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超高场多回波梯度回波 MRI 中的信号隔室反映了大脑中潜在的组织微观结构。

Signal compartments in ultra-high field multi-echo gradient echo MRI reflect underlying tissue microstructure in the brain.

机构信息

Centre for Advanced Imaging, University of Queensland, Brisbane, Queensland, Australia; Queensland Brain Institute, University of Queensland, Brisbane, Queensland, Australia.

Centre for Advanced Imaging, University of Queensland, Brisbane, Queensland, Australia.

出版信息

Neuroimage. 2018 Sep;178:403-413. doi: 10.1016/j.neuroimage.2018.05.061. Epub 2018 May 28.

Abstract

Gradient recalled echo magnetic resonance imaging (GRE-MRI) at ultra-high field holds great promise for new contrast mechanisms and delineation of putative tissue compartments that contribute to the multi-echo GRE-MRI signal may aid structural characterization. Several studies have adopted the three water-pool compartment model to study white matter brain regions, associating individual compartments with myelin, axonal and extracellular water. However, the number and identifiability of GRE-MRI signal compartments has not been fully explored. We undertook this task for human brain imaging data. Multiple echo time GRE-MRI data were acquired in five healthy participants, specific anatomical structures were segmented in each dataset (substantia nigra, caudate, insula, putamen, thalamus, fornix, internal capsule, corpus callosum and cerebrospinal fluid), and the signal fitted with models comprising one to six signal compartments using a complex-valued plane wave formulation. Information criteria and cluster analysis methods were used to ascertain the number of distinct compartments within the signal from each structure and to determine their respective frequency shifts. We identified five principal signal compartments with different relative contributions to each structure's signal. Voxel-based maps of the volume fraction of each of these compartments were generated and demonstrated spatial correlation with brain anatomy.

摘要

超高场梯度回波磁共振成像(GRE-MRI)有望提供新的对比机制,并能描绘出可能对多回波 GRE-MRI 信号有贡献的假定组织隔室,这可能有助于进行结构特征描述。已有几项研究采用三水池模型来研究脑白质区域,将各个隔室与髓鞘、轴突和细胞外水相关联。然而,GRE-MRI 信号隔室的数量和可识别性尚未得到充分探索。我们针对人脑成像数据开展了这项任务。在五名健康参与者中采集了多回波时间 GRE-MRI 数据,在每个数据集(黑质、尾状核、脑岛、壳核、丘脑、穹窿、内囊、胼胝体和脑脊液)中对特定解剖结构进行了分割,并使用复值平面波公式对包含一个到六个信号隔室的模型对信号进行拟合。使用信息准则和聚类分析方法来确定来自每个结构的信号中的不同隔室数量,并确定它们各自的频移。我们确定了五个主要的信号隔室,它们对每个结构的信号有不同的相对贡献。生成了这些隔室中每个的体积分数的体素图,并证明了它们与大脑解剖结构的空间相关性。

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