Data_Sheet_1_Accurate MR Image Registration to Anatomical Reference Space for Diffuse Glioma.docx

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.

为总结患者群体内胶质瘤（glioma）的分布特征，需将个体磁共振图像（MR images）配准至解剖参考空间（anatomical reference space）。本研究以胶质母细胞瘤（glioblastoma）与低级别胶质瘤（lower-grade glioma）的预估肿瘤靶区、术前及术后时间点的解剖标志点为参照，采用6种常用配准工具包（FSL、SPM5、DARTEL、ANTs、Elastix及NiftyReg），量化了线性与非线性变换下的磁共振图像配准精度。本研究收集了20例胶质母细胞瘤患者与20例低级别胶质瘤患者的常规临床术前、术后增强T1加权成像（post-contrast T1-weighted images）。以2009a版蒙特利尔神经研究所脑模板（2009a Montreal Neurological Institute brain template）作为解剖参考空间。研究人员在患者图像空间中手动分割肿瘤，并在解剖参考空间中勾勒出对应健康组织作为靶体积。采用戴斯系数（Dice score）与豪斯多夫距离（Hausdorff distance）量化肿瘤对齐精度。为评估全脑对齐精度，研究人员在患者图像空间与解剖参考空间中设置解剖标志点，并量化配准后的标志点间距。低级别胶质瘤的配准精度高于胶质母细胞瘤。术前与术后磁共振图像的配准精度无显著差异。SPM5与DARTEL的肿瘤配准精度最高，FSL最低。非线性变换的全脑对齐精度优于线性变换，但肿瘤对齐精度在线性与非线性变换下无显著差异。本研究结论表明，线性变换即可满足在解剖参考空间中总结胶质瘤分布的需求。