Streaking artifact reduction for quantitative susceptibility mapping of sources with large dynamic range.

Published

Journal Article

Quantitative susceptibility mapping (QSM) is a novel MRI technique for the measurement of tissue magnetic susceptibility in three dimensions. Although numerous algorithms have been developed to solve this ill-posed inverse problem, the estimation of susceptibility maps with a wide range of values is still problematic. In cases such as large veins, contrast agent uptake and intracranial hemorrhages, extreme susceptibility values in focal areas cause severe streaking artifacts. To enable the reduction of these artifacts, whilst preserving subtle susceptibility contrast, a two-level QSM reconstruction algorithm (streaking artifact reduction for QSM, STAR-QSM) was developed in this study by tuning a regularization parameter to automatically reconstruct both large and small susceptibility values. Compared with current state-of-the-art QSM methods, such as the improved sparse linear equation and least-squares (iLSQR) algorithm, STAR-QSM significantly reduced the streaking artifacts, whilst preserving the sharp boundaries for blood vessels of mouse brains in vivo and fine anatomical details of high-resolution mouse brains ex vivo. Brain image data from patients with cerebral hematoma and multiple sclerosis further illustrated the superiority of this method in reducing streaking artifacts caused by large susceptibility sources, whilst maintaining sharp anatomical details. STAR-QSM is implemented in STI Suite, a comprehensive shareware for susceptibility imaging and quantification.

Full Text

Duke Authors

Cited Authors

  • Wei, H; Dibb, R; Zhou, Y; Sun, Y; Xu, J; Wang, N; Liu, C

Published Date

  • October 2015

Published In

Volume / Issue

  • 28 / 10

Start / End Page

  • 1294 - 1303

PubMed ID

  • 26313885

Pubmed Central ID

  • 26313885

Electronic International Standard Serial Number (EISSN)

  • 1099-1492

International Standard Serial Number (ISSN)

  • 0952-3480

Digital Object Identifier (DOI)

  • 10.1002/nbm.3383

Language

  • eng