Pas Kristofor E, Saleem Kadharbatcha S, Basser Peter J, Avram Alexandru V
National Institutes of Health, Bethesda, MD, United States.
Biomedical Engineering, University of Virginia, Charlottesville, VA, United States.
Imaging Neurosci (Camb). 2024 Dec 20;2. doi: 10.1162/imag_a_00393. eCollection 2024.
We assess the potential of detecting cortical laminar patterns and areal borders by directly clustering voxel values of microstructural parameters derived from high-resolution mean apparent propagator (MAP) magnetic resonance imaging (MRI), as an alternative to conventional template-warping-based cortical parcellation methods. We acquired MAP-MRI data with 200 m resolution in a fixed macaque monkey brain. To improve the sensitivity to cortical layers, we processed the data with a local anisotropic Gaussian filter determined voxel-wise by the plane tangent to the cortical surface. We directly clustered all cortical voxels using only the MAP-derived microstructural imaging biomarkers, with no information regarding their relative spatial location or dominant diffusion orientations. MAP-based 3D cytoarchitectonic segmentation revealed laminar patterns similar to those observed in the corresponding histological images. Moreover, transition regions between these laminar patterns agreed more accurately with histology than the borders between cortical areas estimated using conventional atlas/template-warping cortical parcellation. By cross-tabulating all cortical labels in the atlas- and MAP-based segmentations, we automatically matched the corresponding MAP-derived clusters (i.e., cytoarchitectonic domains) across the left and right hemispheres. Our results demonstrate that high-resolution MAP-MRI biomarkers can effectively delineate three-dimensional cortical cytoarchitectonic domains in single individuals. Their intrinsic tissue microstructural contrasts enable the construction of whole-brain mesoscopic cortical atlases.
我们评估了通过直接对源自高分辨率平均表观传播子（MAP）磁共振成像（MRI）的微观结构参数的体素值进行聚类来检测皮质分层模式和区域边界的潜力，以此作为传统基于模板变形的皮质分区方法的替代方案。我们在固定的猕猴大脑中获取了分辨率为200μm的MAP-MRI数据。为了提高对皮质层的敏感性，我们使用由与皮质表面相切的平面逐体素确定的局部各向异性高斯滤波器对数据进行处理。我们仅使用源自MAP的微观结构成像生物标志物对所有皮质体素进行直接聚类，而不考虑它们的相对空间位置或主要扩散方向。基于MAP的三维细胞构筑分割显示出与在相应组织学图像中观察到的分层模式相似的模式。此外，这些分层模式之间的过渡区域与组织学的一致性比使用传统图谱/模板变形皮质分区估计的皮质区域之间的边界更准确。通过交叉列表对比基于图谱和基于MAP的分割中的所有皮质标签，我们自动匹配了左右半球中相应的源自MAP的聚类（即细胞构筑域）。我们的结果表明，高分辨率MAP-MRI生物标志物可以有效地在单一个体中描绘三维皮质细胞构筑域。它们固有的组织微观结构对比度能够构建全脑介观皮质图谱。
