Ultra-Low Count Quantitative SPECT for Alpha-Particle Therapies

项目概要： 本项目的总体目标是开发和全面验证超低计数定量SPECT 用于α粒子放射性药物治疗（α RPT）的ULC-QSPECT方法，包括首次人体试验 在骨转移性去势抵抗性前列腺癌患者中进行的试验。α RPT，例如基于 锕-225、钍-227和批准的镭-223同位素是一类新兴的细胞毒性疗法 用于患有播散性转移性疾病的患者，使用内部施用的α粒子发射剂。 尽管这些疗法具有巨大的潜力，但目前的αRPT方案并不个性化， 活动仅依赖于质量，可能导致非最佳治疗。为了应对这一挑战， 对测量同位素吸收的方法的关键未满足的需求，因此吸收的辐射剂量， 这些疗法，无论是在疾病部位还是在重要的剂量限制器官。SPECT提供了一个临床上可翻译的 机制来实现这一目标。然而，基于SPECT的量化的关键挑战是， α RPT中的给药活性比典型SPECT扫描低几个数量级，导致超低 检测计数水平。传统的量化方法重建同位素分布， 从重建图像估计区域摄取在这些低计数水平是错误的。解决 在这一问题上，我们提出了一个新的计算ULC-QSPECT框架，用于区域活动估计， α RPT。这些方法跳过重建步骤直接从投影数据量化区域摄取， 并且同时从所采集的投影数据中提取最大可能的信息。为此 目的，我们提出了新的方法，准确地模拟成像α RPT的物理，包括杂散- 辐射相关噪声，使用来自多能量窗口的数据， 量化，并以列表模式格式处理数据。我们广泛的初步数据显示， 方法导致几乎无偏的吸收和接近理论极限的方差。我们建议进一步 开发并严格评估这些方法。我们建议的评估包括多项研究， 具有不同检测器和不同准直器配置的扫描仪。我们的目标是临床翻译 这些方法。为了实现这一目标，我们建议临床评估这些方法测量活动 在患有去势抵抗性前列腺癌的男性中，[223 Ra] RaCl 2摄取部位的浓度。这些方法 将能够量化骨骼中疾病部位的活性以及通过肠道的清除。 该方法与患者直接相关，因为它实现了低管理活动的无创成像 治疗此外，该提议对改善药物的安全性和有效性具有实质性的潜在影响。 在这个快速发展的空间中的发展努力。此外，本提案中提出的方法将 加强SPECT在管理这些治疗患者中的临床效用。

PROJECT SUMMARY: The overall goal of this project is to develop and comprehensively validate ultra-low count quantitative SPECT (ULC-QSPECT) methods for alpha particle radiopharmaceutical therapies (αRPTs), including in a first-in-man trial in patients with bone metastatic castration-resistant prostate cancer. αRPTs, such as those based on Actinium-225, Thorium-227 and approved Radium-223 isotopes, are an emerging class of cytotoxic therapies for patients with disseminated metastatic disease using internally administered alpha-particle emitting agents. Despite the great potential of these therapies, current αRPT regimens are not personalized, with administered activity dependent merely on mass, likely leading to non-optimal therapy. To address this challenge, there is a crucial unmet need for methods to measure the isotope uptake, and hence the absorbed radiation dose with these therapies, both at sites of disease and in vital dose-limiting organs. SPECT provides a clinically translatable mechanism to achieve this goal. However, a key challenge to SPECT-based quantification is that the administered activities in αRPTs are orders of magnitude lower than a typical SPECT scan, leading to ultra-low detected count levels. Conventional approaches to quantification that reconstruct the isotope distribution and estimate the regional uptake from reconstructed images are erroneous at these low count levels. To address this issue, we put forwards a novel computational ULC-QSPECT framework for regional activity estimation from αRPTs. These methods quantify regional uptake directly from projection data skipping the reconstruction step, and at the same time, extract the maximal possible information from the acquired projection data. For this purpose, we propose novel methods that accurately model the physics of imaging αRPTs, including stray- radiation-related noise, use data from multiple-energy windows, incorporate scatter-window photons for quantification, and process data in list-mode format. Our extensive preliminary data show that the proposed methods result in nearly unbiased uptake and variances close to the theoretical limit. We propose to further develop and rigorously evaluate these methods. Our proposed evaluations include studies over multiple scanners with different detectors and different collimator configurations. Further, our goal is clinical translation of these methods. Towards this goal, we propose to clinically evaluate these methods for measuring activity concentrations at sites of uptake of [223Ra]RaCl2 in men with castrate resistant prostate cancer. These methods will enable quantification of activity at disease sites in the skeleton as well as clearance through the intestine. The approach has direct relevance to patients as it achieves noninvasive imaging of low-administered activity therapies. Further, this proposal has substantial potential impact to improve both safety and efficacy of drug development efforts in this rapidly evolving space. Further, the methods developed in this proposal will strengthen the clinical utility of SPECT in managing patients with these therapies.