Choi Nu Ri, Rahman Md Ashequr, Yu Zitong, Siegel Barry A, Jha Abhinav K
Department of Computer Science & Engineering, Washington University, St. Louis, MO, USA.
Department of Biomedical Engineering, Washington University, St. Louis, MO, USA.
Proc SPIE Int Soc Opt Eng. 2024 Feb;12929. doi: 10.1117/12.3006924. Epub 2024 Mar 29.
Myocardial perfusion imaging using single-photon emission computed tomography (SPECT), or myocardial perfusion SPECT (MPS) is a widely used clinical imaging modality for the diagnosis of coronary artery disease. Current clinical protocols for acquiring and reconstructing MPS images are similar for most patients. However, for patients with outlier anatomical characteristics, such as large breasts, images acquired using conventional protocols are often sub-optimal in quality, leading to degraded diagnostic accuracy. Solutions to improve image quality for these patients outside of increased dose or total acquisition time remain challenging. Thus, there is an important need for new methodologies that can help improve the quality of the acquired images for such patients, in terms of the ability to detect myocardial perfusion defects. One approach to improving this performance is adapting the image acquisition protocol specific to each patient. Studies have shown that in MPS, different projection angles usually contain varying amounts of information for the detection task. However, current clinical protocols spend the same time at each projection angle. In this work, we evaluated whether an acquisition protocol that is optimized for each patient could improve performance on the task of defect detection on reconstructed images for patients with outlier anatomical characteristics. For this study, we first designed and implemented a personalized patient-specific protocol-optimization strategy, which we term precision SPECT (PRESPECT). This strategy integrates the theory of ideal observers with the constraints of tomographic reconstruction to optimize the acquisition time for each projection view, such that performance on the task of detecting myocardial perfusion defects is maximized. We performed a clinically realistic simulation study on patients with outlier anatomies on the task of detecting perfusion defects on various realizations of low-dose scans by an anthropomorphic channelized Hotelling observer. Our results show that using PRESPECT led to improved performance on the defect detection task for the considered patients. These results provide evidence that personalization of MPS acquisition protocol has the potential to improve defect detection performance on reconstructed images by anthropomorphic observers for patients with outlier anatomical characteristics. Thus, our findings motivate further research to design optimal patient-specific acquisition and reconstruction protocols for MPS, as well as developing similar approaches for other medical imaging modalities.
使用单光子发射计算机断层扫描（SPECT）的心肌灌注成像，即心肌灌注SPECT（MPS），是一种广泛应用于冠状动脉疾病诊断的临床成像方式。目前，大多数患者获取和重建MPS图像的临床方案相似。然而，对于具有异常解剖特征的患者，如乳房较大者，使用传统方案获取的图像质量往往欠佳，导致诊断准确性下降。在不增加剂量或总采集时间的情况下，提高这些患者图像质量的解决方案仍然具有挑战性。因此，迫切需要新的方法来帮助提高此类患者采集图像的质量，特别是在检测心肌灌注缺损的能力方面。提高这种性能的一种方法是根据每个患者的情况调整图像采集方案。研究表明，在MPS中，不同的投影角度通常包含用于检测任务的不同信息量。然而，当前的临床方案在每个投影角度花费相同的时间。在这项工作中，我们评估了针对每个患者优化的采集方案是否能提高具有异常解剖特征患者重建图像上的缺损检测任务的性能。对于本研究，我们首先设计并实施了一种个性化的、针对患者的方案优化策略，我们称之为精准SPECT（PRESPECT）。该策略将理想观察者理论与断层重建的约束条件相结合，以优化每个投影视图的采集时间，从而使心肌灌注缺损检测任务的性能最大化。我们对具有异常解剖结构的患者进行了一项临床逼真的模拟研究，该研究任务是通过拟人化通道化霍特林观察者在各种低剂量扫描的情况下检测灌注缺损。我们的结果表明，使用PRESPECT可提高所考虑患者在缺损检测任务上的性能。这些结果证明，MPS采集方案的个性化有可能提高拟人化观察者对具有异常解剖特征患者重建图像的缺损检测性能。因此，我们的研究结果促使进一步开展研究，以设计针对MPS的最佳患者特异性采集和重建方案，并为其他医学成像模态开发类似方法。
