Sub-Second Continuous 2D Non-Fourier Dynamic Adaptive MRI Using Near-Optimal Spatial ... excitations in order to dramatically increase the efficiency of MR.
Sub-Second Continuous 2D Non-Fourier Dynamic Adaptive MRI Using Near-Optimal Spatial Encoding Dimitrios MITSOURAS1, Alan S. EDELMAN2, Lawrence Patrick PANYCH3, Ferenc A. JOLESZ4, Gary ZIENTARA5
1Massachusetts Institute of Technology, Department of Electrical Engineering and Laboratory for Computer Science, Cambridge, MA United States; 2Massachusetts Institute of Technology, Department of Mathematics and Laboratory for Computer Science, Cambridge, MA USA; 3Brigham and Women's Hospital, Harvard Medical School, Department of Radiology, Boston, MA USA; 4Brigham and Women's Hospital, Harvard Medical School, 75 Francis Street, Boston, MA USA; 5Brigham and Women's Hospital, Harvard University, Department of Radiology, Boston, MA USA; Introduction Previously, it was shown (1,2) that linear algebraic decompositions such as the SVD can be applied in conjunction with spatially selective excitations in order to dramatically increase the efficiency of MR signal acquisition (3) for applications where the FOV is changing. Using non-Fourier spatially selective encoding, we are able to truncate the amount of data acquired in an imaging cycle, using a subspace computed from relatively recent contents of the FOV and are able to reconstruct a good approximation to the current contents. Linear algebraic decompositions such as the SVD or Krylov methods can provide the subspace. We have designed and implemented a specialized hardware and software system operating in near real-time (e.g. sub-second image acquisition), employing non-Fourier spatially selective excitations dynamically computed 'on the fly' from the current contents of the FOV. The system is attached to a commercial GE SIGNA LX Echospeed MR scanner (GE Medical Systems, Milwaukee, WI), and is currently capable of producing 128x128 and 256x256 spin echo images in
