Comparison of quantitative susceptibility mapping methods on evaluating radiation-induced cerebral microbleeds and basal ganglia at 3T and 7T.
Comparison of quantitative susceptibility mapping methods on evaluating radiation-induced cerebral microbleeds and basal ganglia at 3T and 7T.
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作者:
Quantitative susceptibility mapping (QSM) has the potential of being a biomarker for various diseases because of its ability to measure tissue susceptibility related to iron deposition, myelin, and hemorrhage from the phase signal of a T2*-weighted MRI. Despite its promise as a quantitative marker, QSM is faced with many challenges, including its dependence on preprocessing of the raw phase data, the relatively weak tissue signal, and the inherently ill-posed relationship between the magnetic dipole and measured phase. The goal of this study was to evaluate the effects of background field removal and dipole inversion algorithms on noise characteristics, image uniformity, and structural contrast for CMB quantification at both 3T and 7T. We selected four widely used background phase removal and five dipole field inversion algorithms for QSM and applied them to patients with cerebral microbleeds (CMB) who were scanned at two different field strengths and volunteers with ground truth QSM reference calculated using multiple orientation scans. 7T MRI provided QSM images with lower noise than 3T MRI. QSIP and VSHARP + iLSQR achieved the highest white matter homogeneity and vein contrast, with QSIP also providing the highest CMB contrast. Compared to ground truth COSMOS QSM images, overall good correlations between susceptibility values of dipole inversion algorithms and the COSMOS reference were observed in basal ganglia regions, with VSHARP + iLSQR achieving the most similar susceptibility values to COSMOS across all regions. This study can provide guidance for selecting the most appropriate QSM processing pipeline based on the application of interest and scanner field strength.
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影响因子:
3.3
作者:
Langkammer C;Schweser F;Shmueli K;Kames C;Li X;Guo L;Milovic C;Kim J;Wei H;Bredies K;Buch S;Guo Y;Liu Z;Meineke J;Rauscher A;Marques JP;Bilgic B
通讯作者:
Bilgic B
影响因子:
3.3
作者:
Liu, Tian;Liu, Jing;Wang, Yi
通讯作者:
Wang, Yi
影响因子:
3.7
作者:
Acosta-Cabronero J;Williams GB;Cardenas-Blanco A;Arnold RJ;Lupson V;Nestor PJ
通讯作者:
Nestor PJ
影响因子:
15.9
作者:
Lupo, Janine M.;Molinaro, Annette M.;Nelson, Sarah J.
通讯作者:
Nelson, Sarah J.
DOI:
10.1016/j.ijrobp.2011.05.046
发表时间:
2012-03-01
影响因子:
7
作者:
Lupo, Janine M.;Chuang, Cynthia F.;Nelson, Sarah J.
通讯作者:
Nelson, Sarah J.