Tsang-Wei Tu1, Matthew D Budde2, Mingqiang Xie3, Ying-Jr Chen4, Qing Wang5, James D Quirk3, Sheng-Kwei Song6. 1. Radiology & Imaging Sciences, Clinical Center, National Institutes of Health, Bethesda, MD, USA. 2. Department of Neurosurgery, Medical College of Wisconsin, Milwaukee, WI, USA. 3. Department of Pathology and Immunology, Washington University, St. Louis, MO, USA. 4. Department of Chemistry, Washington University, St. Louis, MO, USA. 5. Department of Radiology, Washington University, St. Louis, MO, USA. 6. Department of Radiology, Washington University, St. Louis, MO, USA. Electronic address: ssong@wustl.edu.
Abstract
PURPOSE: To improve signal-noise-ratio of in vivo mouse spinal cord diffusion tensor imaging using-phase aligned multiple spin-echo technique. MATERIAL AND METHODS: In vivo mouse spinal cord diffusion tensor imaging maps generated by multiple spin-echo and conventional spin-echo diffusion weighting were examined to demonstrate the efficacy of multiple spin-echo diffusion sequence to improve image quality and throughput. Effects of signal averaging using complex, magnitude and phased images from multiple spin-echo diffusion weighting were also assessed. Bayesian probability theory was used to generate phased images by moving the coherent signals to the real channel to eliminate the effect of phase variation between echoes while preserving the Gaussian noise distribution. Signal averaging of phased multiple spin-echo images potentially solves both the phase incoherence problem and the bias of the elevated Rician noise distribution in magnitude image. The proposed signal averaging with Bayesian phase-aligned multiple spin-echo images approach was compared to the conventional spin-echo data acquired with doubling the scan time. The diffusion tensor imaging parameters were compared in the mouse contusion spinal cord injury. Significance level (p-value) and effect size (Cohen's d) were reported between the control and contused spinal cord to inspect the sensitivity of each approach in detecting white matter pathology. RESULTS: Compared to the spin-echo image, the signal-noise-ratio increased to 1.84-fold using the phased image averaging and to 1.30-fold using magnitude image averaging in the spinal cord white matter. Multiple spin-echo phased image averaging showed improved image quality of the mouse spinal cord among the tested methods. Diffusion tensor imaging metrics obtained from multiple spin-echo phased images using three echoes and two averages closely agreed with those derived by spin-echo magnitude data with four averages (two times more in acquisition time). The phased image averaging correctly reflected pathological features in contusion spinal cord injury. CONCLUSION: Our in vivo imaging results indicate that averaging the phased multiple spin-echo images yields an 84% signal-noise-ratio increase over the spin-echo images and a 41% gain over the magnitude averaged multiple spin-echo images with equal acquisition time. Current results from the animal model of spinal cord injury suggest that the phased multiple spin-echo images could be used to improve signal-noise-ratio.
PURPOSE: To improve signal-noise-ratio of in vivo mouse spinal cord diffusion tensor imaging using-phase aligned multiple spin-echo technique. MATERIAL AND METHODS: In vivo mouse spinal cord diffusion tensor imaging maps generated by multiple spin-echo and conventional spin-echo diffusion weighting were examined to demonstrate the efficacy of multiple spin-echo diffusion sequence to improve image quality and throughput. Effects of signal averaging using complex, magnitude and phased images from multiple spin-echo diffusion weighting were also assessed. Bayesian probability theory was used to generate phased images by moving the coherent signals to the real channel to eliminate the effect of phase variation between echoes while preserving the Gaussian noise distribution. Signal averaging of phased multiple spin-echo images potentially solves both the phase incoherence problem and the bias of the elevated Rician noise distribution in magnitude image. The proposed signal averaging with Bayesian phase-aligned multiple spin-echo images approach was compared to the conventional spin-echo data acquired with doubling the scan time. The diffusion tensor imaging parameters were compared in the mouse contusion spinal cord injury. Significance level (p-value) and effect size (Cohen's d) were reported between the control and contused spinal cord to inspect the sensitivity of each approach in detecting white matter pathology. RESULTS: Compared to the spin-echo image, the signal-noise-ratio increased to 1.84-fold using the phased image averaging and to 1.30-fold using magnitude image averaging in the spinal cord white matter. Multiple spin-echo phased image averaging showed improved image quality of the mouse spinal cord among the tested methods. Diffusion tensor imaging metrics obtained from multiple spin-echo phased images using three echoes and two averages closely agreed with those derived by spin-echo magnitude data with four averages (two times more in acquisition time). The phased image averaging correctly reflected pathological features in contusion spinal cord injury. CONCLUSION: Our in vivo imaging results indicate that averaging the phased multiple spin-echo images yields an 84% signal-noise-ratio increase over the spin-echo images and a 41% gain over the magnitude averaged multiple spin-echo images with equal acquisition time. Current results from the animal model of spinal cord injury suggest that the phased multiple spin-echo images could be used to improve signal-noise-ratio.
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