Waspe A C, Holdsworth D W, Lacefield J C, Fenster A
Imaging Research Laboratories, Robarts Research Institute, University of Western Ontario, London, ON.
Biomedical Engineering Graduate Program, University of Western Ontario, London, ON.
Med Phys. 2008 Jul;35(7Part2):3403. doi: 10.1118/1.2965931.
Preclinical research protocols often require the delivery of biological substances to specific targets in small animal disease models. To target biologically relevant locations in mice accurately, the needle positioning error needs to be < 200 μm. If targeting is inaccurate, experimental results can be inconclusive or misleading. We have developed a robotic manipulator that is capable of positioning a needle with a mean error < 100 μm. An apparatus and method were developed for integrating the needle-positioning robot with volumetric micro-computed tomography image guidance for interventions in small animals. Accurate image-to-robot registration is critical for integration as it enables targets identified in the image to be mapped to physical coordinates inside the animal. Registration is accomplished by injecting barium sulphate into needle tracks as the robot withdraws the needle from target points in a tissue-mimicking phantom. Registration accuracy is therefore affected by the positioning error of the robot and is assessed by measuring the point-to-line fiducial and target registration errors (FRE, TRE). Centroid points along cross-sectional slices of the track are determined using region growing segmentation followed by application of a center-of-mass algorithm. The centerline points are registered to needle trajectories in robot coordinates by applying an iterative closest point algorithm between points and lines. Implementing this procedure with four fiducial needle tracks produced a point-to-line FRE and TRE of 246 ± 58 μm and 194 ± 18 μm, respectively. The proposed registration technique produced a TRE < 200 μm, in the presence of robot positioning error, meeting design specification.
临床前研究方案通常要求在小动物疾病模型中将生物物质递送至特定靶点。为了在小鼠体内准确靶向生物学相关位置,针的定位误差需要<200μm。如果靶向不准确,实验结果可能不确定或产生误导。我们开发了一种机器人操纵器,其能够以平均误差<100μm定位针。还开发了一种装置和方法,用于将针定位机器人与体积微计算机断层扫描图像引导相结合,以用于小动物干预。准确的图像到机器人配准对于集成至关重要,因为它能使图像中识别的靶点映射到动物体内的物理坐标。配准是通过在机器人将针从组织模拟体模中的靶点拔出时向针道内注入硫酸钡来完成的。因此,配准精度受机器人定位误差的影响,并通过测量点到线基准和靶点配准误差(FRE、TRE)来评估。使用区域生长分割法,然后应用质心算法,确定沿针道横截面切片的质心点。通过在点和线之间应用迭代最近点算法,将中心线点配准到机器人坐标中的针轨迹。对四条基准针道实施此程序,产生的点到线FRE和TRE分别为246±58μm和194±18μm。在存在机器人定位误差的情况下,所提出的配准技术产生的TRE<200μm,符合设计规范。