SPECT with a Compton Camera for Thyroid Cancer Imaging

使用康普顿相机进行 SPECT 进行甲状腺癌成像

• 批准号: 10286795
• 负责人: Ge Wang
• 金额: $ 40.78万
• 依托单位: UNIVERSITY OF MASSACHUSETTS LOWELL
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-16 至 2024-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10286795
• 关键词: 3-Dimensional; Age; Algorithms; Biological Process; Butterflies; Cancer Patient; Cancer Survivor; Collimator; Compton radiation; Computer software; Conceptions; Data; Data Set; Diagnosis; Diagnostic; Diagnostic Sensitivity; Disease; Distant Metastasis; Dose; Endocrine; Gamma Cameras; Gamma Rays; Geometry; Goals; Gold; Hormones; Human; I131 isotope; Image; Image Enhancement; Incidence; Iodine Isotopes; Label; Learning; Life; Malignant - descriptor; Malignant Neoplasms; Malignant neoplasm of thyroid; Mechanics; Monitor; Monte Carlo Method; Neck; Nodule; Operative Surgical Procedures; Papillary; Patients; Performance; Photons; Population; Prognosis; Publishing; Radiation; Radiation Dose Unit; Radioactive Iodine; Radioisotopes; Radionuclide Imaging; Radiopharmaceuticals; Recurrence; Scanning; Signal Transduction; Software Tools; Speed; System; Techniques; Thyroid Gland; Thyroid Nodule; United States; Visible Human Project; X-Ray Computed Tomography; attenuation; base; cancer imaging; cancer recurrence; clinical translation; combat; deep learning; deep neural network; design; detector; digital; dosage; empowered; experimental study; follow-up; image reconstruction; imaging system; improved; innovation; point of care; prototype; radiotracer; reconstruction; screening; simulation; single photon emission computed tomography; synergism; system architecture; tomography; tool; uptake; virtual; young woman

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.

使用用于甲状腺癌成像的康普顿摄像头的SPECT 抽象的 甲状腺在脖子的下部是蝴蝶形的，并分泌正常生物学的激素 功能。甲状腺结节的发生率随着年龄的增长而增加，涉及一半以上的人群。 甲状腺癌是最常见的内分泌相关癌症类型，也是年轻人中最常见的癌症 在美国，妇女每年有超过50k的新病例。为了检测和治疗甲状腺癌，需要 准确表征结节。目前，单光子排放计算机断层扫描（SPECT）和 计算机断层扫描（CT）与放射性碘闪烁显像一起评估甲状腺癌患者。这 SPECT的伽马摄像头包含一个机械准直仪，极大地损害了剂量效率和限制 诊断灵敏度。幸运的是，康普顿相机正在成为映射的理想方法 甲状腺内放射性药物的分布。这是因为康普顿相机不需要 机械准则和原则上拒绝没有伽玛射线光子。因此，辐射剂量将减少 筛查和随访患者的数量级。 在这个R21项目中，我们将使用Compton设计高效和高质量的层析成像系统 专用于甲状腺癌成像的摄像机，并为康普顿开发相关的软件包 基于散射的SPECT成像。主要的创新在于深度学习的授权形象 重建和基于TimePix3的甲状腺癌成像的康普顿相机。提出的技术 有助于大大减少辐射剂量，提高成像速度并提高图像质量和诊断 性能，具有临床翻译的巨大潜力。三个特定目的定义如下：（1）A 将开发蒙特卡洛模拟器用于伽马ray compton数据合成； （b）深度重建 将为基于康普顿摄像机的SPECT开发算法，（c）SPECT系统将在 超低剂量甲状腺成像的数值模拟和幻影实验。 该项目完成后，模拟和重建软件工具应该是 开发用于人类甲状腺中放射性示意剂分布的层析成像，以及一个护理点（POC） SPECT系统将使用康普顿摄像头设计，并通过实验验证 超低剂量的诊断性能。深度学习技术和 尖端的TimePix3摄像头将被证明用于后续R01提案。