Rahman Md Ashequr, Li Zekun, Yu Zitong, Laforest Richard, Thorek Daniel L J, Jha Abhinav K
Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, USA.
Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, USA.
EJNMMI Phys. 2023 Jun 22;10(1):40. doi: 10.1186/s40658-023-00558-3.
Single-photon emission computed tomography (SPECT) provides a mechanism to perform absorbed-dose quantification tasks for [Formula: see text]-particle radiopharmaceutical therapies ([Formula: see text]-RPTs). However, quantitative SPECT for [Formula: see text]-RPT is challenging due to the low number of detected counts, the complex emission spectrum, and other image-degrading artifacts. Towards addressing these challenges, we propose a low-count quantitative SPECT reconstruction method for isotopes with multiple emission peaks.
Given the low-count setting, it is important that the reconstruction method extracts the maximal possible information from each detected photon. Processing data over multiple energy windows and in list-mode (LM) format provide mechanisms to achieve that objective. Towards this goal, we propose a list-mode multi energy window (LM-MEW) ordered-subsets expectation-maximization-based SPECT reconstruction method that uses data from multiple energy windows in LM format and include the energy attribute of each detected photon. For computational efficiency, we developed a multi-GPU-based implementation of this method. The method was evaluated using 2-D SPECT simulation studies in a single-scatter setting conducted in the context of imaging [[Formula: see text]Ra]RaCl[Formula: see text], an FDA-approved RPT for metastatic prostate cancer.
The proposed method yielded improved performance on the task of estimating activity uptake within known regions of interest in comparison to approaches that use a single energy window or use binned data. The improved performance was observed in terms of both accuracy and precision and for different sizes of the region of interest.
Results of our studies show that the use of multiple energy windows and processing data in LM format with the proposed LM-MEW method led to improved quantification performance in low-count SPECT of isotopes with multiple emission peaks. These results motivate further development and validation of the LM-MEW method for such imaging applications, including for [Formula: see text]-RPT SPECT.
单光子发射计算机断层扫描（SPECT）为α粒子放射性药物治疗（α-RPT）执行吸收剂量定量任务提供了一种机制。然而，由于检测到的计数数量少、发射光谱复杂以及其他图像退化伪影，α-RPT的定量SPECT具有挑战性。为了应对这些挑战，我们提出了一种用于具有多个发射峰的同位素的低计数定量SPECT重建方法。
鉴于低计数设置，重建方法从每个检测到的光子中提取最大可能信息非常重要。在多个能量窗口上并以列表模式（LM）格式处理数据提供了实现该目标的机制。为此，我们提出了一种基于列表模式多能量窗口（LM-MEW）有序子集期望最大化的SPECT重建方法，该方法使用LM格式的多个能量窗口中的数据，并包含每个检测到的光子的能量属性。为了提高计算效率，我们开发了该方法的基于多GPU的实现。该方法在成像[²²³Ra]RaCl₂（一种用于转移性前列腺癌的FDA批准的RPT）的背景下在单散射设置中使用二维SPECT模拟研究进行了评估。
与使用单个能量窗口或使用分箱数据的方法相比，所提出的方法在估计已知感兴趣区域内的活度摄取任务上产生了更好的性能。在准确性和精度方面以及对于不同大小的感兴趣区域都观察到了性能的提高。
我们的研究结果表明，使用多个能量窗口并以LM格式处理数据以及所提出的LM-MEW方法在具有多个发射峰的同位素的低计数SPECT中导致了更好的定量性能。这些结果促使进一步开发和验证LM-MEW方法用于此类成像应用，包括用于α-RPT SPECT。
