SPECT with a Compton Camera for Thyroid Cancer Imaging

康普顿相机SPECT在甲状腺癌显像中的应用 摘要 甲状腺位于颈部前下方，呈蝴蝶状，分泌正常生物所需的荷尔蒙。 功能。甲状腺结节的发病率随着年龄的增长而增加，累及一半以上的人口。 甲状腺癌是最常见的内分泌相关癌症，也是年轻人最常见的癌症。 女性，美国每年有超过50000例新病例。为了检测和治疗甲状腺癌，人们希望 准确地描述结节的特征。目前，单光子发射计算机断层扫描(SPECT)和 计算机断层扫描(CT)和放射性碘核素扫描用于评估甲状腺癌患者。这个 用于SPECT的伽马相机包含一个机械准直器，大大降低了剂量效率和限制 诊断敏感度。幸运的是，康普顿相机正在成为绘制地图的理想方法 放射性药物在甲状腺内的分布。这是因为康普顿的相机不需要 机械准直，原则上不排斥伽马射线光子。因此，辐射剂量将减少 在患者的筛查和后续扫描中的数量级。 在这个R21项目中，我们将设计一个高效率、高质量的层析成像系统，它带有康普顿 专门用于甲状腺癌成像的相机，并为康普顿开发了一个相关的软件包 基于散射的SPECT成像。主要创新之处在于深度学习赋能形象 重建和基于Timepx3的康普顿相机用于甲状腺癌成像。建议的技术 帮助显著减少辐射剂量、提高成像速度并增强图像质量和诊断能力 性能，具有很大的临床翻译潜力。三个具体目标定义如下：(1) 将开发用于伽马射线康普顿数据合成的蒙特卡罗模拟器；(B)深度重建 将为基于康普顿相机的SPECT开发算法，以及(C)将在#年设计SPECT系统 超低剂量甲状腺成像的数值模拟和体模实验。 在这个项目完成后，模拟和重建软件工具应该已经 开发用于人体甲状腺中放射性示踪剂分布的断层成像，以及护理点(POC) SPECT系统将与康普顿相机一起设计，并经过实验验证具有优越的性能 在超低剂量下的诊断性能。深度学习技术与 尖端的TIMEPEPX3相机将为后续的R01提案进行演示。

SPECT with a Compton Camera for Thyroid Cancer Imaging ABSTRACT The thyroid gland is butterfly-shaped in the lower front of the neck, and secretes hormones for normal biological functions. The incidence of thyroid nodules increases with age, involving more than half of the population. Thyroid cancer is the most common type of endocrine-related cancer and the most common cancer in young women, with over 50K new cases per year in the United States. To detect and treat thyroid cancer, it is desired to characterize the nodule accurately. Currently, single photon emission computed tomography (SPECT) and computed tomography (CT) are used with radioiodine scintigraphy to evaluate patients with thyroid cancer. The gamma camera for SPECT contains a mechanical collimator that greatly compromises dose efficiency and limits diagnostic sensitivity. Fortunately, the Compton camera is emerging as an ideal approach for mapping the distribution of radiopharmaceuticals inside the thyroid. It is because the Compton camera requires no mechanical collimation and in principle rejects no gamma ray photon. Hence, radiation dose will be reduced by orders of magnitude in screening and follow-up scans of patients. In this R21 project, we will design a high-efficiency and high-quality tomographic imaging system with a Compton camera dedicated to thyroid cancer imaging, and develop an associated software package for Compton scattering based SPECT imaging. The major innovation lies in the deep learning empowered image reconstruction and the Timepix3-based Compton camera for thyroid cancer imaging. The proposed techniques help reduce radiation dose dramatically, improve the imaging speed, and enhance image quality and diagnostic performance, having a great potential for clinical translation. The three specific aims are defined as follows: (1) a Monte Carlo simulator will be developed for gamma ray Compton data synthesis; (b) deep reconstruction algorithms will be developed for Compton camera based SPECT, and (c) a SPECT system will be designed in numerical simulation and phantom experiments for ultra-low-dose thyroid imaging. Upon the completion of this project, the simulation and reconstruction software tools should have been developed for tomographic imaging of the radiotracer distribution in the human thyroid, and a point of care (POC) SPECT system will have been designed with the Compton camera and experimentally verified for a superior diagnostic performance at an ultra-low dose. The synergy among the deep learning techniques and the cutting-edge Timepix3 camera will have been demonstrated for a follow-up R01 proposal.