Quantitative assessment of four-dimensional computed tomography image acquisition quality
Quantitative assessment of four-dimensional computed tomography image acquisition quality
复制标题
DOI：
10.1120/jacmp.v8i3.2362
复制
发表时间：
2007-01-01
影响因子：
2.1
通讯作者：
Pan, Tinsu
中科院分区：
文献类型：
--
作者：
Starkschall, George;Desai, Neil;Pan, Tinsu
本工作的目的是描述一系列测试的开发和验证，以评估四维(4D)计算机体层摄影(CT)成像的质量，因为它应用于放射治疗计划。使用商用呼吸运动体模和带有CT体模的可编程移动平台，我们在两台商用多层螺旋CT扫描仪上采集了4D CT数据集，这两台扫描仪使用不同的方法进行4D CT图像重建。当平台以各种设计来模拟呼吸的模式移动时，获得了数据集。模体中已知的插入物被画出轮廓，并产生统计数据以评估对放射治疗重要的属性--即，位相入库、形状、体积和CT数的准确性。对于重建图像然后入库的4D过程，相位入库精度变化高达5%，但对于在重建之前对投影入库的4D过程，相位入库精度没有变化。研究发现，两种方法的几何失真和体积误差的大小都很小。然而，垂直于重建横面方向的部分体积效应影响了体积精度。CT数字再现准确，但4D图像比静态CT图像显示更多的CT数字变化。这些特性的表征可以用来更好地了解和优化影响4D CT图像质量的各种参数。
The purpose of the present work was to describe the development and validation of a series of tests to assess the quality of four-dimensional ( 4D) computed-tomography ( CT) imaging as it is applied to radiation treatment planning. Using a commercial respiratory motion phantom and a programmable moving platform with a CT phantom, we acquired 4D CT datasets on two commercial multislice helical CT scanners that use different approaches to 4D CT image reconstruction. Datasets were obtained as the platform moved in various patterns designed to simulate breathing. Known inserts in the phantom were contoured, and statistics were generated to evaluate properties important to radiation therapy-namely, accuracy of phase-binning, shape, volume, and CT number. Phase-binning accuracy varied by as much as 5% for a 4D procedure in which images were reconstructed and then binned, but exhibited no variation for a 4D procedure in which projections were binned before reconstruction. The magnitude of geometric distortion was found to be small for both approaches, as was the magnitude of volume error. Partial-volume effects in the direction perpendicular to the transverse planes of reconstruction affected volume accuracy, however. Computed tomography numbers were reproduced accurately, but 4D images exhibited more variation in CT number than static CT images did. Characterization of such properties can be used to better understand and optimize the various parameters that affect 4D CT image quality.