Attenuation correction strategies for myocardial perfusion imaging using dual-gated SPECT

摘要 使用单光子发射计算机断层扫描(SPECT)的心肌灌注成像(MPI)是一种 冠状动脉病变(CAD)的诊断和预后的临床常用工具。双重心肺 门控SPECT(D-SPECT)很早就被提出，用来消除患者心脏和心脏的伪影 呼吸运动，但噪音升高，缺乏证据表明诊断优于处理复杂性 阻碍了它的临床应用。心电门控SPECT(C-SPECT)仍然是主流，使 评价左心室(LV)功能。高级4D重建，具有卓越的去噪能力 最近重振了对D-SPECT的兴趣。同时，衰减校正(AC)对于定量测量是必不可少的 MPI和最大限度地减少误报。然而，当SPECT图像与不匹配时可能会出现交流伪影 由混合SPECT/CT扫描仪得出的衰减图。这成为D-D的另一个主要障碍- SPECT是因为伴随的锥束CT(CBCT)只产生一个非呼吸门控的三维CT图像。 为了解决这些问题，我们提出了一种新的SPECT MPI协议：运动匹配AC(D-SPECT)的D-SPECT协议。 SPECT-MAC)，这将最小化SPECT MPI伪像。运动匹配的衰减贴图可以是 通过一种通用的同时运动估计和图像重建(G-Smeir)方法和D-Smeir方法获得 SPECT图像在不改变低剂量CBCT成像的情况下。以我们在4D时空上的成功为基础 SPECT和CBCT的重建和伪影校正方法及经验收集 1,500多名患者的数据，以及开发真实计算人体幻影的进展 和计算机能力，现在是使用大规模模拟研究来系统评估D-SPECT-MAC的时候了 由一项患者研究支持，为D-SPECT的使用提供急需的证据。我们假设 与D-SPECT-MAC相比，D-SPECT-MAC能显著提高灌注缺损率和左心功能评价 到其他两个方案：流行的呼吸周期平均AC的C-SPECT(C-SPECT-AAC)和 平均AC的新兴D-SPECT(D-SPECT-AAC)。我们的假设将通过以下方式进行检验 具体目标：1)使用大规模模拟研究来评估三种SPECT MPI协议的性能 来自xCAT幻影计划的5,000名虚拟患者；2)开发D-SPECT-MAC用于临床数据和 使用回顾选择的150个患者数据集验证模拟结果。 这个项目的成功将导致无伪影SPECT MPI，它只允许使用一套忠实的 校正MPI图像而不是视觉读取未校正图像和AC图像 实践，从而显著提高诊断的准确性、重复性和临床工作流程。此外， 这个项目将为国际学生联合会代表不足的学生提供专业发展的机会 与医学院的临床合作者一起接受培训并获得宝贵的医学影像研究经验 这为他们追求成功的生物医学事业铺平了道路。

Summary Myocardial perfusion imaging (MPI) using single photon emission computed tomography (SPECT) is a prevalent clinical tool in diagnosis and prognosis of coronal artery disease (CAD). Dual cardiac-respiratory gated SPECT (D-SPECT) has been proposed long ago to eliminate artifacts from patient's cardiac and respiratory motion, but elevated noise and lack of evidence for diagnostic benefit over processing complexity hamper its clinical adoption. Cardiac ECG-gated SPECT (C-SPECT) remains the mainstream enabling the assessment of left-ventricular (LV) functions. Advanced 4D reconstruction with superior denoising ability resurrects interests in D-SPECT recently. Meanwhile, attenuation correction (AC) is essential for quantitative MPI and minimizing false positives. However, AC artifacts can arise when SPECT images are mismatched with attenuation maps derived from the hybrid SPECT/CT scanner. This becomes another major hurdle for D- SPECT because the accompanied cone-beam CT (CBCT) yields only one non-respiratory-gated 3D CT image. To address these issues, we propose a novel SPECT MPI protocol: D-SPECT with motion matched AC (D- SPECT-MAC), which will minimize SPECT MPI artifacts. The motion-matched attenuation maps can be obtained by a general simultaneous motion estimation and image reconstruction (G-SMEIR) method and D- SPECT images without changing low-dose CBCT imaging. Founded on our success on 4D spatiotemporal reconstruction and artifact-correction methods for both SPECT and CBCT and experience collecting D-SPECT data for more than 1,500 patients, with advances in development of realistic computational human phantoms and computer power, it is time to systematically evaluate D-SPECT-MAC using a mass simulation study backed by a patient study to provide the urgently needed evidence for use of D-SPECT. We hypothesize that D-SPECT-MAC can significantly improve perfusion defect detection and LV functional assessment, compared to two other protocols: popular C-SPECT with averaged AC over respiratory cycles (C-SPECT-AAC) and emerging D-SPECT with averaged AC (D-SPECT-AAC). Our hypothesis will be tested through the following specific aims: 1) To evaluate performance of three SPECT MPI protocols using a mass simulation study of 5,000 virtual patients from the XCAT phantom program; 2) To develop D-SPECT-MAC for clinical data and to verify simulation findings using 150 patient data sets retrospectively selected. The success of this project will lead to artifact-free SPECT MPI, which enables use of only one set of faithfully corrected MPI images instead of visual reading both non-corrected and AC images in the current clinical practice, thus significantly improving diagnostic accuracy, reproducibility, and clinical workflow. Furthermore, this project will provide opportunities for under-represented students at the PI's institute to be professionally trained and to gain precious experience on medical imaging research with clinical collaborators at medical institutes, which paves a way for them to pursue a successful biomedical career.