Pasternak Ofer, Sochen Nir, Gur Yaniv, Intrator Nathan, Assaf Yaniv
Blavatnik School of Computer Science, Raymond and Beverly Sackler Faculty of Exact Sciences, Tel Aviv University, Tel Aviv, Israel.
Magn Reson Med. 2009 Sep;62(3):717-30. doi: 10.1002/mrm.22055.
Relating brain tissue properties to diffusion tensor imaging (DTI) is limited when an image voxel contains partial volume of brain tissue with free water, such as cerebrospinal fluid or edema, rendering the DTI indices no longer useful for describing the underlying tissue properties. We propose here a method for separating diffusion properties of brain tissue from surrounding free water while mapping the free water volume. This is achieved by fitting a bi-tensor model for which a mathematical framework is introduced to stabilize the fitting. Applying the method on datasets from a healthy subject and a patient with edema yielded corrected DTI indices and a more complete tract reconstruction that passed next to the ventricles and through the edema. We were able to segment the edema into areas according to the condition of the underlying tissue. In addition, the volume of free water is suggested as a new quantitative contrast of diffusion MRI. The findings suggest that free water is not limited to the borders of the brain parenchyma; it therefore contributes to the architecture surrounding neuronal bundles and may indicate specific anatomical processes. The analysis requires a conventional DTI acquisition and can be easily merged with existing DTI pipelines.
当图像体素包含含有自由水的脑组织部分体积（如脑脊液或水肿）时，将脑组织特性与扩散张量成像（DTI）相关联是有限的，这使得DTI指数不再可用于描述潜在的组织特性。我们在此提出一种方法，用于在绘制自由水体积的同时，将脑组织的扩散特性与周围的自由水分离。这是通过拟合一个双张量模型来实现的，为此引入了一个数学框架来稳定拟合。将该方法应用于来自健康受试者和水肿患者的数据集，得到了校正后的DTI指数和更完整的纤维束重建，该重建通过脑室旁边并穿过水肿区域。我们能够根据潜在组织的状况将水肿分割成不同区域。此外，自由水的体积被建议作为扩散MRI的一种新的定量对比指标。研究结果表明，自由水不限于脑实质的边界；因此，它对神经元束周围的结构有贡献，并且可能指示特定的解剖过程。该分析需要常规的DTI采集，并且可以很容易地与现有的DTI流程合并。
