Huang S C, Mahoney D K, Phelps M E
J Comput Assist Tomogr. 1987 Mar-Apr;11(2):314-25.
Functional images used in positron emission tomography (PET) have the advantage of presenting simultaneously the anatomical and functional information in cross-sectional body slices. However, the nonlinearity in parameter estimation, when combined with the finite image resolution, can cause systematic errors or biases in the estimated functional parameters. The effect of this error on blood flow images, which are commonly used in PET, is investigated in this study. Computer-simulated brain and heart phantoms of realistic configurations are used to examine the effect of various factors, such as imaging resolution, estimation nonlinearity, and structure configuration. The nonlinearity characteristics of six commonly used blood flow estimation techniques are simulated. Results show that structure boundaries on parametric images between tissues of different blood flows do not usually coincide with the true anatomical boundaries and would thus cause an apparent change in the cross-sectional size of the structures. The regional blood flow values as obtained from the blood flow images are usually lower than the true values. The severity of these effects is dependent on the characteristics of the flow estimation technique, the image resolution, and the size and shape of the structure. Although image resolution is a major factor in causing errors in the parametric images, its improvement, within the range examined in the present study [from 1.5 to 0.5 cm full width at half maximum (FWHM)], is not found to reduce drastically the underestimation of blood flow in brain phantom. The effect on boundary shift, however, is found to be in proportion to the FWHM of image resolution. Implications of these effects on generation, interpretation, and comparison of parametric/functional images are discussed.
正电子发射断层扫描(PET)中使用的功能图像具有在横断面身体切片中同时呈现解剖学和功能信息的优势。然而,参数估计中的非线性与有限的图像分辨率相结合时,会在估计的功能参数中导致系统误差或偏差。本研究调查了这种误差对PET中常用的血流图像的影响。使用具有实际配置的计算机模拟脑和心脏体模来检查各种因素的影响,如成像分辨率、估计非线性和结构配置。模拟了六种常用血流估计技术的非线性特征。结果表明,不同血流组织的参数图像上的结构边界通常与真实解剖边界不一致,从而会导致结构横断面尺寸出现明显变化。从血流图像获得的区域血流值通常低于真实值。这些影响的严重程度取决于血流估计技术的特征、图像分辨率以及结构的大小和形状。虽然图像分辨率是导致参数图像误差的主要因素,但在本研究考察的范围内[从半高宽(FWHM)1.5厘米提高到0.5厘米],未发现其改善能大幅减少脑体模中血流的低估情况。然而,发现对边界偏移的影响与图像分辨率的FWHM成正比。讨论了这些影响对参数/功能图像的生成、解释和比较的意义。