Sadeghi Neda, Prastawa Marcel, Gilmore John H, Lin Weili, Gerig Guido
Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, Utah 84112 ; Department of Biomedical Engineering, University of Utah, Salt Lake City, Utah 84112.
Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, Utah 84112 ; School of Computing, University of Utah, Salt Lake City, Utah 84112.
Proc SPIE Int Soc Opt Eng. 2010 Mar 12;7623:76232U-. doi: 10.1117/12.844526.
The human brain undergoes significant changes in the first few years after birth, but knowledge about this critical period of development is quite limited. Previous neuroimaging studies have been mostly focused on morphometric measures such as volume and shape, although tissue property measures related to the degree of myelination and axon density could also add valuable information to our understanding of brain maturation. Our goal is to complement brain growth analysis via morphometry with the study of longitudinal tissue property changes as reflected in patterns observed in multi-modal structural MRI and DTI. Our preliminary study includes eight healthy pediatric subjects with repeated scans at the age of two weeks, one year, and two years with T1, T2, PD, and DT MRI. Analysis is driven by the registration of multiple modalities and time points within and between subjects into a common coordinate frame, followed by image intensity normalization. Quantitative tractography with diffusion and structural image parameters serves for multi-variate tissue analysis. Different patterns of rapid changes were observed in the corpus callosum and the posterior and anterior internal capsule, structures known for distinctly different myelination growth. There are significant differences in central versus peripheral white matter, and also a wm/gm contrast flip in both T1 and T2 images but not diffusion parameters. We demonstrate that the combined longitudinal analysis of structural and diffusion MRI proves superior to individual modalities and might provide a better understanding of the trajectory of early neurodevelopment.
人类大脑在出生后的头几年会经历显著变化,但关于这一关键发育时期的知识相当有限。以往的神经影像学研究大多集中在形态测量指标上,如体积和形状,尽管与髓鞘化程度和轴突密度相关的组织特性测量也可为我们理解大脑成熟提供有价值的信息。我们的目标是通过形态测量学对大脑生长进行分析,并结合多模态结构磁共振成像(MRI)和扩散张量成像(DTI)中观察到的模式所反映的纵向组织特性变化进行研究。我们的初步研究包括八名健康的儿科受试者,他们在两周、一岁和两岁时分别进行了T1、T2、质子密度加权成像(PD)和DTI MRI的重复扫描。分析过程是将受试者内部和之间的多个模态和时间点配准到一个共同的坐标框架中,然后进行图像强度归一化。利用扩散和结构图像参数进行定量纤维束成像,用于多变量组织分析。在胼胝体以及后、前内囊(已知具有明显不同髓鞘化生长的结构)中观察到了不同的快速变化模式。中央白质和外周白质存在显著差异,在T1和T2图像中也存在白质/灰质对比度反转,但扩散参数不存在这种情况。我们证明,结构MRI和扩散MRI的联合纵向分析优于单独的模态分析,可能会更好地理解早期神经发育的轨迹。