Reliability in multi-site structural MRI studies: Effects of gradient non-linearity correction on phantom and human data
Reliability in multi-site structural MRI studies: Effects of gradient non-linearity correction on phantom and human data
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DOI：
10.1016/j.neuroimage.2005.09.046
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发表时间：
2006-04-01
期刊：
影响因子：
5.7
通讯作者：
Dale, A
中科院分区：
文献类型：
--
作者：
Jovicich, J;Czanner, S;Dale, A
纵向和多站点的临床研究创造了表征和纠正技术来源的必要性，该方差限制了高分辨率结构MRI研究中的图像可重复性，从而促进了精确，定量，无关，独立的，多站点评估。在这项工作中，我们研究了成像梯度非线性对多站点人MRL的可重复性的影响，我们采用了一种基于梯度的球形谐波描述的图像失真校正方法，并使用Phantom数据验证了该方法的准确性。然后将校正方法应用于来自具有不同1.5 T平台的多个位点两次扫描的受试者的大脑图像数据。通过评估基于体素的图像强度可重复性来评估图像数据的现场内部和跨站点变化。通过失真校正，人脑数据的图像强度可重复性显着提高，这表明该方法可以改善形态计量学研究的可重复性。我们提供梯度失真算法的源代码以及幻影数据。 （c）2005 Elsevier Inc.保留所有权利。
Longitudinal and multi-site clinical studies create the imperative to characterize and correct technological sources of variance that limit image reproducibility in high-resolution structural MRI studies, thus facilitating precise, quantitative, platform-independent, multi-site evaluation. In this work, we investigated the effects that imaging gradient non-linearity have on reproducibility of multi-site human MRL We applied an image distortion correction method based on spherical harmonics description of the gradients and verified the accuracy of the method using phantom data. The correction method was then applied to the brain image data from a group of subjects scanned twice at multiple sites having different 1.5 T platforms. Within-site and across-site variabifity of the image data was assessed by evaluating voxel-based image intensity reproducibility. The image intensity reproducibility of the human brain data was significantly improved with distortion correction, suggesting that this method may offer improved reproducibility in morphometry studies. We provide the source code for the gradient distortion algorithm together with the phantom data. (c) 2005 Elsevier Inc. All rights reserved.