sensitivity encoding (SENSE) is a successful MR technique developed to reduce scan time. This study quantitatively assesses the accuracy of SENSE for water reference MRSI data acquisition, compared with the more commonly used reduced resolution technique. METHODS: 2D MRSI water reference data were collected from a phantom and three volunteers at 3 Tesla for full acquisition (306 s); 2× reduced resolution (64 s) and SENSE R = 3 (56 s) scans. Water amplitudes were extracted using MRS quantitation software (TARQUIN). Intensity maps and Bland-Altman statistics were generated to assess the accuracy of the fast-MRSI techniques. RESULTS: The average mean and standard deviation of differences from the full acquisition were 2.1 ± 3.2% for SENSE and 10.3 ± 10.7% for the reduced resolution technique, demonstrating that SENSE acquisition is approximately three times more accurate than the reduced resolution technique. CONCLUSION: SENSE was shown to accurately reconstruct water reference data for the purposes of in vivo absolute metabolite quantification, offering significant improvement over the more commonly used reduced resolution technique. 2014 The Authors. Magnetic Resonance in Medicine Published by Wiley Periodicals, Inc. on behalf of International Society of Medicine in Resonance.
PURPOSE: Accurate and fast (1) H MR spectroscopic imaging (MRSI) water reference scans are important for absolute quantification of metabolites. However, the additional acquisition time required often precludes the water reference quantitation method for MRSI studies. Sensitivity encoding (SENSE) is a successful MR technique developed to reduce scan time. This study quantitatively assesses the accuracy of SENSE for water reference MRSI data acquisition, compared with the more commonly used reduced resolution technique. METHODS: 2D MRSI water reference data were collected from a phantom and three volunteers at 3 Tesla for full acquisition (306 s); 2× reduced resolution (64 s) and SENSE R = 3 (56 s) scans. Water amplitudes were extracted using MRS quantitation software (TARQUIN). Intensity maps and Bland-Altman statistics were generated to assess the accuracy of the fast-MRSI techniques. RESULTS: The average mean and standard deviation of differences from the full acquisition were 2.1 ± 3.2% for SENSE and 10.3 ± 10.7% for the reduced resolution technique, demonstrating that SENSE acquisition is approximately three times more accurate than the reduced resolution technique. CONCLUSION: SENSE was shown to accurately reconstruct water reference data for the purposes of in vivo absolute metabolite quantification, offering significant improvement over the more commonly used reduced resolution technique. 2014 The Authors. Magnetic Resonance in Medicine Published by Wiley Periodicals, Inc. on behalf of International Society of Medicine in Resonance.
Authors: Martin Wilson; Ovidiu Andronesi; Peter B Barker; Robert Bartha; Alberto Bizzi; Patrick J Bolan; Kevin M Brindle; In-Young Choi; Cristina Cudalbu; Ulrike Dydak; Uzay E Emir; Ramon G Gonzalez; Stephan Gruber; Rolf Gruetter; Rakesh K Gupta; Arend Heerschap; Anke Henning; Hoby P Hetherington; Petra S Huppi; Ralph E Hurd; Kejal Kantarci; Risto A Kauppinen; Dennis W J Klomp; Roland Kreis; Marijn J Kruiskamp; Martin O Leach; Alexander P Lin; Peter R Luijten; Małgorzata Marjańska; Andrew A Maudsley; Dieter J Meyerhoff; Carolyn E Mountford; Paul G Mullins; James B Murdoch; Sarah J Nelson; Ralph Noeske; Gülin Öz; Julie W Pan; Andrew C Peet; Harish Poptani; Stefan Posse; Eva-Maria Ratai; Nouha Salibi; Tom W J Scheenen; Ian C P Smith; Brian J Soher; Ivan Tkáč; Daniel B Vigneron; Franklyn A Howe Journal: Magn Reson Med Date: 2019-03-28 Impact factor: 4.668