A Template and Probabilistic Atlas of the Human Sensorimotor Tracts using Diffusion MRI
A Template and Probabilistic Atlas of the Human Sensorimotor Tracts using Diffusion MRI
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DOI：
10.1093/cercor/bhx066
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发表时间：
2018-05-01
期刊：
影响因子：
3.7
通讯作者：
Coombes, Stephen A.
中科院分区：
文献类型：
--
作者：
Archer, Derek B.;Vaillancourt, David E.;Coombes, Stephen A.
本研究的目的是建立一个高分辨率的感觉运动区域束模板（smmatt），该模板基于初级运动皮质、背侧运动前皮质、腹侧运动前皮质、辅助运动区（SMA）、前辅助运动区（preSMA）和初级体感皮质6个皮质区域进行皮质束分割。使用目前可用的最高分辨率数据，对100名受试者进行了个体概率示踪分析。使用一种新颖的算法对束造影结果进行细化，以客观地确定切片水平阈值，从而最大限度地减少束之间的重叠，同时保持束的体积。与猴子和啮齿动物的追踪研究一致，我们的观察结果表明，皮层地形通常通过内囊保存下来，preSMA束保持在最前面，初级体感束保持在最后面。我们将我们的结果结合到一个免费的白质模板中，名为smat。我们还提供了一个概率smat，量化了束之间重叠的程度。最后，我们评估了smat在另一个独立数据集和中风后个体水平上的运作方式。smat和概率smat提供了新的工具，以以前无法获得的空间分辨率分割和标记感觉运动束。
The purpose of this study was to develop a high-resolution sensorimotor area tract template (SMATT) which segments corticofugal tracts based on 6 cortical regions in primary motor cortex, dorsal premotor cortex, ventral premotor cortex, supplementary motor area (SMA), pre-supplementary motor area (preSMA), and primary somatosensory cortex using diffusion tensor imaging. Individual probabilistic tractography analyses were conducted in 100 subjects using the highest resolution data currently available. Tractography results were refined using a novel algorithm to objectively determine slice level thresholds that best minimized overlap between tracts while preserving tract volume. Consistent with tracing studies in monkey and rodent, our observations show that cortical topography is generally preserved through the internal capsule, with the preSMA tract remaining most anterior and the primary somatosensory tract remaining most posterior. We combine our results into a freely available white matter template named the SMATT. We also provide a probabilistic SMATT that quantifies the extent of overlap between tracts. Finally, we assess how the SMATT operates at the individual subject level in another independent data set, and in an individual after stroke. The SMATT and probabilistic SMATT provide new tools that segment and label sensorimotor tracts at a spatial resolution not previously available.