We have recently introduced a novel MRI methodology, so-called super resolution track-density imaging (TDI), which produces high-quality white matter images, with high spatial resolution and exquisite anatomical contrast not available from other MRI modalities. This method achieves super resolution by utilising the long-range information contained in the diffusion MRI fibre tracks. In this study, we validate the super resolution property of the TDI method by using in vivo diffusion MRI data acquired at ultra-high magnetic field strength (7 T), and in silico diffusion MRI data from a well-characterised numerical phantom. Furthermore, an alternative version of the TDI technique is described, which mitigates the track length weighting of the TDI map intensity. For the in vivo data, high-resolution diffusion images were down-sampled to simulate low-resolution data, for which the high-resolution images serve as a gold standard. For the in silico data, the gold standard is given by the known simulated structures of the numerical phantom. Both the in vivo and in silico data show that the structures that could be identified in the TDI maps only after using super resolution were consistent with the corresponding structures identified in the reference maps. This supports the claim that the structures identified by the super resolution step are accurate, thus providing further evidence for the important potential role of the super resolution TDI methodology in neuroscience.

译文

我们最近推出了一种新颖的MRI方法,即所谓的超分辨率轨迹密度成像 (TDI),该方法可产生高质量的白质图像,具有其他MRI方式无法提供的高空间分辨率和精美的解剖对比度。该方法通过利用扩散MRI光纤轨迹中包含的远程信息来实现超分辨率。在这项研究中,我们通过使用在超高磁场强度 (7 T) 下获得的体内扩散MRI数据以及来自特征良好的数值模型的计算机扩散MRI数据来验证TDI方法的超分辨率。此外,描述了TDI技术的替代版本,该技术减轻了TDI地图强度的轨道长度加权。对于体内数据,对高分辨率扩散图像进行下采样以模拟低分辨率数据,其中高分辨率图像作为金标准。对于计算机数据,金标准由数值体模的已知模拟结构给出。体内和计算机数据均表明,仅在使用超分辨率后才能在TDI图中识别出的结构与参考图中识别出的相应结构一致。这支持了通过超分辨率步骤确定的结构是准确的说法,从而为超分辨率TDI方法论在神经科学中的重要潜在作用提供了进一步的证据。

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