Anderson Robert J, Long Christopher M, Calabrese Evan D, Robertson Scott H, Johnson G Allan, Cofer Gary P, O'Brien Richard J, Badea Alexandra
Department of Radiology, Duke University, Durham, CA, United States.
Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, United States.
Front Phys. 2020 Apr;8. doi: 10.3389/fphy.2020.00088. Epub 2020 Apr 21.
Network approaches provide sensitive biomarkers for neurological conditions, such as Alzheimer's disease (AD). Mouse models can help advance our understanding of underlying pathologies, by dissecting vulnerable circuits. While the mouse brain contains less white matter compared to the human brain, axonal diameters compare relatively well (e.g., ~0.6 μm in the mouse and ~0.65-1.05 μm in the human corpus callosum). This makes the mouse an attractive test bed for novel diffusion models and imaging protocols. Remaining questions on the accuracy and uncertainty of connectomes have prompted us to evaluate diffusion imaging protocols with various spatial and angular resolutions. We have derived structural connectomes by extracting gradient subsets from a high-spatial, high-angular resolution diffusion acquisition (120 directions, 43-μm-size voxels). We have simulated protocols with 12, 15, 20, 30, 45, 60, 80, 100, and 120 angles and at 43, 86, or 172-μm voxel sizes. The rotational stability of these schemes increased with angular resolution. The minimum condition number was achieved for 120 directions, followed by 60 and 45 directions. The percentage of voxels containing one dyad was exceeded by those with two dyads after 45 directions, and for the highest spatial resolution protocols. For the 86- or 172-μm resolutions, these ratios converged toward 55% for one and 39% for two dyads, respectively, with <7% from voxels with three dyads. Tractography errors, estimated through dyad dispersion, decreased most with angular resolution. Spatial resolution effects became noticeable at 172 μm. Smaller tracts, e.g., the fornix, were affected more than larger ones, e.g., the fimbria. We observed an inflection point for 45 directions, and an asymptotic behavior after 60 directions, corresponding to similar projection density maps. Spatially downsampling to 86 μm, while maintaining the angular resolution, achieved a subgraph similarity of 96% relative to the reference. Using 60 directions with 86- or 172-μm voxels resulted in 94% similarity. Node similarity metrics indicated that major white matter tracts were more robust to downsampling relative to cortical regions. Our study provides guidelines for new protocols in mouse models of neurological conditions, so as to achieve similar connectomes, while increasing efficiency.
网络方法为神经疾病（如阿尔茨海默病（AD））提供了敏感的生物标志物。小鼠模型有助于通过剖析易损神经回路来推进我们对潜在病理的理解。虽然与人类大脑相比，小鼠大脑中的白质较少，但轴突直径相对比较接近（例如，小鼠胼胝体中的轴突直径约为0.6μm，人类胼胝体中的轴突直径约为0.65 - 1.05μm）。这使得小鼠成为新型扩散模型和成像方案的一个有吸引力的测试平台。关于连接组的准确性和不确定性的遗留问题促使我们评估具有各种空间和角度分辨率的扩散成像方案。我们通过从高空间、高角度分辨率扩散采集（120个方向，43μm大小的体素）中提取梯度子集来推导结构连接组。我们模拟了具有12、15、20、30、45、60、80、100和120个角度以及43、86或172μm体素大小的方案。这些方案的旋转稳定性随着角度分辨率的提高而增加。在120个方向时达到最小条件数，其次是60个和45个方向。在45个方向之后以及对于最高空间分辨率方案，包含两个二元组的体素百分比超过了包含一个二元组的体素百分比。对于86μm或172μm分辨率，这些比率分别趋向于一个二元组的55%和两个二元组的39%，来自具有三个二元组的体素的比率小于7%。通过二元组离散度估计的纤维束追踪误差随着角度分辨率的提高而下降最多。空间分辨率的影响在172μm时变得明显。较小的纤维束，例如穹窿，比较大的纤维束，例如伞，受到的影响更大。我们观察到45个方向时有一个拐点，60个方向之后有渐近行为，这与相似的投影密度图相对应。在保持角度分辨率的同时将空间下采样到86μm，相对于参考实现了96%的子图相似度。使用60个方向和86μm或172μm体素时相似度为94%。节点相似度指标表明，相对于皮质区域，主要的白质纤维束对下采样更具鲁棒性。我们的研究为神经疾病小鼠模型中的新方案提供了指导方针，以便在提高效率的同时实现相似的连接组。
