A constrained least-squares approach to the automated quantitation of in-vivo H MRS data

TARQUIN, a new method for the fully automatic analysis of short echotime in-vivo 1H MRS 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 employed to improve fitting stability. Initial point truncation and HSVD water removal are used to reduce baseline interference. Three methods were used to test performance. Firstly, metabolite concentrations from six healthy volunteers at 3T were compared with LCModelTM. Secondly, a Monte-Carlo simulation was performed and results were compared with LCModelTM to test the accuracy of the new method. Finally, the new algorithm was applied to 1956 spectra, acquired clinically at 1.5T, to test robustness to noisy, abnormal, artefactual and poorly shimmed spectra. Discrepancies of less than approximately 20% were found between the main metabolite concentrations determined by TARQUIN and LCModelTM from healthy volunteer data. The Monte-Carlo simulation revealed that errors in metabolite concentration estimates were comparable to LCModelTM. 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 MRS data making it suitable for use in a clinical setting.