McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, QC, Canada.
Int J Comput Assist Radiol Surg. 2012 Jan;7(1):125-36. doi: 10.1007/s11548-011-0620-2. Epub 2011 Jun 2.
We present a new technique for registering magnetic resonance (MR) and ultrasound images in the context of neurosurgery. It involves generating a pseudo-ultrasound (pseudo-US) from a segmented MR image and uses cross-correlation as the cost function to register the pseudo-US to the real ultrasound data. The algorithm's performance is compared with that of a state-of-the-art technique that uses a median-filtered MR image to register to a Gaussian-blurred ultrasound using a normalized mutual information (NMI) objective function.
The two methods were tested on data from 15 patients with brain tumor, including low-and high-grade gliomas, in both first operations and reoperations. Two metrics were used to evaluate registration accuracy: (1) the mean distance between corresponding points, identified on both MR and ultrasound images by two experts, and (2) ratings based on visual comparison by one neurosurgeon.
The mean residual distance of the pseudo-US technique, 2.97 mm, is significantly more accurate (p = .0011) than that of the NMI approach, 4.86 mm. The visual assessment shows that only 4 of the 15 cases had a satisfactory initial alignment based on homologous skin-point registration. There is a significant correlation between the quantitative distance measures and the qualitative ratings (rho = 0.785).
The results show that the pseudo-US rigid registration technique robustly improves the MRI-ultrasound alignment when compared with the initial alignment, even when applied to highly distorted brains and a large range of tumor sizes and appearances.
我们提出了一种新的神经外科磁共振(MR)和超声图像配准技术。它涉及从分割的 MR 图像生成伪超声(pseudo-US),并使用互相关作为代价函数将伪-US 配准到真实的超声数据。该算法的性能与使用中值滤波的 MR 图像注册到高斯模糊超声的基于归一化互信息(NMI)目标函数的最新技术进行了比较。
该方法在 15 例脑肿瘤患者(包括低级别和高级别胶质瘤)的首次手术和再次手术数据上进行了测试。使用两种指标来评估配准精度:(1)两位专家在 MR 和超声图像上识别的对应点之间的平均距离,(2)一位神经外科医生基于视觉比较的评分。
伪-US 技术的平均残余距离为 2.97mm,明显比 NMI 方法的 4.86mm 更准确(p=0.0011)。视觉评估表明,仅 15 例中有 4 例基于同源皮肤点配准具有满意的初始配准。定量距离测量与定性评分之间存在显著相关性(rho=0.785)。
结果表明,与初始配准相比,伪-US 刚性配准技术可稳健地改善 MRI-超声配准,即使应用于高度扭曲的大脑和广泛的肿瘤大小和形态。