Tissue Characterization with Diffusion MRI

描述（由申请人提供）：在医学成像中，组织表征是评估脑肿瘤病理学和形态学的基础。在T1或T2加权MR图像上，即使使用造影剂，病理组织与正常组织的区分通常也是有限的。然而，在急性中风的情况下，弥散加权MR成像的结果是良好的对比度。此外，扩散张量成像允许基于主要扩散方向和扩散各向异性的白色物质束的详细表征。可以在临床MR系统上执行的具有非常高的扩散加权的成像已经揭示，与流体中的扩散衰减信号不同，组织中的扩散相关MR信号衰减是非单指数的。从纯单指数信号衰减的偏离被发现在肿瘤组织中特别强。一个有充分根据的假设是，偏差可能与限制扩散，它确实可以提供在微米尺度水平上的细胞结构的见解。最终，在这种分辨率水平下，组织学组织样本的光学显微镜分析允许肿瘤和正常组织之间的明确区分。本研究的主要目标是通过比较MR扩散测量结果与在进行扩散扫描的组织切片中获得的光学显微镜图像数据的详细分析，进一步了解受限扩散。在人类神经纤维样本中，我们想研究扩散各向异性和神经纤维密度或髓鞘形成程度之间的关系。在动物脑肿瘤模型中，我们想比较单指数MR信号衰减与细胞密度、细胞核与细胞质尺寸比或细胞尺寸分布的偏差。磁共振扩散成像广泛用于医学诊断，并正在迅速探索新的适应症。因此，这项研究提出了基础研究，这将提高临床MR扩散图像数据的解释。

DESCRIPTION (provided by applicant): In medical imaging, tissue characterization is fundamental for the assessment of brain tumor pathology and morphology. On T1 or T2-weighted MR images, even with contrast agents, distinction of pathologic tissue from normal tissue often is limited. Excellent contrast, however, results from diffusion weighted MR imaging in the case of acute stroke. Moreover, diffusion tensor imaging permits a detailed characterization of white matter tracts based on the principal diffusion direction and diffusion anisotropy. Imaging with very high diffusion weighting, which can be performed on clinical MR systems, has revealed that the diffusion related MR signal decay in tissues, unlike the diffusion attenuated signal in fluids, is non-monoexponential. The departure from a pure monoexponential signal decay was found to be particularly strong in tumor tissue. A well-founded hypothesis is that the deviation may be linked to restricted diffusion and that it may indeed provide insights into cellular architecture at the micrometer dimension level. Ultimately, at this level of resolution, it is light microscopy analysis of histologic tissue samples that permits definitive differentiation between tumor and normal tissue. The main goal of this research is to further our understanding about restricted diffusion by comparing the MR diffusion measurements with detailed analysis of light-microscopy image data obtained in tissue sections that underwent diffusion scans. In human nerve fiber samples, we would like to investigate the relationship between diffusion anisotropy and nerve fiber density or degree of myelination. In animal brain tumor models, we would like to compare the deviation from a monoexponential MR signal decay with cell density, nucleus to cytoplasma size ratio, or cell size distribution. MR diffusion imaging is widely used for medical diagnosis and is rapidly exploring new indications. This study, therefore, proposes basic research, which will improve the interpretation of clinical MR diffusion image data.