DeepHealth, Inc., Belmont, MA, United States.
Department of Pharmacology and Physiology, University of Rochester, Rochester, NY, United States; McLean Hospital, Belmont, MA, United States.
Neuroimage. 2021 Oct 1;239:118300. doi: 10.1016/j.neuroimage.2021.118300. Epub 2021 Jun 22.
Anatomic tracing is recognized as a critical source of knowledge on brain circuitry that can be used to assess the accuracy of diffusion MRI (dMRI) tractography. However, most prior studies that have performed such assessments have used dMRI and tracer data from different brains and/or have been limited in the scope of dMRI analysis methods allowed by the data. In this work, we perform a quantitative, voxel-wise comparison of dMRI tractography and anatomic tracing data in the same macaque brain. An ex vivo dMRI acquisition with high angular resolution and high maximum b-value allows us to compare a range of q-space sampling, orientation reconstruction, and tractography strategies. The availability of tracing in the same brain allows us to localize the sources of tractography errors and to identify axonal configurations that lead to such errors consistently, across dMRI acquisition and analysis strategies. We find that these common failure modes involve geometries such as branching or turning, which cannot be modeled well by crossing fibers. We also find that the default thresholds that are commonly used in tractography correspond to rather conservative, low-sensitivity operating points. While deterministic tractography tends to have higher sensitivity than probabilistic tractography in that very conservative threshold regime, the latter outperforms the former as the threshold is relaxed to avoid missing true anatomical connections. On the other hand, the q-space sampling scheme and maximum b-value have less of an impact on accuracy. Finally, using scans from a set of additional macaque brains, we show that there is enough inter-individual variability to warrant caution when dMRI and tracer data come from different animals, as is often the case in the tractography validation literature. Taken together, our results provide insights on the limitations of current tractography methods and on the critical role that anatomic tracing can play in identifying potential avenues for improvement.
解剖示踪被认为是大脑回路知识的重要来源,可以用于评估扩散磁共振成像(dMRI)轨迹的准确性。然而,大多数进行此类评估的先前研究都使用了来自不同大脑的 dMRI 和示踪剂数据,或者受到数据允许的 dMRI 分析方法范围的限制。在这项工作中,我们在同一猕猴大脑中对 dMRI 轨迹和解剖示踪数据进行了定量的体素比较。具有高角分辨率和高最大 b 值的离体 dMRI 采集使我们能够比较一系列 q 空间采样、方向重建和轨迹重建策略。在同一大脑中提供示踪,使我们能够定位轨迹重建误差的来源,并确定导致这些错误的轴突配置,这些错误在 dMRI 采集和分析策略中是一致的。我们发现这些常见的失效模式涉及分支或转弯等几何形状,而这些形状不能很好地通过交叉纤维来建模。我们还发现,在轨迹重建中常用的默认阈值对应于相当保守的低灵敏度工作点。虽然确定性轨迹重建在非常保守的阈值范围内比概率性轨迹重建具有更高的灵敏度,但在后一种情况下,随着阈值的放宽以避免错过真实的解剖连接,其性能优于前者。另一方面,q 空间采样方案和最大 b 值对准确性的影响较小。最后,使用来自一组额外的猕猴大脑的扫描,我们表明,个体间的变异性足以引起警惕,当 dMRI 和示踪剂数据来自不同的动物时,就像在轨迹重建验证文献中经常出现的情况一样。总之,我们的研究结果提供了对当前轨迹重建方法的局限性的深入了解,并强调了解剖示踪在确定潜在改进途径方面的关键作用。
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