Dataset Information

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

ABSTRACT: 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.

SUBMITTER: Wei H

PROVIDER: S-EPMC4572914 | biostudies-literature | 2015 Oct

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

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

Wei Hongjiang H Dibb Russell R Zhou Yan Y Sun Yawen Y Xu Jianrong J Wang Nian N Liu Chunlei C

NMR in biomedicine 20150827 10

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 reduc ...[more]

PMID: 26313885

Similar Datasets

Project description:BACKGROUND:Accurate measurement of the liver iron concentration (LIC) is needed to guide iron-chelating therapy for patients with transfusional iron overload. In this work, we investigate the feasibility of automated quantitative susceptibility mapping (QSM) to measure the LIC. PURPOSE:To develop a rapid, robust, and automated liver QSM for clinical practice. STUDY TYPE:Prospective. POPULATION:13 healthy subjects and 22 patients. FIELD STRENGTH/SEQUENCES:1.5 T and 3 T/3D multiecho gradient-recalled echo (GRE) sequence. ASSESSMENT:Data were acquired using a 3D GRE sequence with an out-of-phase echo spacing with respect to each other. All odd echoes that were in-phase (IP) were used to initialize the fat-water separation and field estimation (T2 *-IDEAL) before performing QSM. Liver QSM was generated through an automated pipeline without manual intervention. This IP echo-based initialization method was compared with an existing graph cuts initialization method (simultaneous phase unwrapping and removal of chemical shift, SPURS) in healthy subjects (n = 5). Reproducibility was assessed over four scanners at two field strengths from two manufacturers using healthy subjects (n = 8). Clinical feasibility was evaluated in patients (n = 22). STATISTICAL TESTS:IP and SPURS initialization methods in both healthy subjects and patients were compared using paired t-test and linear regression analysis to assess processing time and region of interest (ROI) measurements. Reproducibility of QSM, R2 *, and proton density fat fraction (PDFF) among the four different scanners was assessed using linear regression, Bland-Altman analysis, and the intraclass correlation coefficient (ICC). RESULTS:Liver QSM using the IP method was found to be ~5.5 times faster than SPURS (P < 0.05) in initializing T2 *-IDEAL with similar outputs. Liver QSM using the IP method were reproducibly generated in all four scanners (average coefficient of determination 0.95, average slope 0.90, average bias 0.002 ppm, 95% limits of agreement between -0.06 to 0.07 ppm, ICC 0.97). DATA CONCLUSION:Use of IP echo-based initialization enables robust water/fat separation and field estimation for automated, rapid, and reproducible liver QSM for clinical applications. LEVEL OF EVIDENCE:1 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;50:725-732.

Dataset Information

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

Publications

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

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets