Correction for direction-dependent distortions in diffusion tensor imaging using matched magnetic field maps
Correction for direction-dependent distortions in diffusion tensor imaging using matched magnetic field maps
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DOI：
10.1016/j.neuroimage.2005.09.008
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发表时间：
2006-03-01
期刊：
影响因子：
5.7
通讯作者：
Song, AW
中科院分区：
文献类型：
--
作者：
Chen, B;Guo, H;Song, AW
过去十年中，弥散张量成像（DTI）在临床和基础科学研究中的应用不断增加。通过评估生物组织内的水扩散各向异性，例如在大脑中，研究人员可以推断出对神经通路重要的不同纤维结构。典型的 DTI 数据集包含至少一幅基础图像和沿非共线编码方向的六幅扩散加权图像。然后可以组合所得图像以导出扩散张量的三个主轴及其各自的交叉项，这又可以用于计算分数各向异性 (FA) 图、表观扩散系数 (ADC) 图并构建轴突纤维。上述操作均假设同一大脑沿不同扩散加权方向的 DTI 图像相互配准而没有空间失真。这种假设通常是错误的，因为大的扩散加权梯度通常会感应涡流以生成扩散加权方向相关的场梯度，从而导致 DTI 数据集中的配准错误。校正磁场引起的畸变的传统方法通常不会考虑 DTI 特有的这些与方向相关的涡流，而且通常非常耗时，因为需要采集多个相位图像。在本报告中，我们描述了一种高效且有效的方法的理论和实现，该方法可在统一的框架下校正 DTI 图像的主场和涡流引起的方向相关畸变，以促进 DTI 采集的日常实践。 (c) 2005 Elsevier Inc. 保留所有权利。
Diffusion tensor imaging (DTI) has seen increased usage in clinical and basic science research in the past decade. By assessing the water diffusion anisotropy within biological tissues, e.g. brain, researchers can infer different fiber structures important for neural pathways. A typical DTI data set contains at least one base image and six diffusion-weighted images along non-collinear encoding directions. The resultant images can then be combined to derive the three principal axes of the diffusion tensor and their respective cross terms, which can in turn be used to compute fractional anisotropy (FA) maps, apparent diffusion coefficient (ADC) maps, and to construct axonal fibers. The above operations all assume that DTI images along different diffusion-weighting directions for the same brain register to each other without spatial distortions. This assumption is generally false, as the large diffusion-weighting gradients would usually induce eddy currents to generate diffusion-weighting direction-dependent field gradients, leading to mis-registration within the DTI data set. Traditional methods for correcting magnetic field-induced distortions do not usually take into account these direction-dependent eddy currents unique for DTI, and they are usually time-consuming because multiple phase images need to be acquired. In this report, we describe our theory and implementation of an efficient and effective method to correct for the main field and eddy current-induced direction-dependent distortions for DTI images under a unified framework to facilitate the daily practice of DTI acquisitions. (c) 2005 Elsevier Inc. All rights reserved.