Software-based PET-MR image coregistration: combined PET-MRI for the rest of us!
Software-based PET-MR image coregistration: combined PET-MRI for the rest of us!
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DOI：
10.1007/s00247-016-3641-8
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发表时间：
2016-10-01
影响因子：
2.3
通讯作者：
Shekhar, Raj
中科院分区：
文献类型：
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作者：
Robertson, Matthew S.;Liu, Xinyang;Shekhar, Raj
随着混合正电子发射断层扫描/磁共振成像（PET/MRI）的引入，获得具有互补解剖和功能信息的多模态图像的新成像选项已变得可用。与混合PET/计算机断层扫描（CT）相比，混合PET/MRI能够提供上级解剖细节，同时消除与CT相关的辐射暴露。为了验证基于软件的PET/MRI图像配准方法，为PET/MRI硬件配准提供一种可行的替代方案，本文采用了一种全自动的、图形处理单元加速的三维变形图像配准技术来实现PET/MRI图像的配准（作为PET/CT采集）和17例患者的MR图像对（年龄范围：10个月-21岁，平均年龄：10岁），接受PET/CT和身体MRI检查（胸部、腹部或骨盆），在28天（平均：10.5天）间隔内进行。大多数病例的MRI数据包括单站增强后轴向T1加权图像。配准后，比较了82个感兴趣体积的共同配准PET（cPET）和原始PET中观察到的最大标准化摄取值（SUVmax）。此外，我们计算了目标配准误差作为图像配准质量的衡量标准，并评估了该算法在interexpert可变性背景下的性能。配准执行时间平均为97 +/- 45 s。cPET-MRI和PET/CT之间的总体相对SUVmax差异为7%。平均目标配准误差为10.7 +/- 6.6 mm，与MRI的8.0 mm（典型分辨率：0.66 mm x 0.66 mm x 8 mm）和PET的6.1 mm（典型分辨率：3.65 mm x 3.65 mm x 3.27 mm）的典型体素尺寸（对角线距离）相比，这是有利的。在标志识别的变化并没有表现出统计上的显着差异之间的算法和一个典型的expert.We提出了一个基于软件的解决方案，实现了混合PET/MRI扫描仪的许多好处，而实际上不需要一个。该方法被证明是准确的和潜在的临床有用的。
With the introduction of hybrid positron emission tomography/magnetic resonance imaging (PET/MRI), a new imaging option to acquire multimodality images with complementary anatomical and functional information has become available. Compared with hybrid PET/computed tomography (CT), hybrid PET/MRI is capable of providing superior anatomical detail while removing the radiation exposure associated with CT. The early adoption of hybrid PET/MRI, however, has been limited.To provide a viable alternative to the hybrid PET/MRI hardware by validating a software-based solution for PET-MR image coregistration.A fully automated, graphics processing unit-accelerated 3-D deformable image registration technique was used to align PET (acquired as PET/CT) and MR image pairs of 17 patients (age range: 10 months-21 years, mean: 10 years) who underwent PET/CT and body MRI (chest, abdomen or pelvis), which were performed within a 28-day (mean: 10.5 days) interval. MRI data for most of these cases included single-station post-contrast axial T1-weighted images. Following registration, maximum standardized uptake value (SUVmax) values observed in coregistered PET (cPET) and the original PET were compared for 82 volumes of interest. In addition, we calculated the target registration error as a measure of the quality of image coregistration, and evaluated the algorithm's performance in the context of interexpert variability.The coregistration execution time averaged 97 +/- 45 s. The overall relative SUVmax difference was 7% between cPET-MRI and PET/CT. The average target registration error was 10.7 +/- 6.6 mm, which compared favorably with the typical voxel size (diagonal distance) of 8.0 mm (typical resolution: 0.66 mm x 0.66 mm x 8 mm) for MRI and 6.1 mm (typical resolution: 3.65 mm x 3.65 mm x 3.27 mm) for PET. The variability in landmark identification did not show statistically significant differences between the algorithm and a typical expert.We have presented a software-based solution that achieves the many benefits of hybrid PET/MRI scanners without actually needing one. The method proved to be accurate and potentially clinically useful.