Jamie Near1, Richard Edden2, C John Evans3, Raphaël Paquin4, Ashley Harris2, Peter Jezzard5. 1. Douglas Mental Health University Institute and Department of Psychiatry, McGill University, Montreal, Canada. 2. Division of Neuroradiology, Russel H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA. 3. Cardiff University Brain Research Imaging Centre, School of Psychology, Cardiff University, Cardiff, UK. 4. Siemens Canada Limited, Healthcare, Montreal, Canada. 5. Centre for Functional Magnetic Resonance Imaging of the Brain, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.
Abstract
PURPOSE: Frequency and phase drifts are a common problem in the acquisition of in vivo magnetic resonance spectroscopy (MRS) data. If not accounted for, frequency and phase drifts will result in artifactual broadening of spectral peaks, distortion of spectral lineshapes, and a reduction in signal-to-noise ratio (SNR). We present herein a new method for estimating and correcting frequency and phase drifts in in vivo MRS data. METHODS: We used a simple method of fitting each spectral average to a reference scan (often the first average in the series) in the time domain through adjustment of frequency and phase terms. Due to the similarity with image registration, this method is referred to as "spectral registration." Using simulated data with known frequency and phase drifts, the performance of spectral registration was compared with two existing methods at various SNR levels. RESULTS: Spectral registration performed well in comparison with the other methods tested in terms of both frequency and phase drift estimation. CONCLUSIONS: Spectral registration provides an effective method for frequency and phase drift correction. It does not involve the collection of navigator echoes, and does not rely on any specific resonances, such as residual water or creatine, making it highly versatile.
PURPOSE: Frequency and phase drifts are a common problem in the acquisition of in vivo magnetic resonance spectroscopy (MRS) data. If not accounted for, frequency and phase drifts will result in artifactual broadening of spectral peaks, distortion of spectral lineshapes, and a reduction in signal-to-noise ratio (SNR). We present herein a new method for estimating and correcting frequency and phase drifts in in vivo MRS data. METHODS: We used a simple method of fitting each spectral average to a reference scan (often the first average in the series) in the time domain through adjustment of frequency and phase terms. Due to the similarity with image registration, this method is referred to as "spectral registration." Using simulated data with known frequency and phase drifts, the performance of spectral registration was compared with two existing methods at various SNR levels. RESULTS: Spectral registration performed well in comparison with the other methods tested in terms of both frequency and phase drift estimation. CONCLUSIONS: Spectral registration provides an effective method for frequency and phase drift correction. It does not involve the collection of navigator echoes, and does not rely on any specific resonances, such as residual water or creatine, making it highly versatile.
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