Biomedical Imaging Science Department, University of Leeds, Leeds, UK.
Department of Statistics, University of Leeds, Leeds, UK.
Contrast Media Mol Imaging. 2019 Jan 16;2019:3438093. doi: 10.1155/2019/3438093. eCollection 2019.
Positron emission tomography (PET) provides simple noninvasive imaging biomarkers for multiple human diseases which can be used to produce quantitative information from single static images or to monitor dynamic processes. Such kinetic studies often require the tracer input function (IF) to be measured but, in contrast to direct blood sampling, the image-derived input function (IDIF) provides a noninvasive alternative technique to estimate the IF. Accurate estimation can, in general, be challenging due to the partial volume effect (PVE), which is particularly important in preclinical work on small animals. The recently proposed hybrid kernelised ordered subsets expectation maximisation (HKEM) method has been shown to improve accuracy and contrast across a range of different datasets and count levels and can be used on PET/MR or PET/CT data. In this work, we apply the method with the purpose of providing accurate estimates of the aorta IDIF for rabbit PET studies. In addition, we proposed a method for the extraction of the aorta region of interest (ROI) using the MR and the HKEM image, to minimise the PVE within the rabbit aortic region-a method which can be directly transferred to the clinical setting. A realistic simulation study was performed with ten independent noise realisations while two, real data, rabbit datasets, acquired with the Biograph Siemens mMR PET/MR scanner, were also considered. For reference and comparison, the data were reconstructed using OSEM, OSEM with Gaussian postfilter and KEM, as well as HKEM. The results across the simulated datasets and different time frames show reduced PVE and accurate IDIF values for the proposed method, with 5% average bias (0.8% minimum and 16% maximum bias). Consistent results were obtained with the real datasets. The results of this study demonstrate that HKEM can be used to accurately estimate the IDIF in preclinical PET/MR studies, such as rabbit mMR data, as well as in clinical human studies. The proposed algorithm is made available as part of an open software library, and it can be used equally successfully on human or animal data acquired from a variety of PET/MR or PET/CT scanners.
正电子发射断层扫描（PET）为多种人类疾病提供了简单的无创影像学生物标志物，可用于从单次静态图像中产生定量信息，或用于监测动态过程。这种动力学研究通常需要测量示踪剂输入函数（IF），但与直接采血相比，图像衍生的输入函数（IDIF）提供了一种无创替代技术来估计 IF。由于部分容积效应（PVE），一般来说，准确的估计可能具有挑战性，而 PVE 在小动物的临床前工作中尤为重要。最近提出的混合核有序子集期望最大化（HKEM）方法已被证明可以提高不同数据集和计数水平的准确性和对比度，并且可以用于 PET/MR 或 PET/CT 数据。在这项工作中，我们应用该方法的目的是为兔 PET 研究提供准确的主动脉 IDIF 估计。此外，我们提出了一种使用 MR 和 HKEM 图像提取主动脉感兴趣区域（ROI）的方法，以最小化兔主动脉区域内的 PVE——该方法可以直接转移到临床环境中。进行了具有十个独立噪声实现的逼真模拟研究，同时还考虑了使用 Biograph Siemens mMR PET/MR 扫描仪采集的两个真实的兔数据集。作为参考和比较，使用 OSEM、带高斯后滤波器的 OSEM 和 KEM 以及 HKEM 对数据进行了重建。模拟数据集和不同时间帧的结果显示，所提出的方法具有较低的 PVE 和准确的 IDIF 值，平均偏差为 5%（最小偏差为 0.8%，最大偏差为 16%）。真实数据集也得到了一致的结果。这项研究的结果表明，HKEM 可用于准确估计临床前 PET/MR 研究（如兔 mMR 数据）以及临床人体研究中的 IDIF。所提出的算法作为一个开放软件库的一部分提供，并可成功用于从各种 PET/MR 或 PET/CT 扫描仪采集的人类或动物数据。
