Hôpital Erasme, B-1070 Brussels, Belgium.
Magn Reson Imaging. 2010 Jul;28(6):834-41. doi: 10.1016/j.mri.2010.03.030. Epub 2010 Apr 21.
Diffusion tensor imaging (DTI) and tractography are noninvasive MRI methods, providing an insight on microscopic structural information of anisotropic tissues in vivo. The success of this technique stems on a watchful choice of imaging parameters and post-acquisition reconstruction. In the present work, we have focused on the problem of residual linear image misalignment in the DTI data and its effects on the parameters of the diffusion tensor and fiber tracking in human brain. We demonstrate substantial sensitivity of the reconstructed diffusion tensor and fiber tractography on increasing amplitude of artificially induced random image misalignment in the DTI. We show that already a submillimeter image misalignment in the DTI is an important source of error, which may potentially mask pathological presentations of the diseases and may partially explain variations in the results obtained from the DTI. Finally, we evaluated four implementations of image registrations and demonstrate their variable performance. This further supports the fact that a robust image registration must be performed to ensure reliable and reproducible diffusion tensor mapping and reconstruction of white matter (WM) fibers.
弥散张量成像（DTI）和示踪技术是一种非侵入性的 MRI 方法，可提供活体各向异性组织的微观结构信息。该技术的成功源于对成像参数的谨慎选择和采集后重建。在本工作中，我们专注于 DTI 数据中残留线性图像配准问题及其对人脑扩散张量和纤维追踪参数的影响。我们证明了在 DTI 中人为引入的随机图像配准幅度增加时，重建的扩散张量和纤维追踪术具有很大的敏感性。我们表明，即使在 DTI 中存在亚毫米级的图像配准误差，也是一个重要的误差源，可能潜在地掩盖疾病的病理表现，并部分解释从 DTI 获得的结果的变化。最后，我们评估了四种图像配准方法的实现，并证明了它们的性能存在差异。这进一步证实了必须进行稳健的图像配准，以确保可靠和可重复的弥散张量成像和白质（WM）纤维重建。
