Abstract #0869

TGV-Regularized Single-Step Quantitative Susceptibility Mapping

Itthi Chatnuntawech¹, Patrick McDaniel¹, Stephen F. Cauley^2,3, Borjan A. Gagoski^3,4, Christian Langkammer⁵, Adrian Martin⁶, Ellen Grant^3,4, Lawrence L. Wald^2,3,7, Kawin Setsompop^2,3, Elfar Adalsteinsson^1,7,8, and Berkin Bilgic²

¹Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, United States, ²Department of Radiology, A. A. Martinos Center for Biomedical Imaging, Charlestown, MA, United States, ³Harvard Medical School, Boston, MA, United States, ⁴Fetal-Neonatal Neuroimaging & Developmental Science Center, Boston Children’s Hospital, Boston, MA, United States, ⁵Department of Neurology, Medical University of Graz, Graz, Austria, ⁶Applied Mathematics, Universidad Rey Juan Carlos, Madrid, Spain, ⁷Harvard-MIT Health Sciences and Technology, Cambridge, MA, United States, ⁸Institute for Medical Engineering and Science, Cambridge, MA, United States

To directly estimate tissue magnetic susceptibility distribution from the raw phase of a gradient echo acquisition, we propose a single-step quantitative susceptibility mapping (QSM) method that benefits from its three components: (i) the single-step processing that prevents error propagation normally encountered in multiple-step QSM algorithms, (ii) multiple spherical mean value kernels that permit high fidelity background removal, and (iii) total generalized variation regularization that promotes a piecewise-smooth solution without staircasing artifacts. A fast solver for the proposed method, which enables simple analytical solutions for all of the optimization steps, is also developed. Improved image quality over conventional QSM algorithms is demonstrated using the SNR-efficient Wave-CAIPI and 3D-EPI acquisitions.

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