Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States of America. Author to whom any correspondence should be addressed.
Phys Med Biol. 2019 Mar 14;64(6):065018. doi: 10.1088/1361-6560/ab0472.
Myocardial blood flow and myocardial blood flow reserve (MBFR) measurements are often used clinically to quantify coronary microvascular function. Developing imaging-based methods to measure MBFR for research in mice would be advantageous for evaluating new treatment methods for coronary microvascular disease (CMVD), yet this is more challenging in mice than in humans. This work investigates microSPECT's quantitative capabilities of cardiac imaging by utilizing a multi-part cardiac phantom and applying a known kinetic model to synthesize kinetic data from static data, allowing for assessment of kinetic modeling accuracy. The phantom was designed with four main components: two left-ventricular (LV) myocardial sections and two LV blood-pool sections, sized for end-systole (ES) and end-diastole (ED). Each section of the phantom was imaged separately while acquiring list-mode data. These static, separate-compartment data were manipulated into synthetic dynamic data using a kinetic model representing the myocardium and blood-pool activity concentrations over time and then combined into a set of dynamic image frames and reconstructed. Regions of interest were drawn on the resulting images, and kinetic parameters were estimated. This process was performed for three tracer uptake values (K ), three myocardial wall thicknesses, ten filter parameters, and 20 iterations for 25 noise ensembles. The degree of filtering and iteration number were optimized to minimize the root mean-squared error (RMSE) of K values, with the largest number of iterations and minimal filtering yielding the lowest error. Using the optimized parameters, K was determined with reasonable error (~3% RMSE) over all wall thicknesses and K input values. This work demonstrates that accurate and precise measurements of K are possible for the U-SPECT+ system used in this study, for several different uptake rates and LV dimensions. Additionally, it allows for future investigation utilizing other imaging systems, including PET studies with any radiotracer, as well as with additional phantom parts containing lesions.
心肌血流和心肌血流储备(MBFR)测量常用于临床量化冠状动脉微血管功能。开发基于成像的方法来测量小鼠的 MBFR 对于评估冠状动脉微血管疾病(CMVD)的新治疗方法将是有利的,但这在小鼠中比在人类中更具挑战性。这项工作通过利用多部分心脏体模和应用已知的动力学模型来从静态数据中合成动力学数据,从而研究 microSPECT 对心脏成像的定量能力,这允许评估动力学建模的准确性。该体模设计有四个主要部分:两个左心室(LV)心肌部分和两个 LV 血池部分,大小适合收缩末期(ES)和舒张末期(ED)。在获取列表模式数据的同时,对体模的每个部分分别进行成像。使用代表心肌和血池随时间变化的活性浓度的动力学模型对这些静态的、单独的隔室数据进行处理,将其转换为合成动态数据,然后将其组合成一组动态图像帧并进行重建。在生成的图像上绘制感兴趣区域,并估计动力学参数。该过程针对三种示踪剂摄取值(K )、三种心肌壁厚度、十种滤波器参数和 20 次迭代进行了 25 次噪声集合。优化过滤程度和迭代次数以最小化 K 值的均方根误差(RMSE),使用最大数量的迭代和最小的过滤可获得最低的误差。使用优化的参数,可以在所有壁厚度和 K 输入值上以合理的误差(~3% RMSE)确定 K 。这项工作表明,在本研究中使用的 U-SPECT+系统可以对几种不同的摄取率和 LV 尺寸进行准确和精确的 K 测量。此外,它还允许未来利用其他成像系统进行研究,包括使用任何放射性示踪剂的 PET 研究,以及使用包含病变的其他体模部件。