Biomedical Engineering Program, Faculty of Engineering, Chulalongkorn University, Bangkok, Thailand.
Chulalongkorn University Biomedical Imaging Group, Department of Radiology, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand.
Ann Nucl Med. 2022 Jan;36(1):24-32. doi: 10.1007/s12149-021-01680-x. Epub 2021 Sep 24.
Previously, a joint ictal/inter-ictal SPECT reconstruction was proposed to reconstruct a differential image representing the change of brain SPECT image from an inter-ictal to an ictal study. The so-called joint method yielded better performance for epileptic foci localization than the conventional subtraction method. In this study, we evaluated the performance of different reconstruction settings of the joint reconstruction of ictal/inter-ictal SPECT data, which creates a differential image showing the difference between ictal and inter-ictal images, in lesion detection and localization in epilepsy imaging.
Differential images reconstructed from phantom data using the joint and the subtraction methods were compared based on lesion detection performance (channelized Hotelling observer signal-to-noise ratio (SNR) averaged across four lesion-to-background contrast levels) at the optimal iteration. The joint-initial method which was the joint method that was initialized by the subtraction method at optimal iteration was also used to reconstruct differential images. These three methods with respective optimal iteration and the subtraction method with four iterations were applied to epileptic patient datasets. A human observer lesion localization study was performed based on localization receiver operating characteristic (LROC) analysis.
From the phantom study, at their respective optimal iteration, the joint method yielded an improvement in lesion detection performance over the subtraction method of 26%, which increased to 145% when using the joint-initial method. From the patient study, the joint-initial method yielded the highest area under the LROC curve as compared with those of the joint and the subtraction methods with optimal iteration and with 4 iterations (0.44 vs 0.41, 0.39 and 0.36, respectively).
In lesion detection and localization, the joint method at optimal iteration outperformed the subtraction method at optimal iteration and at iteration typically used in clinical practice. Furthermore, initialization by the subtraction method improved the performance of the joint method.
之前提出了一种发作期/发作间期 SPECT 联合重建方法，用于重建从发作间期到发作期研究的脑 SPECT 图像变化的差分图像。与传统的减影法相比，所谓的联合法在癫痫灶定位方面表现出更好的性能。在这项研究中，我们评估了发作期/发作间期 SPECT 数据联合重建的不同重建设置在癫痫成像中的病灶检测和定位中的性能，该方法创建了一个差分图像，显示发作期和发作间期图像之间的差异。
基于病变检测性能（在四个病变与背景对比水平的最优迭代处，通道化 Hotelling 观察者信噪比 (SNR) 的平均值），比较了使用联合和减影方法从体模数据重建的差分图像。还使用联合-初始方法（即最优迭代处通过减影法初始化的联合方法）来重建差分图像。将这三种方法（各自的最优迭代）和减影法（四次迭代）应用于癫痫患者数据集。基于定位接收器操作特征 (LROC) 分析进行了人类观察者病变定位研究。
从体模研究中可以看出，在各自的最优迭代处，联合方法的病变检测性能比减影法提高了 26%，当使用联合-初始方法时，提高了 145%。从患者研究中可以看出，与联合和减影法的最优迭代和四次迭代相比，联合-初始法的 LROC 曲线下面积最高（分别为 0.44 比 0.41、0.39 和 0.36）。
在病灶检测和定位方面，最优迭代处的联合方法优于最优迭代处的减影法和临床常用的迭代次数。此外，通过减影法初始化可以提高联合方法的性能。
