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Abstract #4751

MPPCA denoising before GRAPPA reconstruction improves the precision of microscopic anisotropy in the gray matter

Kouhei Kamiya1,2,3, Issei Fukunaga1, Syo Murata1,4, Tomoko Maekawa1, Shimpei Kato1,3, Katsutoshi Murata5, Thorsten Feiweier6, Koji Kamagata1, Masaaki Hori1,2, and Shigeki Aoki1
1Department of Radiology, Juntendo University, Tokyo, Japan, 2Department of Radiology, Toho University, Tokyo, Japan, 3Department of Radiology, The University of Tokyo, Tokyo, Japan, 4Department of Radiological Sciences, Komazawa University, Tokyo, Japan, 5Siemens Healthcare K.K., Tokyo, Japan, 6Siemens Healthcare GmbH, Erlangen, Germany


The ability of double diffusion encoding to estimate tissue microscopic anisotropy has gained increasing attention in clinical studies. However, the estimation of smaller values of microscopic anisotropy is known to be less precise, posing a challenge for clinical translation because many tissues of interest including the gray matter exhibit smaller values. In this study, we adopted the recently proposed denoising strategy where Marcenko‐Pastur principal component analysis (MPPCA) is applied to coil data before GRAPPA reconstruction. The results suggested this strategy is effective for improving the scan-rescan repeatability of microscopic anisotropy in the gray matter.

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