Volume 72, Issue 2 pp. 337-346
Full Paper

Susceptibility map-weighted imaging (SMWI) for neuroimaging

Sung-Min Gho

Sung-Min Gho

Department of Electrical and Electronic Engineering, Yonsei University, Seoul, Republic of Korea

Search for more papers by this author
Chunlei Liu

Chunlei Liu

Brain Imaging and Analysis Center, Duke University, Durham, North Carolina, USA

Search for more papers by this author
Wei Li

Wei Li

Brain Imaging and Analysis Center, Duke University, Durham, North Carolina, USA

Search for more papers by this author
Ung Jang

Ung Jang

Department of Electrical and Electronic Engineering, Yonsei University, Seoul, Republic of Korea

Search for more papers by this author
Eung Yeop Kim

Eung Yeop Kim

Department of Radiology, Gachon University Gil Medical Center, 1198, Guwol-dong, Namdong-Gu, Incheon, Republic of Korea

Search for more papers by this author
Dosik Hwang

Dosik Hwang

Department of Electrical and Electronic Engineering, Yonsei University, Seoul, Republic of Korea

Search for more papers by this author
Dong-Hyun Kim

Corresponding Author

Dong-Hyun Kim

Department of Electrical and Electronic Engineering, Yonsei University, Seoul, Republic of Korea

Correspondence to: Dong-Hyun Kim, Ph.D., (120–749) Department of Electrical and Electronic Engineering, Yonsei University, 134 Shinchondong, Seodaemungu, Seoul, Republic of Korea. E-mail:[email protected]Search for more papers by this author
First published: 04 September 2013
Citations: 43

Abstract

Purpose

To propose a susceptibility map-weighted imaging (SMWI) method by combining a magnitude image with a quantitative susceptibility mapping (QSM) -based weighting factor thereby providing an alternative contrast compared with magnitude image, susceptibility-weighted imaging, and QSM.

Methods

A three-dimensional multi-echo gradient echo sequence is used to obtain the data. The QSM was transformed to a susceptibility mask that varies in amplitude between zero and unity. This mask was multiplied several times with the original magnitude image to create alternative contrasts between tissues with different susceptibilities. A temporal domain denoising method to enhance the signal-to-noise ratio was further applied. Optimal reconstruction processes of the SMWI were determined from simulations.

Results

Temporal domain denoising enhanced the signal-to-noise ratio, especially at late echoes without spatial artifacts. From phantom simulations, the optimal number of multiplication and threshold values was chosen. Reconstructed SMWI created different contrasts based on its weighting factors made from paramagnetic or diamagnetic susceptibility tissue and provided an excellent delineation of microhemorrhage without blooming artifacts typically caused by the nonlocal property of phase.

Conclusion

SMWI presents an alternative contrast for susceptibility-based imaging. The validity of this method was demonstrated using in vivo data. This proposed method together with denoising allows high-quality reconstruction of susceptibility-weighted image of human brain in vivo. Magn Reson Med 72:337–346, 2014. © 2013 Wiley Periodicals, Inc.

The full text of this article hosted at iucr.org is unavailable due to technical difficulties.