Translational Medicine Branch, National Heart Lung and Blood Institute, National Institutes of Health, Bethesda, Maryland, USA.
Magn Reson Med. 2010 Apr;63(4):1070-9. doi: 10.1002/mrm.22307.
The accurate visualization of interventional devices is crucial for the safety and effectiveness of MRI-guided interventional procedures. In this paper, we introduce an improvement to the visualization of active devices. The key component is a fast, robust method ("CurveFind") that reconstructs the three-dimensional trajectory of the device from projection images in a fraction of a second. CurveFind is an iterative prediction-correction algorithm that acts on a product of orthogonal projection images. By varying step size and search direction, it is robust to signal inhomogeneities. At the touch of a key, the imaged slice is repositioned to contain the relevant section of the device ("SnapTo"), the curve of the device is plotted in a three-dimensional display, and the point on a target slice, which the device will intersect, is displayed. These features have been incorporated into a real-time MRI system. Experiments in vitro and in vivo (in a pig) have produced successful results using a variety of single- and multichannel devices designed to produce both spatially continuous and discrete signals. CurveFind is typically able to reconstruct the device curve, with an average error of approximately 2 mm, even in the case of complex geometries.
准确显示介入设备对于 MRI 引导介入手术的安全性和有效性至关重要。本文提出了一种改进的主动设备可视化方法。关键组件是一种快速、鲁棒的方法(“CurveFind”),可在几分之一秒内从投影图像中重建设备的三维轨迹。CurveFind 是一种迭代预测校正算法,作用于正交投影图像的乘积上。通过改变步长和搜索方向,它对信号非均匀性具有鲁棒性。只需点击一下键,即可重新定位成像切片以包含设备的相关部分(“SnapTo”),在三维显示器上绘制设备曲线,并显示设备将与之相交的目标切片上的点。这些功能已被集成到实时 MRI 系统中。在体外和体内(猪)进行的实验中,使用各种设计用于产生空间连续和离散信号的单通道和多通道设备取得了成功的结果。CurveFind 通常能够重建设备曲线,平均误差约为 2 毫米,即使在复杂的几何形状下也是如此。