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首页> 外文期刊>EJNMMI Physics >Fast GPU-based Monte Carlo code for SPECT/CT reconstructions generates improved 177 Lu images
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Fast GPU-based Monte Carlo code for SPECT/CT reconstructions generates improved 177 Lu images

机译：用于SPECT / CT重建的基于GPU的快速蒙特卡洛代码可生成177 Lu图像

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BackgroundFull Monte Carlo (MC)-based SPECT reconstructions have a strong potential for correcting for image degrading factors, but the reconstruction times are long. The objective of this study was to develop a highly parallel Monte Carlo code for fast, ordered subset expectation maximum (OSEM) reconstructions of SPECT/CT images. The MC code was written in the Compute Unified Device Architecture language for a computer with four graphics processing units (GPUs) (GeForce GTX Titan X, Nvidia, USA). This enabled simulations of parallel photon emissions from the voxels matrix (1283 or 2563). Each computed tomography (CT) number was converted to attenuation coefficients for photo absorption, coherent scattering, and incoherent scattering. For photon scattering, the deflection angle was determined by the differential scattering cross sections. An angular response function was developed and used to model the accepted angles for photon interaction with the crystal, and a detector scattering kernel was used for modeling the photon scattering in the detector. Predefined energy and spatial resolution kernels for the crystal were used. The MC code was implemented in the OSEM reconstruction of clinical and phantom 177Lu SPECT/CT images. The Jaszczak image quality phantom was used to evaluate the performance of the MC reconstruction in comparison with attenuated corrected (AC) OSEM reconstructions and attenuated corrected OSEM reconstructions with resolution recovery corrections (RRC). ResultThe performance of the MC code was 3200 million photons/s. The required number of photons emitted per voxel to obtain a sufficiently low noise level in the simulated image was 200 for a 1283 voxel matrix. With this number of emitted photons/voxel, the MC-based OSEM reconstruction with ten subsets was performed within 20?s/iteration. The images converged after around six iterations. Therefore, the reconstruction time was around 3?min. The activity recovery for the spheres in the Jaszczak phantom was clearly improved with MC-based OSEM reconstruction, e.g., the activity recovery was 88% for the largest sphere, while it was 66% for AC-OSEM and 79% for RRC-OSEM. ConclusionThe GPU-based MC code generated an MC-based SPECT/CT reconstruction within a few minutes, and reconstructed patient images of 177Lu-DOTATATE treatments revealed clearly improved resolution and contrast.
机译：背景基于全蒙特卡洛（MC）的SPECT重建具有校正图像退化因素的强大潜力，但重建时间长。这项研究的目的是为SPECT / CT图像的快速，有序的子集期望最大值（OSEM）重建开发高度并行的蒙特卡洛代码。 MC代码是用Compute Unified Device Architecture语言为一台具有四个图形处理单元（GPU）的计算机（GeForce GTX Titan X，Nvidia，美国）编写的。这样就可以模拟来自体素矩阵（128 3 或256 3 ）的平行光子发射。将每个计算机断层扫描（CT）数转换为用于光吸收，相干散射和非相干散射的衰减系数。对于光子散射，偏转角由微分散射截面确定。开发了角度响应函数，并将其用于对光子与晶体相互作用的可接受角度进行建模，并使用检测器散射核对检测器中的光子散射进行建模。使用了晶体的预定义能量和空间分辨率内核。 MC代码是在临床和幻影 177 Lu SPECT / CT图像的OSEM重建中实现的。 Jaszczak图像质量模型用于评估MC重建与衰减校正（AC）OSEM重建和衰减校正OSEM重建（具有分辨率恢复校正（RRC））的性能。结果MC代码的性能为32亿光子/秒。对于128 3 体素矩阵，要在模拟图像中获得足够低的噪声水平，每个体素发出的光子数量需要200个。利用这个数量的光子/体素，在20？s /迭代内执行了基于MC的OSEM重建，包含10个子集。大约经过六次迭代后，图像收敛。因此，重建时间约为3分钟。基于MC的OSEM重建明显改善了Jaszczak体模中球体的活性恢复，例如，最大球体的活性恢复率为88％，而AC-OSEM为66％，RRC-OSEM为79％。结论基于GPU的MC代码在几分钟内生成了基于MC的SPECT / CT重建，重建的 177 Lu-DOTATATE治疗患者图像显示分辨率和对比度明显改善。

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