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基于快速蒙特卡罗的联合迭代重建用于同步99mTc/123I单光子发射计算机断层显像成像

Fast Monte Carlo based joint iterative reconstruction for simultaneous 99mTc/ 123I SPECT imaging.

作者信息

Ouyang Jinsong, El Fakhri Georges, Moore Stephen C

机构信息

Department of Radiology, Harvard Medical School and Brigham and Women's Hospital, Boston, Massachusetts 02115, USA.

出版信息

Med Phys. 2007 Aug;34(8):3263-72. doi: 10.1118/1.2756601.

Abstract

Simultaneous 99mTC/ 123I SPECT allows the assessment of two physiological functions under identical conditions. The separation of these radionuclides is difficult, however, because their energies are close. Most energy-window-based scatter correction methods do not fully model either physical factors or patient-specific activity and attenuation distributions. We have developed a fast Monte Carlo (MC) simulation-based multiple-radionuclide and multiple-energy joint ordered-subset expectation-maximization (JOSEM) iterative reconstruction algorithm, MC-JOSEM. MC-JOSEM simultaneously corrects for scatter and cross talk as well as detector response within the reconstruction algorithm. We evaluated MC-JOSEM for simultaneous brain profusion (99mTc-HMPAO) and neurotransmission (123I-altropane) SPECT. MC simulations of 99mTc and 123I studies were generated separately and then combined to mimic simultaneous 99mTc/ 123I SPECT. All the details of photon transport through the brain, the collimator, and detector, including Compton and coherent scatter, septal penetration, and backscatter from components behind the crystal, were modeled. We reconstructed images from simultaneous dual-radionuclide projections in three ways. First, we reconstructed the photopeak-energy-window projections (with an asymmetric energy window for 1231) using the standard ordered-subsets expectation-maximization algorithm (NSC-OSEM). Second, we used standard OSEM to reconstruct 99mTc photopeak-energy-window projections, while including an estimate of scatter from a Compton-scatter energy window (SC-OSEM). Third, we jointly reconstructed both 99mTc and 123I images using projection data associated with two photo-peak energy windows and an intermediate-energy window using MC-JOSEM. For 15 iterations of reconstruction, the bias and standard deviation of 99mTc activity estimates in several brain structures were calculated for NSC-OSEM, SC-OSEM, and MC-JOSEM, using images reconstructed from primary (unscattered) photons as a reference. Similar calculations were performed for 123I images for NSC-OSEM and MC-JOSEM. For 123I images, dopamine binding potential (BP) at equilibrium and its signal-to-noise ratio (SNR) were also calculated. Our results demonstrate that MC-JOSEM performs better than NSC- and SC-OSEM for quantitation tasks. After 15 iterations of reconstruction, the relative bias of 99mTc activity estimates in the thalamus, striata, white matter, and gray matter volumes from MC-JOSEM ranged from -2.4% to 1.2%, while the same estimates for NSC-OSEM (SC-OSEM) ranged from 20.8% to 103.6% (7.2% to 41.9%). Similarly, the relative bias of 123I activity estimates from 15 iterations of MC-JOSEM in the striata and background ranged from -1.4% to 2.9%, while the same estimates for NSC-OSEM ranged from 1.6% to 10.0%. The relative standard deviation of 99mTc activity estimates from MC-JOSEM ranged from 1.1% to 4.8% versus 1.2% to 6.7% (1.2% to 5.9%) for NSC-OSEM (SC-OSEM). The relative standard deviation of 123I activity estimates using MC-JOSEM ranged from 1.1% to 1.9% versus 1.5% to 2.7% for NSC-OSEM. Using the 123I dopamine BP obtained from the reconstruction produced by primary photons as a reference, the result for MC-JOSEM was 50.5% closer to the reference than that of NSC-OSEM after 15 iterations. The SNR for dopamine BP was 23.6 for MC-JOSEM as compared to 18.3 for NSC-OSEM.

摘要

同时进行的99m锝/123碘单光子发射计算机断层显像(SPECT)可在相同条件下评估两种生理功能。然而,由于这些放射性核素的能量相近,分离它们很困难。大多数基于能量窗的散射校正方法都不能完全模拟物理因素或患者特异性的活度及衰减分布。我们开发了一种基于快速蒙特卡罗(MC)模拟的多放射性核素和多能量联合有序子集期望最大化(JOSEM)迭代重建算法,即MC-JOSEM。MC-JOSEM在重建算法中同时校正散射、串扰以及探测器响应。我们评估了MC-JOSEM用于同时进行脑灌注(99m锝-六甲基丙烯胺肟)和神经传递(123碘-阿替派)SPECT的情况。分别生成99m锝和123碘研究的MC模拟,然后将其合并以模拟同时进行的99m锝/123碘SPECT。对光子通过大脑、准直器和探测器的所有细节进行了建模,包括康普顿散射和相干散射、隔板穿透以及晶体后方部件的反向散射。我们用三种方法从同时的双放射性核素投影重建图像。首先,我们使用标准有序子集期望最大化算法(NSC-OSEM)重建光电峰能量窗投影(对123碘使用不对称能量窗)。其次,我们用标准OSEM重建99m锝光电峰能量窗投影,同时包括来自康普顿散射能量窗的散射估计(SC-OSEM)。第三,我们使用与两个光电峰能量窗和一个中间能量窗相关的投影数据,通过MC-JOSEM联合重建99m锝和123碘图像。对于15次重建迭代,以从初级(无散射)光子重建的图像为参考,计算了NSC-OSEM、SC-OSEM和MC-JOSEM在几个脑结构中99m锝活度估计的偏差和标准差。对NSC-OSEM和MC-JOSEM的123碘图像进行了类似计算。对于123碘图像, 还计算了平衡时的多巴胺结合势(BP)及其信噪比(SNR)。我们的结果表明,在定量任务中MC-JOSEM比NSC-OSEM和SC-OSEM表现更好。重建15次迭代后,MC-JOSEM在丘脑、纹状体、白质和灰质体积中99m锝活度估计的相对偏差范围为-2.4%至1.2%,而NSC-OSEM(SC-OSEM)的相同估计范围为20.8%至103.6%(7.2%至41.9%)。同样,MC-JOSEM 15次迭代后在纹状体和背景中123碘活度估计的相对偏差范围为-1.4%至2.9%,而NSC-OSEM的相同估计范围为1.6%至10.0%。MC-JOSEM的99m锝活度估计的相对标准差范围为1.1%至4.8%,而NSC-OSEM为1.2%至6.7%(SC-OSEM为1.2%至5.9%)。使用MC-JOSEM重建得到的123碘多巴胺BP作为参考,15次迭代后MC-JOSEM的结果比NSC-OSEM的结果更接近参考值50.5%。MC-JOSEM的多巴胺BP的SNR为23.6,而NSC-OSEM为18.3。

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