Conklin Chris J, Middleton Devon M, Alizadeh Mahdi, Finsterbusch Jürgen, Raunig David L, Faro Scott H, Shah Pallav, Krisa Laura, Sinko Rebecca, Delalic Joan Z, Mulcahey M J, Mohamed Feroze B
Electrical Engineering, Temple University, Philadelphia, PA, United States; Radiology, Thomas Jefferson University, Philadelphia, PA, United States.
Radiology, Temple University, Philadelphia, PA, United States; Bioengineering, Temple University, Philadelphia, PA, United States.
Neuroimage Clin. 2016 Jan 12;11:61-67. doi: 10.1016/j.nicl.2016.01.009. eCollection 2016.
Magnetic resonance based diffusion imaging has been gaining more utility and clinical relevance over the past decade. Using conventional echo planar techniques, it is possible to acquire and characterize water diffusion within the central nervous system (CNS); namely in the form of Diffusion Weighted Imaging (DWI) and Diffusion Tensor Imaging (DTI). While each modality provides valuable clinical information in terms of the presence of diffusion and its directionality, both techniques are limited to assuming an ideal Gaussian distribution for water displacement with no intermolecular interactions. This assumption neglects pathological processes that are not Gaussian therefore reducing the amount of potentially clinically relevant information. Additions to the Gaussian distribution measured by the excess kurtosis, or peakedness, of the probabilistic model provide a better understanding of the underlying cellular structure. The objective of this work is to provide mathematical and experimental evidence that Diffusion Kurtosis Imaging (DKI) can offer additional information about the micromolecular environment of the pediatric spinal cord. This is accomplished by a more thorough characterization of the nature of random water displacement within the cord. A novel DKI imaging sequence based on a tilted 2D spatially selective radio frequency pulse providing reduced field of view (FOV) imaging was developed, implemented, and optimized on a 3 Tesla MRI scanner, and tested on pediatric subjects (healthy subjects: 15; patients with spinal cord injury (SCI):5). Software was developed and validated for post processing of the DKI images and estimation of the tensor parameters. The results show statistically significant differences in mean kurtosis (p < 0.01) and radial kurtosis (p < 0.01) between healthy subjects and subjects with SCI. DKI provides incremental and novel information over conventional diffusion acquisitions when coupled with higher order estimation algorithms.
在过去十年中，基于磁共振的扩散成像已变得更具实用性和临床相关性。使用传统的回波平面技术，可以获取并表征中枢神经系统（CNS）内的水扩散情况；具体表现为扩散加权成像（DWI）和扩散张量成像（DTI）。虽然每种模态在扩散的存在及其方向性方面都提供了有价值的临床信息，但这两种技术都局限于假设水分子位移呈理想的高斯分布，不存在分子间相互作用。这种假设忽略了非高斯分布的病理过程，从而减少了潜在的临床相关信息量。通过概率模型的超额峰度（即峰态）来测量对高斯分布的补充，能更好地理解潜在的细胞结构。这项工作的目的是提供数学和实验证据，证明扩散峰度成像（DKI）可以提供有关小儿脊髓微分子环境的额外信息。这是通过对脊髓内随机水分子位移的性质进行更全面的表征来实现的。基于倾斜的二维空间选择性射频脉冲开发了一种新型DKI成像序列，该序列可提供缩小视野（FOV）成像，在3特斯拉MRI扫描仪上进行了实施和优化，并在小儿受试者（健康受试者：15名；脊髓损伤（SCI）患者：5名）上进行了测试。开发并验证了用于DKI图像后处理和张量参数估计的软件。结果显示，健康受试者与SCI受试者之间的平均峰度（p < 0.01）和径向峰度（p < 0.01）存在统计学上的显著差异。当与高阶估计算法结合使用时，DKI能在传统扩散采集的基础上提供增量和新颖的信息。
