Advanced planar image reconstruction for targeted alpha therapy

用于靶向 α 治疗的高级平面图像重建

• 批准号: 10453023
• 负责人: Charles Ross Schmidtlein
• 金额: $ 24.18万
• 依托单位: SLOAN-KETTERING INST CAN RESEARCH
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-04-01 至 2024-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10453023
• 关键词: Address; Alpha Particles; Biodistribution; Caliber; Cell Cycle; Cells; Clinical; DNA Double Strand Break; Data; Development; Distributional Activity; Dose; Dose-Rate; Environment; FOLH1 gene; Fractionation; Generations; Glioma; Goals; Image; Knowledge; Linear Energy Transfer; Malignant Neoplasms; Malignant neoplasm of urinary bladder; Measures; Mediating; Metastatic Prostate Cancer; Metastatic to; Methods; Mission; Modeling; Neuroendocrine Tumors; Noise; Normal tissue morphology; Organ; Outcome; Patient-Focused Outcomes; Patients; Performance; Public Health; Radiation Dose Unit; Radioisotopes; Radiopharmaceuticals; Research; Schedule; Surrogate Markers; System; Testing; Tissues; Toxic effect; United States National Institutes of Health; X-Ray Computed Tomography; base; cancer cell; castration resistant prostate cancer; cell killing; cytotoxicity; design; digital; dosimetry; image reconstruction; imaging modality; improved; leukemia; low dose computed tomography; melanoma; novel; personalized medicine; personalized predictions; physical model; prevent; quantitative imaging; reconstruction; response; single photon emission computed tomography; standard of care; success; targeted treatment; therapy design; tumor

Project Summary Title: Advanced Planar Image Reconstruction for Targeted Alpha Therapy Targeted Alpha Therapy (TAT) based on the alpha-emitting radiopharmaceuticals (AER) has been recently successfully applied as a treatment for many advanced-stage cancers incurable with conventional methods. However, current methods of imaging the biodistribution of AER are sub-optimal, due to very low administered activity. As a result, AER biodistributions are unknown and hence, absorbed dose distributions for AER are unknown. Thus, our ability to anticipate normal tissue toxicity and prescribe personalized treatment is compromised. Accurate quantitative imaging of the AER biodistribution is necessary to remedy this situation. To address this need, our project’s long-term goal is development of a method for the generation of accurate projection images of AER (proj-AER) using low-count AER planar data and co-registered low-dose CT images acquired on SPECT/CT cameras. The obtained proj-AER combined with CT will permit accurate AER activity estimation that will be used as input data for a dosimetry model, which will provide information on the radiation dose to organs/tumor. The objective of this proposal is to develop a novel sparsity promoting reconstruction method based on a physical model for planar AER imaging and perform a proof-of-concept study of its superior quantitative accuracy vs. standard-of-care (SOC). We will use low-count 225Ac planar images and co-registered low-dose CT images acquired on SPECT/CT cameras. Physical and digital phantoms will be employed. Guided by strong preliminary data, this objective will be attained by pursuing two specific aims: 1) Develop and validate an accurate projected planar activity distribution reconstruction method for AER; and 2) Compare performance of our method with current SOC in 225Ac quantitation tasks using simulated and physical-phantom planar/CT data acquired on SPECT/CT camera. The approach will rely on a physical imaging model containing the system kernels and regularization. To control noise, we will use sparsity promoting regularization with envelope of the l0-norm. The fixed-point proximity-operator approach will be used to solve the resulting nonconvex minimization problem. The effects of noise on organ/tumor activity estimates will be accounted for with an ensemble mean squared error performance metric. The estimation tradeoffs of bias and variance will be explored. Simulated dosimetry tasks will be used to demonstrate performance improvements. Outcomes: We will establish that the novel planar reconstruction method is ready for testing in the clinical environment. The measure of success is defined as substantial (>50%) improvement in precision and accuracy in the estimation of regional activity concentration of AER. The proposed research is significant because it is expected that the direct quantitative imaging of AER will allow optimized personalized design of TAT including activity/fractionation schedule. It will also enable rational assessment of the utility of imaging AER surrogates. Ultimately, such knowledge will lead to higher likelihood of response and cure for patients with advanced stages of many cancers.

项目概要 标题：用于靶向阿尔法治疗的高级平面图像重建 最近，基于α发射放射性药物（AER）的靶向α疗法（TAT） 成功应用于治疗许多传统方法无法治愈的晚期癌症。 然而，由于给药量非常低，目前对 AER 生物分布进行成像的方法并不是最佳的。 活动。因此，AER 生物分布是未知的，因此 AER 的吸收剂量分布是 未知。因此，我们预测正常组织毒性并制定个性化治疗的能力是 妥协了。为了纠正这种情况，需要对 AER 生物分布进行准确的定量成像。 为了满足这一需求，我们项目的长期目标是开发一种生成准确数据的方法 使用低计数 AER 平面数据和共同配准的低剂量 CT 图像的 AER 投影图像 (proj-AER) 在 SPECT/CT 相机上采集。获得的 proj-AER 与 CT 相结合将允许准确的 AER 活性 估计将用作剂量测定模型的输入数据，该模型将提供有关辐射的信息 对器官/肿瘤的剂量。该提案的目标是开发一种新的稀疏性促进重建 基于平面 AER 成像物理模型的方法，并对其优越性进行概念验证研究 定量准确性与护理标准 (SOC)。我们将使用低计数 225Ac 平面图像并共同配准 SPECT/CT 相机采集的低剂量 CT 图像。将使用物理和数字幻影。 在强有力的初步数据的指导下，这一目标将通过追求两个具体目标来实现：1) 开发和 验证 AER 的精确投影平面活动分布重建方法； 2) 比较 使用模拟和物理模型，我们的方法在当前 SOC 的 225Ac 定量任务中的性能 SPECT/CT 相机采集的平面/CT 数据。该方法将依赖于包含以下内容的物理成像模型： 系统内核和正则化。为了控制噪声，我们将使用稀疏性促进正则化 l0-范数的包络线。定点邻近算子方法将用于求解所得结果 非凸最小化问题。将考虑噪声对器官/肿瘤活动估计的影响 具有集成均方误差性能指标。偏差和方差的估计权衡将 被探索。模拟剂量测定任务将用于演示性能改进。结果： 我们将确定新型平面重建方法已准备好在临床环境中进行测试。 成功的衡量标准被定义为精确度和准确度的显着提高 (>50%) AER 区域活动浓度的估计。拟议的研究意义重大，因为它 预计 AER 的直接定量成像将允许 TAT 的优化个性化设计，包括 活动/分割时间表。它还将使成像 AER 替代物的效用得以合理评估。 最终，这些知识将提高晚期患者的反应和治愈可能性 许多癌症的阶段。