Li Wei, Wang Nian, Yu Fang, Han Hui, Cao Wei, Romero Rebecca, Tantiwongkosi Bundhit, Duong Timothy Q, Liu Chunlei
Brain Imaging and Analysis Center, Duke University, Durham NC 27705, USA; Research Imaging Institute, University of Texas Health Science Center at San Antonio, TX 78229, USA; Department of Ophthalmology, University of Texas Health Science Center at San Antonio, TX 78229, USA.
Brain Imaging and Analysis Center, Duke University, Durham NC 27705, USA.
Neuroimage. 2015 Mar;108:111-22. doi: 10.1016/j.neuroimage.2014.12.043. Epub 2014 Dec 20.
Quantitative susceptibility mapping (QSM) is a novel MRI method for quantifying tissue magnetic property. In the brain, it reflects the molecular composition and microstructure of the local tissue. However, susceptibility maps reconstructed from single-orientation data still suffer from streaking artifacts which obscure structural details and small lesions. We propose and have developed a general method for estimating streaking artifacts and subtracting them from susceptibility maps. Specifically, this method uses a sparse linear equation and least-squares (LSQR)-algorithm-based method to derive an initial estimation of magnetic susceptibility, a fast quantitative susceptibility mapping method to estimate the susceptibility boundaries, and an iterative approach to estimate the susceptibility artifact from ill-conditioned k-space regions only. With a fixed set of parameters for the initial susceptibility estimation and subsequent streaking artifact estimation and removal, the method provides an unbiased estimate of tissue susceptibility with negligible streaking artifacts, as compared to multi-orientation QSM reconstruction. This method allows for improved delineation of white matter lesions in patients with multiple sclerosis and small structures of the human brain with excellent anatomical details. The proposed methodology can be extended to other existing QSM algorithms.
定量磁化率成像(QSM)是一种用于量化组织磁特性的新型磁共振成像方法。在大脑中,它反映了局部组织的分子组成和微观结构。然而,从单方向数据重建的磁化率图仍然存在条纹伪影,这会掩盖结构细节和小病变。我们提出并开发了一种估计条纹伪影并从磁化率图中减去它们的通用方法。具体而言,该方法使用稀疏线性方程和基于最小二乘法(LSQR)算法的方法来推导磁化率的初始估计值,使用快速定量磁化率成像方法来估计磁化率边界,并采用迭代方法仅从病态k空间区域估计磁化率伪影。通过为初始磁化率估计以及随后的条纹伪影估计和去除设置一组固定参数,与多方向QSM重建相比,该方法能够提供对组织磁化率的无偏估计,且条纹伪影可忽略不计。该方法能够更好地描绘多发性硬化症患者的白质病变以及具有出色解剖细节的人脑小结构。所提出的方法可以扩展到其他现有的QSM算法。