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Improved dose-volume histogram estimates for radiopharmaceutical therapy by optimizing quantitative SPECT reconstruction parameters

机译:通过优化定量SPECT重建参数来改进放射药物治疗的剂量-体积直方图估计

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摘要

In radiopharmaceutical therapy, an understanding of the dose distribution in normal and target tissues is important for optimizing treatment. Three-dimensional (3D) dosimetry takes into account patient anatomy and the nonuniform uptake of radiopharmaceuticals in tissues. Dose-volume histograms (DVHs) provide a useful summary representation of the 3D dose distribution and have been widely used for external beam treatment planning. Reliable 3D dosimetry requires an accurate 3D radioactivity distribution as the input. However, activity distribution estimates from SPECT are corrupted by noise and partial volume effects (PVEs). In this work, we systematically investigated OS-EM based quantitative SPECT (QSPECT) image reconstruction in terms of its effect on DVHs estimates. A modified 3D NURBS-based Cardiac-Torso (NCAT) phantom that incorporated a non-uniform kidney model and clinically realistic organ activities and biokinetics was used. Projections were generated using a Monte Carlo (MC) simulation; noise effects were studied using 50 noise realizations with clinical count levels. Activity images were reconstructed using QSPECT with compensation for attenuation, scatter and collimator-detector response (CDR). Dose rate distributions were estimated by convolution of the activity image with a voxel S kernel. Cumulative DVHs were calculated from the phantom and QSPECT images and compared both qualitatively and quantitatively. We found that noise, PVEs, and ringing artifacts due to CDR compensation all degraded histogram estimates. Low-pass filtering and early termination of the iterative process were needed to reduce the effects of noise and ringing artifacts on DVHs, but resulted in increased degradations due to PVEs. Large objects with few features, such as the liver, had more accurate histogram estimates and required fewer iterations and more smoothing for optimal results. Smaller objects with fine details, such as the kidneys, required more iterations and less smoothing at early time points post-radiopharmaceutical administration but more smoothing and fewer iterations at later time points when the total organ activity was lower. The results of this study demonstrate the importance of using optimal reconstruction and regularization parameters. Optimal results were obtained with different parameters at each time point, but using a single set of parameters for all time points produced near-optimal dose-volume histograms.
机译:在放射性药物治疗中,了解正常组织和靶组织中的剂量分布对于优化治疗很重要。三维(3D)剂量测定法考虑了患者的解剖结构以及组织中放射性药物的不均匀吸收。剂量-体积直方图(DVH)提供了3D剂量分布的有用摘要表示,已被广泛用于外部束治疗计划。可靠的3D剂量测定需要准确的3D放射性分布作为输入。但是,SPECT的活动分布估计会受到噪声和部分体积效应(PVE)的破坏。在这项工作中,我们系统地研究了基于OS-EM的定量SPECT(QSPECT)图像重建对DVHs估计的影响。使用修改后的基于NURBS的3D心脏躯干(NCAT)幻像,该幻像结合了不均匀的肾脏模型以及临床上现实的器官活动和生物动力学。使用蒙特卡洛(MC)模拟生成投影;使用具有临床计数水平的50种噪音实现方法研究了噪音效果。使用QSPECT重建活动图像,并补偿衰减,散射和准直仪-检测器响应(CDR)。通过将活动图像与体素S核卷积来估计剂量率分布。从幻像和QSPECT图像计算出DVH的累积量,并进行定性和定量比较。我们发现,由于CDR补偿而导致的噪声,PVE和振铃伪影都会降低直方图估计值。需要低通滤波和迭代过程的早期终止以减少噪声和振铃伪影对DVH的影响,但由于PVE而导致的劣化增加。具有少量特征的大型对象(例如肝脏)的直方图估计值更加准确,并且需要更少的迭代次数和更多的平滑处理才能获得最佳结果。具有细微细节的较小物体(例如肾脏)在放射性药物给药后的早期时间点需要更多的迭代和较少的平滑,而在总器官活动较低的较晚的时间点需要更多的平滑和较少的迭代。这项研究的结果证明了使用最佳重构和正则化参数的重要性。在每个时间点使用不同的参数可获得最佳结果,但对于所有时间点使用一组参数即可产生接近最佳的剂量体积直方图。

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