To summarize the distribution of glioma location within a patient population, registration of individual MR images to anatomical reference space is required. In this study, we quantified the accuracy of MR image registration to anatomical reference space with linear and non-linear transformations using estimated tumor targets of glioblastoma and lower-grade glioma, and anatomical landmarks at pre- and post-operative time-points using six commonly used registration packages (FSL, SPM5, DARTEL, ANTs, Elastix, and NiftyReg). Routine clinical pre- and post-operative, post-contrast T1-weighted images of 20 patients with glioblastoma and 20 with lower-grade glioma were collected. The 2009a Montreal Neurological Institute brain template was used as anatomical reference space. Tumors were manually segmented in the patient space and corresponding healthy tissue was delineated as a target volume in the anatomical reference space. Accuracy of the tumor alignment was quantified using the Dice score and the Hausdorff distance. To measure the accuracy of general brain alignment, anatomical landmarks were placed in patient and in anatomical reference space, and the landmark distance after registration was quantified. Lower-grade gliomas were registered more accurately than glioblastoma. Registration accuracy for pre- and post-operative MR images did not differ. SPM5 and DARTEL registered tumors most accurate, and FSL least accurate. Non-linear transformations resulted in more accurate general brain alignment than linear transformations, but tumor alignment was similar between linear and non-linear transformation. We conclude that linear transformation suffices to summarize glioma locations in anatomical reference space.

中文翻译：

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弥散性胶质瘤解剖参考空间的精确 MR 图像配准

为了总结患者群体中胶质瘤位置的分布，需要将单个 MR 图像配准到解剖参考空间。在这项研究中，我们使用胶质母细胞瘤和低级别胶质瘤的估计肿瘤靶标以及术前和术后时间点的解剖标志，通过线性和非线性变换量化了 MR 图像配准到解剖参考空间的准确性，使用六个常用的注册包（FSL、SPM5、DARTEL、ANTs、Elastix 和 NiftyReg）。收集了 20 名胶质母细胞瘤患者和 20 名低级别胶质瘤患者的常规临床术前和术后对比后 T1 加权图像。2009a 蒙特利尔神经学研究所大脑模板被用作解剖参考空间。在患者空间中手动分割肿瘤，并在解剖参考空间中将相应的健康组织描绘为目标体积。使用 Dice 评分和 Hausdorff 距离量化肿瘤对齐的准确性。为了测量一般大脑对齐的准确性，将解剖标志放置在患者和解剖参考空间中，并量化配准后的标志距离。低级别胶质瘤比胶质母细胞瘤更准确。术前和术后 MR 图像的配准精度没有差异。SPM5 和 DARTEL 记录肿瘤最准确，FSL 最不准确。非线性变换导致比线性变换更准确的一般大脑对齐，但线性变换和非线性变换之间的肿瘤对齐相似。