Hannequin P P, Mas J F
Centre d'Imagerie Nucléaire, Annecy, France.
J Nucl Med. 1998 Mar;39(3):555-62.
One of the major limitations of gamma cameras is their relatively poor energy resolution. The main practical consequence of this is that the detection of both scattered and unscattered photons in the photopeak energy window, affecting image contrast and resolution, makes the data inconsistent with the assumption of scatter-free projection data in reconstruction and attenuation correction algorithms. Here, we proposed a method to improve the effective energy resolution of scintigraphic acquisitions. This method is called photon energy recovery (PER).
Photon energy recovery is based on a spectral deconvolution analysis and uses iterative recurrent linear regressions. In practice, PER only required splitting the photopeak energy window into several subwindows and did not need list mode acquisitions. The method was fully automated. Photon energy recovery was quantitatively validated on 99mTc planar images using a Monte Carlo simulation and a real phantom and was illustrated by a bone study.
The Monte Carlo simulation demonstrated that convergence was reached within relatively few (10-15) iterations. Photon energy recovery led to a considerable quantitative improvement because the mean error between the photopeak energy window image and the true unscattered image was equal to 8.72 s.d. (the mean error between one image and the true image was the mean of the differences between the two images; the difference is expressed as several s.d., where s.d. was the square root of the true value), whereas the mean error between the 140-keV PER image and the true unscattered image was only equal to 2.70. Moreover, the true and PER spectra were highly correlated. The real phantom data pointed out that the counts in the 140-keV PER image calculated from the images acquired "with scatter" were not very different from the true counts given by the "scatter-free" reference image. Planar pelvic bone scintigraphy demonstrated the advantages of PER because contrast increased when only unscattered photons were selected.
Photon energy recovery is a stable and automated method that allows recovery of the correct value of the photon energy after a scintigraphic acquisition. Its ability to separate scattered from unscattered events has been quantitatively validated.
γ相机的主要局限性之一是其能量分辨率相对较差。这一情况的主要实际后果是,在光电峰能量窗口中同时检测到散射光子和未散射光子,会影响图像对比度和分辨率,使得数据与重建和衰减校正算法中无散射投影数据的假设不一致。在此,我们提出了一种提高闪烁扫描采集有效能量分辨率的方法。该方法称为光子能量恢复(PER)。
光子能量恢复基于光谱反卷积分析,并使用迭代递归线性回归。实际上,PER只需要将光电峰能量窗口划分为几个子窗口,不需要列表模式采集。该方法是完全自动化的。使用蒙特卡罗模拟和真实体模在99mTc平面图像上对光子能量恢复进行了定量验证,并通过一项骨骼研究进行了说明。
蒙特卡罗模拟表明,在相对较少(10 - 15)次迭代内即可达到收敛。光子能量恢复带来了显著的定量改善,因为光电峰能量窗口图像与真实未散射图像之间的平均误差等于8.72标准差(一张图像与真实图像之间的平均误差是两张图像之间差异的平均值;差异以几个标准差表示,其中标准差是真实值的平方根),而140keV PER图像与真实未散射图像之间的平均误差仅为2.70。此外,真实光谱与PER光谱高度相关。真实体模数据指出,从“有散射”采集的图像计算出的140keV PER图像中的计数与“无散射”参考图像给出的真实计数没有太大差异。平面骨盆骨闪烁扫描证明了PER的优势,因为仅选择未散射光子时对比度会增加。
光子能量恢复是一种稳定且自动化的方法,可在闪烁扫描采集后恢复光子能量的正确值。其区分散射事件和未散射事件的能力已得到定量验证。