Optimization of PET Imaging

PET 成像的优化

• 批准号: 8313653
• 负责人: JINYI QI
• 金额: $ 31.12万
• 依托单位: UNIVERSITY OF CALIFORNIA AT DAVIS
• 依托单位国家: 美国
• 财政年份: 2003
• 资助国家: 美国
• 起止时间: 2003-04-01 至 2014-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8313653
• 关键词: Address; Algorithms; Animals; Biochemical Process; Blood; Blood specimen; Breast; Cancer Detection; Cancer Patient; Characteristics; Clinical; Computer Simulation; Data; Data Analyses; Detection; Development; Development Plans; Diagnostic Neoplasm Staging; Early Diagnosis; Functional Imaging; Funding; General Population; Goals; Healthcare; Histologic; Histology; Human; Image; Imaging Techniques; Machine Learning; Malignant Neoplasms; Mammary Gland Parenchyma; Maps; Mastectomy; Measures; Medical Imaging; Methods; Micrometastasis; Modeling; Monitor; Motion; Nature; Neoplasm Metastasis; Noise; Operative Surgical Procedures; Outcome; Patients; Pattern; Performance; Phase; Physiological; Positron-Emission Tomography; Primary Neoplasm; Property; Protocols documentation; Radioactive Tracers; Recruitment Activity; Research; Resolution; Scanning; Staging; Structure; System; Techniques; Time; Translating; Validation; base; cancer imaging; clinical practice; clinically relevant; computerized data processing; fluorodeoxyglucose; fluorodeoxyglucose positron emission tomography; image reconstruction; imaging modality; improved; instrumentation; lymph nodes; malignant breast neoplasm; novel; novel strategies; patient population; public health relevance; reconstruction; research study; success; technology development; tool; treatment response; tumor; uptake

DESCRIPTION (provided by applicant): Positron emission tomography (PET) is a functional imaging modality that is capable of imaging biochemical processes in humans or animals through the use of radioactive tracers. PET/CT with [18F]fluorodeoxyglucose (FDG) is increasingly being used for staging, restaging and treatment monitoring for cancer patients with different types of tumors. However, current FDG-PET provides a low sensitivity to detect micrometastases and small tumor infiltrated lymph nodes. The goal of this project is to improve the efficacy of PET imaging through the development of novel image reconstruction methods and data analysis tools. During the current funding period, we have developed a method for tuning reconstruction algorithm based on the noise characteristics in measured patient data. This patient-adaptive reconstruction algorithm has been validated using computer simulations and phantom experiments. In the next phase of the project, we will implement the patient-adaptive algorithm on clinical PET scanners and validate the method using patient data. We will further expand the capability of PET imaging by developing novel methods to utilize the anatomical information provided by PET/CT scanners and by exploring the potential of dynamic PET for cancer detection and staging. The four specific aims of the project are (1) To implement the patient-adaptive MAP reconstruction on clinical scanners and to validate the algorithm using breast cancer patients; (2) To develop a novel approach to PET image reconstruction using anatomical information; (3) To develop statistically efficient image reconstruction methods for dynamic PET; (4) To identify spatial-temporal features in dynamic PET image for detection and characterization of breast cancer and to evaluate the performance using breast cancer patient data. The first aim is an important step towards translating image reconstruction technology development into patient health care. Once validated using breast cancer patients, the method is readily applicable to imaging other types of tumors. The second to the fourth aims will greatly enhance the capability of PET by taking advantage of the recent advances in instrumentation (wide availability of PET/CT) and the dynamic nature of PET imaging. We expect the new methods to be developed will be able to extract clinically relevant features from dynamic PET for detecting small tumors and characterizing the malignancy of primary tumors. All the results will be validated using breast cancer patient data with histologically verified ground truth. The success of this research will have a significant and positive impact on the management of patients with breast cancer. PUBLIC HEALTH RELEVANCE: Positron emission tomography (PET) is a medical imaging technique that can detect cancer and monitor treatment response. This research aims to improve the efficacy of PET by developing novel image reconstruction and data processing tools that will enable early detection and characterization of breast cancer. The success of this research is of substantial benefit to the general population of breast cancer suffers.

描述（由申请人提供）：正电子发射断层扫描（PET）是一种功能成像模式，能够通过使用放射性示踪剂对人类或动物的生化过程进行成像。使用[18F]氟脱氧葡萄糖（FDG）的PET/CT越来越多地用于患有不同类型肿瘤的癌症患者的分期、再分期和治疗监测。然而，目前的FDG-PET检测微转移和小肿瘤浸润淋巴结的灵敏度较低。该项目的目标是通过开发新的图像重建方法和数据分析工具来提高PET成像的功效。在目前的资助期间，我们已经开发出一种方法，用于调整重建算法的基础上测量的患者数据中的噪声特性。这种患者自适应重建算法已通过计算机模拟和体模实验进行了验证。在项目的下一阶段，我们将在临床PET扫描仪上实现患者自适应算法，并使用患者数据验证该方法。我们将通过开发新方法来利用PET/CT扫描仪提供的解剖信息，并通过探索动态PET用于癌症检测和分期的潜力，进一步扩展PET成像的能力。该项目的四个具体目标是：（1）在临床扫描仪上实现患者自适应MAP重建，并使用乳腺癌患者验证该算法;（2）开发一种使用解剖信息的PET图像重建新方法;（3）开发统计学上有效的动态PET图像重建方法;（4）在动态PET图像中识别用于乳腺癌检测和表征的时空特征，并使用乳腺癌患者数据评估性能。第一个目标是将图像重建技术发展转化为患者健康护理的重要一步。一旦使用乳腺癌患者验证，该方法很容易适用于成像其他类型的肿瘤。第二至第四个目标将通过利用仪器的最新进展（PET/CT的广泛可用性）和PET成像的动态特性，大大提高PET的能力。我们期望开发的新方法将能够从动态PET中提取临床相关特征，用于检测小肿瘤和表征原发性肿瘤的恶性程度。所有结果都将使用乳腺癌患者数据进行验证，这些数据具有组织学验证的基本事实。这项研究的成功将对乳腺癌患者的管理产生重大而积极的影响。 公共卫生相关性：正电子发射断层扫描（PET）是一种医学成像技术，可以检测癌症和监测治疗反应。这项研究旨在通过开发新的图像重建和数据处理工具来提高PET的功效，这些工具将能够早期检测和表征乳腺癌。这项研究的成功对一般乳腺癌患者有很大的好处。