Moore S C, Kijewski M F, Müller S P, Rybicki F, Zimmerman R E
Department of Radiology, Harvard Medial School, Brigham and Women's Hospital, Boston, Massachusetts 02115, USA.
Med Phys. 2001 Feb;28(2):278-87. doi: 10.1118/1.1344201.
Three algorithms for scatter compensation in Tc-99m brain single-photon emission computed tomography (SPECT) were optimized and compared on the basis of the accuracy and precision with which lesion and background activity could be simultaneously estimated. These performance metrics are directly related to the clinically important tasks of activity quantitation and lesion detection, in contrast to measures based solely on the fidelity of image pixel values. The scatter compensation algorithms were (a) the Compton-window (CW) method with a 20% photopeak window, a 92-126 keV scatter window, and an optimized "k-factor," (b) the triple-energy window (TEW) method, with optimized widths of the photopeak window and the abutting scatter window, and (c) a general spectral (GS) method using seventeen 4 keV windows with optimized energy weights. Each method was optimized by minimizing the sum of the mean-squared errors (MSE) of the estimates of lesion and background activity concentrations. The accuracy and precision of activity estimates were then determined for lesions of different size, location, and contrast, as well as for a more complex Bayesian estimation task in which lesion size was also estimated. For the TEW and GS methods, parameters optimized for the estimation task differed significantly from those optimized for global normalized pixel MSE. For optimal estimation, the CW bias of activity estimates was larger and varied more (-2% to 22%) with lesion location and size than that of the other methods. The magnitude of the TEW bias was less than 7% across most conditions, although its precision was worse than that of CW estimates. The GS method performed best, with bias generally less than 4% and the lowest variance; its root-mean square (rms) estimation error was within a few percent of that achievable from primary photons alone. For brain SPECT, estimation performance with an optimized, energy-based, subtractive correction may approach that of an ideal scatter-rejection procedure.
在99m锝脑单光子发射计算机断层扫描（SPECT）中，基于能够同时估计病变和本底活性的准确性和精密度，对三种散射补偿算法进行了优化和比较。与仅基于图像像素值保真度的测量方法不同，这些性能指标与活性定量和病变检测等临床重要任务直接相关。散射补偿算法包括：（a）康普顿窗（CW）法，采用20%的光电峰窗、92 - 126 keV散射窗和优化的“k因子”；（b）三能量窗（TEW）法，优化了光电峰窗和相邻散射窗的宽度；（c）通用谱（GS）法，使用17个4 keV窗并优化了能量权重。每种方法通过最小化病变和本底活性浓度估计值的均方误差（MSE）之和进行优化。然后针对不同大小、位置和对比度的病变，以及在还估计病变大小的更复杂贝叶斯估计任务中，确定活性估计的准确性和精密度。对于TEW和GS方法，针对估计任务优化的参数与针对全局归一化像素MSE优化的参数有显著差异。为实现最佳估计，活性估计的CW偏差比其他方法更大，并且随病变位置和大小变化更多（-2%至22%）。在大多数情况下，TEW偏差的幅度小于7%，尽管其精密度比CW估计差。GS方法表现最佳，偏差通常小于4%且方差最低；其均方根（rms）估计误差仅比仅由初级光子获得的误差高几个百分点。对于脑SPECT，采用优化的基于能量的减法校正的估计性能可能接近理想的散射去除程序。
