Validation strategies for the interpretation of microstructure imaging using diffusion MRI
Validation strategies for the interpretation of microstructure imaging using diffusion MRI
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DOI：
10.1016/j.neuroimage.2018.06.049
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发表时间：
2018-11-15
期刊：
影响因子：
5.7
通讯作者：
Lundell, Henrik
中科院分区：
文献类型：
--
作者：
Dyrby, Tim B.;Innocenti, Giorgio M.;Lundell, Henrik
提取超出MRI图像分辨率的显微解剖信息将为诊断和神经科学研究提供有价值的工具。许多数学模型已经提出了弥散磁共振成像(DMRI)数据的微观结构解释。这种微结构特征的例子可以是细胞体和轴突，例如轴突的直径或它们的方位分布，用于使用纤维束造影术进行全球连通性分析，并且以前只能通过尸检组织的传统组织学或侵入性活组织检查来获得。从整个活着的人脑中非侵入性地获得相同知识的前景可能会推动神经和精神疾病诊断的前沿。它还可以提供对健康大脑在整个人群中的发育和自然变异性的一般了解。然而，由于图像分辨率的限制，大多数dMRI测量都是间接估计，可能依赖于从实验参数设置到模型假设和实施的整个链。在这里，我们回顾了这一领域的现有文献，并强调了验证和信任一种新的dMRI方法所需的跨解剖长度尺度的综合工作。我们鼓励在应用和开发新的验证技术方面的跨学科合作和数据共享，以提高未来dMRI方法的特异性。
Extracting microanatomical information beyond the image resolution of MRI would provide valuable tools for diagnostics and neuroscientific research. A number of mathematical models already suggest microstructural interpretations of diffusion MRI (dMRI) data. Examples of such microstructural features could be cell bodies and neurites, e.g. the axon's diameter or their orientational distribution for global connectivity analysis using tractography, and have previously only been possible to access through conventional histology of post mortem tissue or invasive biopsies. The prospect of gaining the same knowledge non-invasively from the whole living human brain could push the frontiers for the diagnosis of neurological and psychiatric diseases. It could also provide a general understanding of the development and natural variability in the healthy brain across a population. However, due to a limited image resolution, most of the dMRI measures are indirect estimations and may depend on the whole chain from experimental parameter settings to model assumptions and implementation.Here, we review current literature in this field and highlight the integrative work across anatomical length scales that is needed to validate and trust a new dMRI method. We encourage interdisciplinary collaborations and data sharing in regards to applying and developing new validation techniques to improve the specificity of future dMRI methods.