Abstract #1346

Improved multi-shot EPI ghost correction for high gradient strength diffusion MRI using Structured Low-Rank Modeling k-space reconstruction

Gabriel Ramos-Llordén¹, Rodrigo A. Lobos², Tae Hyung Kim¹, Qiyuan Tian¹, Slimane Tounetki¹, Thomas Witzel³, Boris Keil⁴, Anatasia Yendiki¹, Berkin Bilgic^1,5, Justin P. Haldar², and Susie Huang^1,5

¹Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Masachusetts General Hospital, Harvard Medical School, Charlestown, MA, United States, ²Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, CA, United States, ³Q Bio Inc, San Carlos, CA, United States, ⁴Institute of Medical Physics and Radiation Protection, Mittelhessen University of Applied Sciences, Giessen, Germany, ⁵Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, United States

Multi-shot EPI diffusion MRI acquired using high diffusion-encoding gradient strengths suffers from severe ghosting artifacts, which can bias and confound the estimation of diffusion microstructural MRI measures at high b-values. In this work, we show that conventional EPI ghost correction techniques fall short in ghosting reduction when high diffusion-encoding gradient strengths ~250mT/m are used, and that advanced reconstruction algorithms based on structured low-rank matrix modeling can substantially reduce ghosting without introducing additional artifacts.

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