A constrained least-squares approach to the automated quantitation of in vivo 1H magnetic resonance spectroscopy data
Corresponding Author
Martin Wilson
Cancer Sciences, University of Birmingham, Birmingham, United Kingdom
Academic Department of Paediatrics and Child Health, Birmingham Children's Hospital NHS Foundation Trust, Birmingham, United Kingdom
Academic Department of Paediatrics and Child Health, Birmingham Children's Hospital, Steelhouse Lane, Birmingham, West Midlands B4 6NH, United Kingdom===Search for more papers by this authorGreg Reynolds
Pattern Analytics Ltd., Birmingham, United Kingdom
Search for more papers by this authorRisto A. Kauppinen
Department of Radiology, Dartmouth College, Hanover, New Hampshire, USA
Search for more papers by this authorTheodoros N. Arvanitis
Academic Department of Paediatrics and Child Health, Birmingham Children's Hospital NHS Foundation Trust, Birmingham, United Kingdom
School of Electronic, Electrical and Computer Engineering, University of Birmingham, Birmingham, United Kingdom
Search for more papers by this authorAndrew C. Peet
Cancer Sciences, University of Birmingham, Birmingham, United Kingdom
Academic Department of Paediatrics and Child Health, Birmingham Children's Hospital NHS Foundation Trust, Birmingham, United Kingdom
Search for more papers by this authorCorresponding Author
Martin Wilson
Cancer Sciences, University of Birmingham, Birmingham, United Kingdom
Academic Department of Paediatrics and Child Health, Birmingham Children's Hospital NHS Foundation Trust, Birmingham, United Kingdom
Academic Department of Paediatrics and Child Health, Birmingham Children's Hospital, Steelhouse Lane, Birmingham, West Midlands B4 6NH, United Kingdom===Search for more papers by this authorGreg Reynolds
Pattern Analytics Ltd., Birmingham, United Kingdom
Search for more papers by this authorRisto A. Kauppinen
Department of Radiology, Dartmouth College, Hanover, New Hampshire, USA
Search for more papers by this authorTheodoros N. Arvanitis
Academic Department of Paediatrics and Child Health, Birmingham Children's Hospital NHS Foundation Trust, Birmingham, United Kingdom
School of Electronic, Electrical and Computer Engineering, University of Birmingham, Birmingham, United Kingdom
Search for more papers by this authorAndrew C. Peet
Cancer Sciences, University of Birmingham, Birmingham, United Kingdom
Academic Department of Paediatrics and Child Health, Birmingham Children's Hospital NHS Foundation Trust, Birmingham, United Kingdom
Search for more papers by this authorAbstract
Totally Automatic Robust Quantitation in NMR (TARQUIN), a new method for the fully automatic analysis of short echo time in vivo 1H Magnetic resonance spectroscopy is presented. Analysis is performed in the time domain using non-negative least squares, and a new method for applying soft constraints to signal amplitudes is used to improve fitting stability. Initial point truncation and Hankel singular value decomposition water removal are used to reduce baseline interference. Three methods were used to test performance. First, metabolite concentrations from six healthy volunteers at 3 T were compared with LCModel™. Second, a Monte-Carlo simulation was performed and results were compared with LCModel™ to test the accuracy of the new method. Finally, the new algorithm was applied to 1956 spectra, acquired clinically at 1.5 T, to test robustness to noisy, abnormal, artifactual, and poorly shimmed spectra. Discrepancies of less than approximately 20% were found between the main metabolite concentrations determined by TARQUIN and LCModel™ from healthy volunteer data. The Monte-Carlo simulation revealed that errors in metabolite concentration estimates were comparable with LCModel™. TARQUIN analyses were also found to be robust to clinical data of variable quality. In conclusion, TARQUIN has been shown to be an accurate and robust algorithm for the analysis of magnetic resonance spectroscopy data making it suitable for use in a clinical setting. Magn Reson Med, 2010. © 2010 Wiley-Liss, Inc.
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