Lawrence R Frank1,2, Benjamin Zahneisen3, Vitaly L Galinsky1,4. 1. Center for Scientific Computation in Imaging, University of California at San Diego, La Jolla, CA, USA. 2. Center for Functional MRI, University of California at San Diego, La Jolla, CA, USA. 3. Department of Radiology, Stanford University, Stanford, CA, USA. 4. Electrical and Computer Engineering Department, University of California at San Diego, La Jolla, CA, USA.
Abstract
PURPOSE: A new method for enhancing the sensitivity of diffusion MRI (dMRI) by combining the data from single (sPFG) and double (dPFG) pulsed field gradient experiments is presented. METHODS: This method uses our JESTER framework to combine microscopic anisotropy information from dFPG experiments using a new method called diffusion tensor subspace imaging (DiTSI) to augment the macroscopic anisotropy information from sPFG data analyzed using our guided by entropy spectrum pathways method. This new method, called joint estimation diffusion imaging (JEDI), combines the sensitivity to macroscopic diffusion anisotropy of sPFG with the sensitivity to microscopic diffusion anisotropy of dPFG methods. RESULTS: Its ability to produce significantly more detailed anisotropy maps and more complete fiber tracts than existing methods within both brain white matter (WM) and gray matter (GM) is demonstrated on normal human subjects on data collected using a novel fast, robust, and clinically feasible sPFG/dPFG acquisition. CONCLUSIONS: The potential utility of this method is suggested by an initial demonstration of its ability to mitigate the problem of gyral bias. The capability of more completely characterizing the tissue structure and connectivity throughout the entire brain has broad implications for the utility and scope of dMRI in a wide range of research and clinical applications.
PURPOSE: A new method for enhancing the sensitivity of diffusion MRI (dMRI) by combining the data from single (sPFG) and double (dPFG) pulsed field gradient experiments is presented. METHODS: This method uses our JESTER framework to combine microscopic anisotropy information from dFPG experiments using a new method called diffusion tensor subspace imaging (DiTSI) to augment the macroscopic anisotropy information from sPFG data analyzed using our guided by entropy spectrum pathways method. This new method, called joint estimation diffusion imaging (JEDI), combines the sensitivity to macroscopic diffusion anisotropy of sPFG with the sensitivity to microscopic diffusion anisotropy of dPFG methods. RESULTS: Its ability to produce significantly more detailed anisotropy maps and more complete fiber tracts than existing methods within both brain white matter (WM) and gray matter (GM) is demonstrated on normal human subjects on data collected using a novel fast, robust, and clinically feasible sPFG/dPFG acquisition. CONCLUSIONS: The potential utility of this method is suggested by an initial demonstration of its ability to mitigate the problem of gyral bias. The capability of more completely characterizing the tissue structure and connectivity throughout the entire brain has broad implications for the utility and scope of dMRI in a wide range of research and clinical applications.
Authors: Michal E Komlosh; Evren Özarslan; Martin J Lizak; Ferenc Horkay; Vincent Schram; Noam Shemesh; Yoram Cohen; Peter J Basser Journal: J Magn Reson Date: 2010-10-26 Impact factor: 2.229
Authors: Evren Özarslan; Cheng Guan Koay; Timothy M Shepherd; Michal E Komlosh; M Okan İrfanoğlu; Carlo Pierpaoli; Peter J Basser Journal: Neuroimage Date: 2013-04-13 Impact factor: 6.556