IRCCS SDN, Naples, Italy.
J Healthc Eng. 2017;2017:2634389. doi: 10.1155/2017/2634389. Epub 2017 Jul 18.
Coregistration of multimodal diagnostic images is crucial for qualitative and quantitative multiparametric analysis. While retrospective coregistration is computationally intense and could be inaccurate, hybrid PET/MR scanners allow acquiring implicitly coregistered images. Aim of this study is to assess the performance of state-of-the-art coregistration methods applied to PET and MR acquired as single modalities, comparing the results with the implicitly coregistration of a hybrid PET/MR, in complex anatomical regions such as head/neck (HN). A dataset consisting of PET/CT and PET/MR subsequently acquired in twenty-three patients was considered: performance of rigid (RR) and deformable (DR) registration obtained by a commercial software and an open-source registration package was evaluated. Registration accuracy was qualitatively assessed in terms of visual alignment of anatomical structures and qualitatively measured by the Dice scores computed on segmented tumors in PET and MRI. The resulting scores highlighted that hybrid PET/MR showed higher registration accuracy than retrospectively coregistered images, because of an overall misalignment after RR, unrealistic deformations and volume variations after DR. DR revealed superior performance compared to RR due to complex nonrigid movements of HN district. Moreover, simultaneous PET/MR offers unique datasets serving as ground truth for the improvement and validation of coregistration algorithms, if acquired with PET/CT.
多模态诊断图像的配准对于定性和定量的多参数分析至关重要。虽然回顾性配准计算量很大,并且可能不准确,但混合 PET/MR 扫描仪允许获取隐含配准的图像。本研究的目的是评估应用于单模态采集的 PET 和 MR 的最新配准方法的性能,将结果与混合 PET/MR 的隐含配准进行比较,在头颈部(HN)等复杂解剖区域进行比较。考虑了包含 23 名患者的 PET/CT 和 PET/MR 随后采集的数据集:通过商业软件和开源注册包评估了刚性(RR)和变形(DR)配准的性能。通过在 PET 和 MRI 上分割的肿瘤计算 Dice 分数来定性评估注册准确性。所得分数表明,由于 RR 后整体错位、DR 后不现实的变形和体积变化,混合 PET/MR 显示出比回顾性配准图像更高的配准准确性。由于 HN 区的复杂非刚性运动,DR 比 RR 表现更好。此外,如果与 PET/CT 一起采集,同时的 PET/MR 提供了独特的数据集,可作为配准算法改进和验证的基准。