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Intracortical smoothing of small-voxel fMRI data can provide increased detection power without spatial resolution losses compared to conventional large-voxel fMRI data

机译:与传统的大体素fMRI数据相比小体素fMRI数据的皮层内平滑处理可提供增强的检测能力而不会造成空间分辨率损失

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摘要

Continued improvement in MRI acquisition technology has made functional MRI (fMRI) with small isotropic voxel sizes down to 1 mm and below more commonly available. Although many conventional fMRI studies seek to investigate regional patterns of cortical activation for which conventional voxel sizes of 3 mm and larger provide sufficient spatial resolution, smaller voxels can help avoid contamination from adjacent white matter (WM) and cerebrospinal fluid (CSF), and thereby increase the specificity of fMRI to signal changes within the gray matter. Unfortunately, temporal signal-to-noise ratio (tSNR), a metric of fMRI sensitivity, is reduced in high-resolution acquisitions, which offsets the benefits of small voxels. Here we introduce a framework that combines small, isotropic fMRI voxels acquired at 7 Tesla field strength with a novel anatomically-informed, surface mesh-navigated spatial smoothing that can provide both higher detection power and higher resolution than conventional voxel sizes. Our smoothing approach uses a family of intracortical surface meshes and allows for kernels of various shapes and sizes, including curved 3D kernels that adapt to and track the cortical folding pattern. Our goal is to restrict smoothing to the cortical gray matter ribbon and avoid noise contamination from CSF and signal dilution from WM via partial volume effects. We found that the intracortical kernel that maximizes tSNR does not maximize percent signal change (ΔS/S), and therefore the kernel configuration that optimizes detection power cannot be determined from tSNR considerations alone. However, several kernel configurations provided a favorable balance between boosting tSNR and ΔS/S, and allowed a 1.1-mm isotropic fMRI acquisition to have higher performance after smoothing (in terms of both detection power and spatial resolution) compared to an unsmoothed 3.0-mm isotropic fMRI acquisition. Overall, the results of this study support the strategy of acquiring voxels smaller than the cortical thickness, even for studies not requiring high spatial resolution, and smoothing them down within the cortical ribbon with a kernel of an appropriate shape to achieve the best performance—thus decoupling the choice of fMRI voxel size from the spatial resolution requirements of the particular study. The improvement of this new intracortical smoothing approach over conventional surface-based smoothing is expected to be modest for conventional resolutions, however the improvement is expected to increase with higher resolutions. This framework can also be applied to anatomically-informed intracortical smoothing of higher-resolution data (e.g. along columns and layers) in studies with prior information about the spatial structure of activation.
机译:MRI采集技术的不断改进使功能性MRI(fMRI)的等方体素尺寸小至1 mm,甚至更小。尽管许多常规功能磁共振成像研究试图研究皮质激活的区域模式,而传统的3mm及更大的体素可提供足够的空间分辨率,但较小的体素可帮助避免相邻白质(WM)和脑脊液(CSF)的污染,从而增加功能磁共振成像的特异性,以信号通知灰质内的变化。不幸的是,在高分辨率采集中,时间信噪比(tSNR)(fMRI灵敏度的度量)降低了,这抵消了小体素的好处。在这里,我们介绍了一个框架,该框架结合了在7特斯拉场强下获得的各向同性的小型fMRI体素与新颖的解剖学信息,表面网格导航的空间平滑功能,与传统体素尺寸相比,可以提供更高的检测能力和更高的分辨率。我们的平滑方法使用了一系列皮质内表面网格,并允许使用各种形状和大小的内核,包括适应并跟踪皮质折叠模式的弯曲3D内核。我们的目标是限制对皮质灰质带的平滑处理,并避免CSF造成的噪声污染和WM通过部分体积效应造成的信号稀释。我们发现,使tSNR最大化的皮层内内核不能使信号变化百分比(ΔS/ S)最大化,因此优化检测能力的内核配置不能仅从tSNR考虑因素来确定。但是,几种内核配置在提升tSNR和ΔS/ S之间提供了良好的平衡,并且与不平滑的3.0 mm相比,平滑后的1.1 mm各向同性fMRI采集(在检测能力和空间分辨率方面)具有更高的性能。各向同性fMRI采集。总体而言,这项研究的结果支持以下策略:即使对于不需要高空间分辨率的研究,也要获取小于皮质厚度的体素,并使用具有适当形状的核将其平滑到皮质带状区域中以达到最佳性能,因此将fMRI体素大小的选择与特定研究的空间分辨率要求脱钩。对于常规分辨率,这种新的皮质内平滑方法相对于常规的基于表面的平滑方法的改进预计是适度的,但是,随着分辨率的提高,该改进预计会增加。在具有关于激活的空间结构的先验信息的研究中,该框架还可以应用于高分辨率数据(例如沿列和层)的解剖学信息的皮质内平滑。

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