Generation of Individualized Thalamus Target Maps by Using Statistical Shape Models and Thalamocortical Tractography
Generation of Individualized Thalamus Target Maps by Using Statistical Shape Models and Thalamocortical Tractography
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DOI：
10.3174/ajnr.a3140
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发表时间：
2012-12-01
影响因子：
3.5
通讯作者：
Szekely, G.
中科院分区：
文献类型：
--
作者：
Jakab, A.;Blanc, R.;Szekely, G.
背景与目的：丘脑的神经外科干预依赖于将立体定向坐标从地图集转移到患者的MR脑图像上。我们提出了一个原型应用程序，通过融合患者特异性丘脑几何信息和扩散张量束图来执行丘脑目标图个性化。材料和方法：之前，我们的工作组通过融合来自7个经组织学处理的丘脑的解剖信息开发了丘脑图谱。通过使用先前描述的程序，从40名受试者的DTI扫描中生成丘脑皮质连通性图，并将其映射到标准神经成像空间。这些数据被合并成一个统计形状模型，描述丘脑轮廓、核和连接标志的形态变异性。该模型用于将地图集变形为单个图像。死后磁共振成像扫描被用来量化核预测的准确性。结果：可靠的神经束图标记位于丘脑腹侧侧，体感觉连接与VPLa和VPLp核重合；和运动/前运动连接，与VLpv和VLa核。SSM方法对丘脑轮廓的预测准确率高于ACPC对齐方法（0.56 mm比1.24 mm； Dice重叠：0.87比0.7）；单个核：0.65 mm，粒：0.63 (SSM)；1.24 mm, Dice: 0.4 （ACPC）。结论：先前的研究已经将DTI应用于丘脑。在这个方向上更进一步，我们通过使用统计形状模型展示了一种混合方法，该模型有可能处理个体丘脑几何结构的主体间变化。
BACKGROUND AND PURPOSE: Neurosurgical interventions of the thalamus rely on transferring stereotactic coordinates from an atlas onto the patient's MR brain images. We propose a prototype application for performing thalamus target map individualization by fusing patient-specific thalamus geometric information and diffusion tensor tractography.MATERIALS AND METHODS: Previously, our workgroup developed a thalamus atlas by fusing anatomic information from 7 histologically processed thalami. Thalarnocortical connectivity maps were generated from DTI scans of 40 subjects by using a previously described procedure and were mapped to a standard neuroimaging space. These data were merged into a statistical shape model describing the morphologic variability of the thalamic outline, nuclei, and connectivity landmarks. This model was used to deform the atlas to individual images. Postmortem MR imaging scans were used to quantify the accuracy of nuclei predictions.RESULTS: Reliable tractography-based markers were located in the ventral lateral thalamus, with the somatosensory connections coinciding with the VPLa and VPLp nuclei; and motor/premotor connections, with the VLpv and VLa nuclei. Prediction accuracy of thalamus outlines was higher with the SSM approach than the ACPC alignment of data (0.56 mm versus 1.24; Dice overlap: 0.87 versus 0.7); for individual nuclei: 0.65 mm, Dice: 0.63 (SSM); 1.24 mm, Dice: 0.4 (ACPC).CONCLUSIONS: Previous studies have already applied DTI to the thalamus. As a further step in this direction, we demonstrate a hybrid approach by using statistical shape models, which have the potential to cope with intersubject variations in individual thalamus geometry.