Prastawa Marcel, Sadeghi Neda, Gilmore John H, Lin Weili, Gerig Guido
Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, Utah 84112.
Proc IEEE Int Symp Biomed Imaging. 2010:97-100. doi: 10.1109/isbi.2010.5490404.
The trajectory of early brain development is marked by rapid growth presented by volume but also by tissue property changes. Capturing regional characteristics of axonal structuring and myelination via neuroimaging requires analysis of longitudinal image data with multiple modalities. Complementary to earlier studies of volume and cortical folding analysis, this paper focuses on white matter tissue changes as seen in multimodal MRI and DTI. We propose a new framework for analyzing early maturation in white matter that generates a normative spatiotemporal model and provides 3D maps of absolute and relative indices of maturation. The method, using a continuous model of intensity changes using modified Legendre polynomials, has been applied to a multimodal dataset (T1W, T2W, PD, DTI) with 8 subjects that have been scanned at approximately 2 weeks, 1 year, and 2 years. We demonstrate that spatial maturation maps generated from different modalities capture different properties of white matter growth which might lead to a better understanding of the underlying neurobiology.
早期大脑发育的轨迹不仅表现为体积的快速增长，还表现为组织特性的变化。通过神经成像捕捉轴突结构和髓鞘形成的区域特征需要对多种模态的纵向图像数据进行分析。与早期关于体积和皮质折叠分析的研究互补，本文重点关注多模态MRI和DTI中所见的白质组织变化。我们提出了一个用于分析白质早期成熟的新框架，该框架生成一个规范的时空模型，并提供成熟度的绝对和相对指标的三维地图。该方法使用基于修正勒让德多项式的强度变化连续模型，已应用于一个多模态数据集（T1W、T2W、PD、DTI），该数据集包含8名受试者，分别在大约2周、1年和2年时进行了扫描。我们证明，从不同模态生成的空间成熟度图捕捉了白质生长的不同特性，这可能有助于更好地理解潜在的神经生物学。
