Optimization of PET Image Reconstruction for Lesion Detection

用于病变检测的 PET 图像重建优化

• 批准号: 10041119
• 负责人: Kuang Gong
• 金额: $ 9.43万
• 依托单位: MASSACHUSETTS GENERAL HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-07-01 至 2022-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10041119
• 关键词: Address; Adult; Algorithms; Awareness; Biological Models; Clinic; Clinical; Computer Simulation; Data; Data Set; Detection; Diagnosis; Distant Metastasis; Dose; Early Diagnosis; Enhancing Lesion; FOLH1 gene; Gallium; Goals; Half-Life; Image; Incidence; Injections; Label; Lead; Lesion; Location; Malignant Neoplasms; Malignant neoplasm of prostate; Measures; Methodology; Methods; Modeling; Neuroendocrine Tumors; Noise; Oncology; Outcome; Output; Patients; Performance; Phase; Physics; Play; Positron; Positron-Emission Tomography; Prevalence; Protocols documentation; Radionuclide Imaging; Reader; Recovery; Recurrence; Resolution; Role; Savings; Sensitivity and Specificity; Staging; Testing; Time; Tracer; Training; United States; Validation; Vendor; X-Ray Computed Tomography; base; cancer type; deep learning; denoising; effectiveness validation; experience; fluorodeoxyglucose; image reconstruction; imaging modality; improved; learning strategy; molecular imaging; neural network; neuroendocrine differentiation; novel; outcome forecast; pediatric patients; pentetreotide; radiologist; radiotracer; reconstruction; routine imaging; success; treatment optimization; treatment planning; tumor

Optimization of PET Image Reconstruction for Lesion Detection Abstract PET is a molecular imaging modality widely used in oncology studies due to its high sensitivity and the potential of early diagnosis. For neuroendocrine tumors (NETs), 68Ga-DOTATATE PET has been recently used in clinical routine for imaging NETs in adult and pediatric patients since 2016. It plays an important role in the diagnosis and staging of NETs. However, compared to 18F-FDG PET, the image quality of 68Ga-DOTATATE PET is lower due to much larger positron range, shorter half-life, and lower dose administration limited by generator capacity. All of these compromises the lesion detectability of 68Ga-DOTATATE PET, especially for small lesions, and can potentially lead to inaccurate NET diagnosis. As 68Ga-DOTATATE PET is increasingly used in clinics, there is an urgent and unmet need to further optimize 68Ga-DOTATATE PET/CT imaging for NET detection. Recently, data-driven methods have been developed for PET image denoising, where the PET system model is not considered. As the tumor-to-background ratio of 68Ga-DOTATATE PET is greater than 18F-FDG PET, the lesion recovery of 68Ga-DOTATATE PET can be hugely influenced by the smoothing effects as well as potential mismatches between training and testing datasets. In this study, we propose a novel data- informed and lesion detection-driven image reconstruction framework. The PET system model, image denoising module, and lesion-detection module will all be included in this reconstruction framework. The two specific aims of this exploratory proposal are (1) to develop a lesion detection-driven PET image reconstruction framework and validate it based on comprehensive computer simulations, (2) to apply the proposed reconstruction framework to existing clinical 68Ga-DOTATATE PET/CT datasets and test it based on various figure-of-merits. We expect that the integrated outcome of the specific aims will be a novel and robust image reconstruction framework to better recover lesions in a 68Ga- DOTATATE PET scan, which is essential for NET managements.

宠物图像重建用于病变检测 抽象的 PET是一种分子成像方式，由于其高灵敏度和 早期诊断的潜力。对于神经内分泌肿瘤（NETS），68Ga-凝聚宠物已经 自2016年以来，最近在临床常规中用于成人和儿科患者的成像网。 在网的诊断和分期中的重要作用。但是，与18f-fdg宠物相比 由于较大的正电子范围，较短的半衰期和较低 剂量给药受发电机容量有限的限制。所有这些都妥协了病变的可检测性 68GA-核宠物，特别是对于小病变，可能导致网络不准确 诊断。由于诊所中越来越多地使用68Ga-核PET，因此有紧急且未满足的需求 进一步优化68GA-核PET/CT成像以进行净检测。最近，数据驱动 已经开发了用于PET图像Denoisising的方法，其中宠物系统模型不是 经过考虑的。由于肿瘤与背景的比率为68GA-GATATATE PET大于18F-FDG PET，因此 68GA-核PET的病变恢复也可能受到平滑效果的极大影响 作为培训和测试数据集之间的潜在不匹配。在这项研究中，我们提出了一个新的数据 - 通知和病变检测驱动的图像重建框架。宠物系统模型，图像 该重建框架中将包括降解模块和病变检测模块。 该探索性建议的两个具体目的是（1）开发病变检测驱动的宠物 图像重建框架并根据全面的计算机模拟验证它，（2） 将建议的重建框架应用于现有的临床68GA-DOTATATE PET/CT数据集 并根据各种合格进行测试。我们期望具体目标的综合结果 将是一个新颖而健壮的图像重建框架，可以更好地恢复68GA- Dotatate PET扫描，这对于净管理人员至关重要。