Ultra-Low Count Quantitative SPECT for Alpha-Particle Therapies

项目总结： 该项目的总体目标是开发和全面验证超低计数定量SPECT 阿尔法粒子放射药物治疗(αRPTS)的方法，包括首例人 在骨转移耐去势前列腺癌患者中的试验。αRPT，例如基于 ~(225)Ac、~(227)Th~(227)和经批准的~(223)Re同位素是一种新兴的细胞毒性疗法 用于使用内部注射的阿尔法粒子发射剂的播散性转移性疾病患者。 尽管这些疗法具有巨大的潜力，但目前的αRPT方案并不是个性化的， 活动仅依赖于质量，很可能导致非最佳治疗。为了应对这一挑战，有一个 对测量同位素摄取量的方法的关键需求未得到满足，因此 这些疗法既适用于疾病部位，也适用于重要的剂量限制器官。SPECT提供了一种临床可翻译的 实现这一目标的机制。然而，基于SPECT的量化的一个关键挑战是 αRPT中的管理活动比典型的SPECT扫描低一个数量级，导致超低 检测到计数级别。重建同位素分布的传统量化方法和 在这些低计数水平下，从重建图像估计区域摄取是错误的。致信地址 针对这一问题，我们提出了一个新的用于区域活动估计的计算ULC-QSPECT框架 α报告。这些方法直接从跳过重建步骤的投影数据量化区域摄取， 同时，从获取的投影数据中提取最大可能信息。为了这个 目的：我们提出了精确模拟成像αRPT的物理模型的新方法，其中包括杂散模型。 与辐射相关噪声，使用来自多个能量窗的数据，结合散射窗光子 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，拟议中的 方法的结果是近乎无偏见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 具有不同探测器和不同准直器配置的扫描仪。此外，我们的目标是临床翻译 这些方法中的一个。为了达到这个目标，我们建议对这些测量活动性的方法进行临床评估。 去势抵抗前列腺癌患者摄取[223Ra]RaCl2部位的浓度。这些方法 将能够量化骨骼中疾病部位的活动以及通过肠道的清除。 该方法与患者直接相关，因为它实现了对低剂量活动的非侵入性成像 治疗。此外，这项建议对提高药物的安全性和有效性具有重大的潜在影响。 在这一快速发展的空间中的发展努力。此外，本提案中制定的方法将 加强SPECT在治疗患者中的临床应用。

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.