Benjamin Rowland1, Sai K Merugumala1, Huijun Liao1, Mark A Creager2, James Balschi2,3, Alexander P Lin1. 1. Center for Clinical Spectroscopy, Department of Radiology, Brigham and Women's Hospital, Boston, Massachusetts, USA. 2. Cardiovascular Division, Department of Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA. 3. Physiological NMR Core Laboratory, Department of Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA.
Abstract
PURPOSE: MR spectroscopy (MRS) typically requires averaging of multiple acquisitions to achieve adequate signal-to-noise ratio (SNR). In systems undergoing dynamic changes this can compromise the temporal resolution of the measurement. One such example is (31) P MRS of exercising skeletal muscle. Spectral improvement by Fourier thresholding (SIFT) offers a way of suppressing noise without averaging. In this study, we evaluate the performance of SIFT in healthy subjects and clinical cases. METHODS: (31) P MRS of the calf or thigh muscle of subjects (n = 12) was measured continuously before, during, and after exercise. The data were processed conventionally and with the addition of SIFT before quantifying peak amplitudes and frequencies. The postexercise increase in the amplitude of phosphocreatine was also characterized by fitting with an exponential function to obtain the recovery time constant. RESULTS: Substantial reductions in the uncertainty of peak fitting for phosphocreatine (73%) and inorganic phosphate (60%) were observed when using SIFT relative to conventional processing alone. SIFT also reduced the phosphocreatine recovery time constant uncertainty by 38%. CONCLUSION: SIFT considerably improves SNR, which improved quantification and parameter estimation. It is suitable for any type of time varying MRS and is both straightforward and fast to apply. Magn Reson Med 76:978-985, 2016.
PURPOSE: MR spectroscopy (MRS) typically requires averaging of multiple acquisitions to achieve adequate signal-to-noise ratio (SNR). In systems undergoing dynamic changes this can compromise the temporal resolution of the measurement. One such example is (31) P MRS of exercising skeletal muscle. Spectral improvement by Fourier thresholding (SIFT) offers a way of suppressing noise without averaging. In this study, we evaluate the performance of SIFT in healthy subjects and clinical cases. METHODS: (31) P MRS of the calf or thigh muscle of subjects (n = 12) was measured continuously before, during, and after exercise. The data were processed conventionally and with the addition of SIFT before quantifying peak amplitudes and frequencies. The postexercise increase in the amplitude of phosphocreatine was also characterized by fitting with an exponential function to obtain the recovery time constant. RESULTS: Substantial reductions in the uncertainty of peak fitting for phosphocreatine (73%) and inorganic phosphate (60%) were observed when using SIFT relative to conventional processing alone. SIFT also reduced the phosphocreatine recovery time constant uncertainty by 38%. CONCLUSION: SIFT considerably improves SNR, which improved quantification and parameter estimation. It is suitable for any type of time varying MRS and is both straightforward and fast to apply. Magn Reson Med 76:978-985, 2016.
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