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小动物 CT 的全自动内在呼吸和心脏门控

Fully automated intrinsic respiratory and cardiac gating for small animal CT.

机构信息

Department of Medical Physics in Radiology, German Cancer Research Center, Heidelberg, Germany.

出版信息

Phys Med Biol. 2010 Apr 7;55(7):2069-85. doi: 10.1088/0031-9155/55/7/018. Epub 2010 Mar 19.

Abstract

A fully automated, intrinsic gating algorithm for small animal cone-beam CT is described and evaluated. A parameter representing the organ motion, derived from the raw projection images, is used for both cardiac and respiratory gating. The proposed algorithm makes it possible to reconstruct motion-corrected still images as well as to generate four-dimensional (4D) datasets representing the cardiac and pulmonary anatomy of free-breathing animals without the use of electrocardiogram (ECG) or respiratory sensors. Variation analysis of projections from several rotations is used to place a region of interest (ROI) on the diaphragm. The ROI is cranially extended to include the heart. The centre of mass (COM) variation within this ROI, the filtered frequency response and the local maxima are used to derive a binary motion-gating parameter for phase-sensitive gated reconstruction. This algorithm was implemented on a flat-panel-based cone-beam CT scanner and evaluated using a moving phantom and animal scans (seven rats and eight mice). Volumes were determined using a semiautomatic segmentation. In all cases robust gating signals could be obtained. The maximum volume error in phantom studies was less than 6%. By utilizing extrinsic gating via externally placed cardiac and respiratory sensors, the functional parameters (e.g. cardiac ejection fraction) and image quality were equivalent to this current gold standard. This algorithm obviates the necessity of both gating hardware and user interaction. The simplicity of the proposed algorithm enables adoption in a wide range of small animal cone-beam CT scanners.

摘要

描述并评估了一种用于小动物锥形束 CT 的全自动内在门控算法。从原始投影图像中得出的代表器官运动的参数可用于心脏和呼吸门控。所提出的算法使得重建运动校正的静态图像以及生成代表自由呼吸动物的心脏和肺部解剖结构的四维(4D)数据集成为可能,而无需使用心电图(ECG)或呼吸传感器。对来自几个旋转的投影的变化分析用于在横膈膜上放置感兴趣区域(ROI)。ROI 向颅侧扩展以包括心脏。在此 ROI 内的质心(COM)变化、滤波频率响应和局部最大值用于为相敏门控重建导出二进制运动门控参数。该算法在基于平板的锥形束 CT 扫描仪上实现,并使用移动体模和动物扫描(七只大鼠和八只小鼠)进行了评估。使用半自动分割来确定体积。在所有情况下,都可以获得稳健的门控信号。在体模研究中,最大体积误差小于 6%。通过利用外部放置的心脏和呼吸传感器进行外部门控,功能参数(例如心脏射血分数)和图像质量与当前的金标准相当。该算法无需门控硬件和用户交互。所提出的算法的简单性使得它能够在广泛的小动物锥形束 CT 扫描仪中采用。

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