Task-Based Optimization for Gated Myocardial ECT

描述（由申请人提供）：在第二次重新提交的5年竞争性更新中，我们仔细解决了评审员提出的一系列新问题，包括关于MAP-EM算法的更多详细信息、使用模拟4D门控SPECT和PET数据的优化方法、拟定4D观察者模型的确认方法和临床评价研究。在目前的补助金，我们已经开发了改进的4D图像重建方法的门控心肌灌注（GMP）SPECT，提供更好的时间分辨率，通过使用更多的帧每个心动周期，而不会降低图像的噪声特性。这有可能改善局部心肌壁运动异常的可视化。我们已经开发出的方法来确定运动矢量场的心肌GMP SPECT数据使用已知的心脏材料的属性和心脏的平均运动模型作为初始估计。此外，我们还使用CHO和ROC方法开发了基于任务的方法，使用来自4D NCAT体模群体的模拟数据来优化和评估这些新技术，这些体模真实地模拟了临床数据中发现的解剖和生理变化。基于这项研究令人鼓舞的结果，我们建议继续研究4D图像重建方法，以进一步提高4D GMP ECT图像的质量和定量准确性。我们建议使用Rb-82将研究扩展到GMP PET。与GMP SPECT的当前研究类似，我们建议使用逼真的计算机模拟数据对GMP PET的数据采集和4D图像重建方法进行初步优化和评估。我们实验室开发的混合蒙特卡罗技术将用于从4D NCAT体模的群体中有效生成GMP PET数据，并对PET系统几何形状和探测器配置进行精确建模。然后，我们将验证数据采集和优化的4D图像重建方法，通过实验的临床系统，使用动态心脏物理体模。在GE Healthcare的支持下，我们建议在本研究中使用的GE SPECT/CT和PET/CT临床系统中实现列表模式数据采集功能。采用CHO和ROC方法的基于任务的评价方法将用于评价从体模数据获得的GMP SPECT和PET图像中检测局部室壁运动异常的改进。最后，我们建议使用临床GMP SPECT和PET数据（使用列表模式数据采集）开始评估4D图像重建方法。我们将使用模拟数据比较CHO和人类观察员的评估结果。我们还将比较模拟研究和使用经过培训的医生进行的临床研究的评价结果。这些结果将允许评估的效用数学观察员在基于任务的评价4D GMP SPECT和PET成像技术。

DESCRIPTION (provided by applicant): In this second resubmission of a 5-year competing renewal, we have carefully addressed a new set of concerns raised by the reviewers including more details on the MAP-EM algorithm, the optimization methods using simulated 4D gated SPECT and PET data, validation method for the proposed 4D observer model and the clinical evaluation study. During the current grant, we have developed improved 4D image reconstruction methods for gated myocardial perfusion (GMP) SPECT that provide better time resolution through the use of more frames per cardiac cycle without degrading the noise characteristics of the images. This has the potential to provide improved visualization of regional myocardial wall motion abnormalities. We have developed methods to determine the motion vector fields of the myocardium from the GMP SPECT data using known cardiac material properties and an average motion model of the heart as the initial estimate. Also, we have developed task-based methods using the CHO and ROC methodology to optimize and evaluate these new techniques using simulated data from populations of 4D NCAT phantoms that realistically model anatomical and physiological variations found in clinical data. Based on encouraging results from this study, we propose to continue our investigation into 4D image reconstruction methods to further improve the quality and quantitative accuracy of 4D GMP ECT images. We propose to extend the investigation to GMP PET using Rb-82. Similar to the current study on GMP SPECT, we propose to initially optimize and evaluate the data acquisition and 4D image reconstruction methods for GMP PET using realistic computer simulated data. A hybrid Monte Carlo technique developed in our laboratory will be used to provide efficient generation of GMP PET data from populations of the 4D NCAT phantoms with accurate modeling of the PET system geometries and detector configuration. We will then validate the data acquisition and optimize the 4D image reconstruction methods through experiments on clinical systems using a dynamic cardiac physical phantom. With the support of GE Healthcare, we propose to implement listmode data acquisition capabilities in both the GE SPECT/CT and PET/CT clinical systems used in this study. Task-based evaluation methods using CHO and ROC methodology will be applied to evaluate improvements in detecting regional wall motion abnormalities in GMP SPECT and PET images obtained from the phantom data. Finally, we propose to initiate evaluation of the 4D image reconstruction methods using clinical GMP SPECT and PET data acquired using the listmode data acquisition. We will compare evaluation results from the CHO and human observers using simulated data. We will also compare evaluation results from the simulation study and clinical study using trained physicians. These results will allow assessment of the utility of mathematical observers in task-based evaluation of 4D GMP SPECT and PET imaging techniques.