ESTIMATION STRATEGIES FOR NUCLEAR MEDICAL IMAGING

描述(改编自申请者摘要)：长期目标 本研究旨在开发体内定量检测技术。 放射性同位素在小动物体内的定位，以加速和 简化新型放射性标记药物的设计和评价。 作为另一个项目的一部分，申请者正在完成 高分辨率模拟单光子环层析成像系统的构建 在SPRINT之后，但专门为99mTC、123I和 ~(131)I在小鼠和大鼠体内，具有毫米分辨率。 申请人已提议使用统一Cramer-Rao(CR)下限 作为一种工具来评估从 成像系统，并比较几种估计器的性能 确定整个器官或肿瘤的特定任务目标 器官内的活性浓度和分布。首字母 应用和测试将针对小动物的情况，但它 预计所开发的方法将适用于 对人类的想象。将开发计算CR界限的方法 当Fisher矩阵条件较差时。几项措施 将从偏置图像导出的偏置梯度长度与偏置梯度长度进行比较 以确定它们作为图像质量衡量标准的有用性。这个 统一的CR界限将被用来表征成像系统 性能、估计器性能和系统的稳健性 对象模型。两个相对较新的估计算法，受到惩罚 加权最小二乘(PWLS)和空间交替广义 将对期望最大化(SAGE)进行评估和比较，并 为量化任务确定的性能限制 可获得辅助信息的情况，例如以估计的形式 从核磁共振获得的器官和肿瘤边界 (核磁共振)图像，我们没有这样的信息。方法将 被设计成从核磁共振图像中参数化边界，构造 联合估计边界和具体活动的估计者，以及 描述这些估计的偏差和方差。理论上的 开发将通过模拟、幻影和小动物进行测试 成像实验。

DESCRIPTION (Adapted from Applicant's Abstract): The long term aim of this research is to develop techniques for in vivo quantification of radioisotope localization in small animals in order to speed and simplify the design and evaluation of new radiolabeled pharmaceuticals. As part of another project, the applicants are completing the construction of a high-resolution single photon ring tomograph modeled after SPRINT, but specifically designed for imaging 99mTc, 123I, and 131I in mice and rats with millimeter resolution. The applicant have proposed to use uniform Cramer-Rao (CR) lower bound as a tool to evaluate the intrinsic quality of data obtained from an imaging system, and to compare the performance of several estimators for the task- specific objectives of determining whole organ or tumor activity concentration and distribution within the organ. The initial application and testing will be for the case of small animals, but it is anticipated that the methods developed will be applicable to the imaging of humans. Methods will be developed to compute the CR bound when the Fisher matrices are poorly conditioned. Several measures derived from the bias image will be compared to the bias gradient length to determine their usefulness as a measure of image quality. The uniform CR bound will be used to characterize imaging system performance, estimator performance, and the robustness of the system and object models. Two relatively recent estimation algorithms, Penalized Weighted Least Squares, (PWLS), and Space-Alternating Generalized Expectation- maximization, (SAGE), will be evaluated and compared, and performance limits determined for the quantification tasks both for the case where side information is available, e.g. in the form of estimates of organ and tumor boundaries obtained from nuclear magnetic resonance (NMR) images and were no such information is available. Methods will be devised to parameterize boundaries from NMR images, construct estimators for joint estimation of boundaries and specific activity, and characterize the bias and variance of these estimates. Theoretical developments will be tested by simulation and phantom and small animal imaging experiments.