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: 10593085
• 负责人: Charles Ross Schmidtlein
• 金额: $ 23.18万
• 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 2025-03-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10593085
• 关键词: Address; Alpha Particles; Biodistribution; Cell Cycle Stage; Cells; Clinical; DNA Double Strand Break; Data; Development; Diameter; Distributional Activity; Dose; Dose Rate; Environment; FOLH1 gene; Fractionation; Generations; Glioma; Goals; Happiness; Image; Knowledge; Linear Energy Transfer; Malignant Neoplasms; Malignant neoplasm of urinary bladder; Measures; Mediating; Metastatic Prostate Cancer; 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; absorption; cancer cell; castration resistant prostate cancer; cell killing; cytotoxicity; design; digital; dosimetry; image reconstruction; imaging modality; improved; leukemia; low dose computed tomography; melanoma; meter; 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.

项目摘要 标题：针对目标α疗法的高级平面图像重建 基于α发射放射性药物（AER）的靶向α疗法（TAT）已最近已成为 成功应用于许多传统方法无法治愈的许多晚期癌症的治疗方法。 但是，由于非常低的管理 活动。结果，AER生物分布未知，因此，AER吸收的剂量分布为 未知。这，我们预见正常组织毒性和处方个性化治疗的能力是 需要对AER生物分布的准确定量成像来记住这种情况。 为了满足这一需求，我们项目的长期目标是开发一种能够生成准确的方法 使用低计数AER平面数据和共同注册的低剂量CT图像的AER（ProJ-AER）投影图像 在SPECT/CT摄像机上获得。获得的Proj-AER与CT合并将允许精确的AER活动 将用作剂量计模型的输入数据的估计，该数据将提供有关辐射的信息 剂量为器官/肿瘤。该提议的目的是发展一种新颖的稀疏性，以促进重建 基于平面AER成像的物理模型的方法，并对其上级进行概念验证研究 定量准确性与护理标准（SOC）。我们将使用低计数225ac平面图像并共同注册 在SPECT/CT摄像机上获得的低剂量CT图像。物理和数字幻影将被雇用。 在强大的初步数据的指导下，将通过追求两个具体目标来附加此目标：1）开发和 验证AER的准确的投影平面活动分布重建方法； 2）比较 使用模拟和物理状态的225AC定量任务中当前SOC的方法的性能 在SPECT/CT摄像机上获取的Planar/CT数据。该方法将依靠包含的物理成像模型 系统内核和调节。为了控制噪声，我们将使用促进调节的稀疏性 L0-NORM的信封。固定点接近操作员方法将用于解决结果 非covex最小化问题。噪声对器官/肿瘤活动估计的影响将被解释 带有合奏平方误差性能指标。偏见和差异的估计权衡将 被探索。模拟的剂量学任务将用于展示性能改进。结果： 我们将确定新型的平面重建方法已准备好在临床环境中进行测试。 成功的衡量标准定义为在精度和准确性方面的重大提高（> 50％） AER区域活动浓度的估计。拟议的研究很重要，因为它是 预计AER的直接定量成像将允许优化的TAT个性化设计，包括 活动/分馏时间表。它还将对成像AER替代物的实用性进行合理评估。 最终，此类知识将导致晚期患者的反应和治疗可能性更高 许多癌症的阶段。

项目成果

Multi‐scale cascaded networks for synthesis of mammogram to decrease intensity distortion and increase model‐based perceptual similarity

用于合成乳房X光照片的多尺度级联网络，以减少强度失真并增加基于模型的感知相似性

• DOI: 10.1002/mp.16007
• 发表时间: 2022
• 期刊: Medical Physics
• 影响因子: 3.8
• 作者: Jiang, Gongfa;He, Zilong;Zhou, Yuanpin;Wei, Jun;Xu, Yuesheng;Zeng, Hui;Wu, Jiefang;Qin, Genggeng;Chen, Weiguo;Lu, Yao
• 通讯作者: Lu, Yao