Abstract #3078

Joint-CAIPI reconstruction of multi-echo GRASE data for fast, high-resolution myelin water imaging

Gian Franco Piredda^1,2,3, Tom Hilbert^1,2,3, Berkin Bilgic^4,5,6, Erick Jorge Canales-Rodríguez³, Marco Pizzolato^3,7, Reto Meuli², Jean-Philippe Thiran^2,3, and Tobias Kober^1,2,3

¹Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland, ²Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland, ³LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland, ⁴Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, United States, ⁵Department of Radiology, Harvard Medical School, Boston, MA, United States, ⁶Harvard‐MIT Health Sciences and Technology, MIT, Cambridge, MA, United States, ⁷Department of Applied Mathematics and Computer Science, Technical University of Denmark, Kongens Lyngby, Denmark

In previous work, CAIPIRINHA was implemented in multi-echo gradient and spin echo (GRASE) acquisitions for 3D myelin water imaging, achieving significant acceleration. However, residual undersampling artifacts prevented further acquisition time reduction. In this work, we propose a joint-CAIPI reconstruction across echoes of GRASE k-space data to remove aliasing artifacts and further accelerate the acquisition. Exploiting the redundant anatomical information across the different GRASE echoes helped mitigate aliasing artifacts in myelin water fraction maps and provided an additional ~40% reduction in scan time to 6:18$$$\,$$$minutes for a whole-brain acquisition at 1.6$$$\,$$$mm³ isotropic resolution.

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