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.

使用康普顿相机进行 SPECT 进行甲状腺癌成像 抽象的 甲状腺呈蝴蝶状，位于颈部前下方，分泌维持正常生物功能的激素。 功能。甲状腺结节的发病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，也是年轻人中最常见的癌症 女性，美国每年新增病例超过 5 万例。为了检测和治疗甲状腺癌，需要 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) 与放射性碘闪烁扫描一起使用来评估甲状腺癌患者。这 用于 SPECT 的伽马相机包含一个机械准直器，该机械准直器极大地影响了剂量效率和限制 诊断敏感性。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 患者筛查和随访扫描的数量级。 在这个R21项目中，我们将设计一个高效、高质量的断层成像系统，采用康普顿 甲状腺癌成像专用相机，并为康普顿开发相关软件包 基于散射的 SPECT 成像。主要创新在于深度学习赋能图像 重建和基于 Timepix3 的康普顿相机用于甲状腺癌成像。提议的技术 有助于大幅降低辐射剂量，提高成像速度，并增强图像质量和诊断能力 性能优异，具有巨大的临床转化潜力。这三个具体目标定义如下： (1) 将开发蒙特卡罗模拟器用于伽马射线康普顿数据合成； (b) 深度重建 将为基于康普顿相机的 SPECT 开发算法，并且 (c) 将设计 SPECT 系统 超低剂量甲状腺成像的数值模拟和体模实验。 该项目完成后，仿真和重建软件工具应该已经完成 开发用于人体甲状腺中放射性示踪剂分布的断层扫描成像和护理点 (POC) SPECT 系统将采用康普顿相机设计，并经过实验验证，具有卓越的性能 超低剂量下的诊断性能。深度学习技术与人工智能之间的协同作用 尖端的 Timepix3 相机将在后续 R01 提案中进行演示。