Onwanna Jaruwan, Chantadisai Maythinee, Chaiwatanarat Tawatchai, Rakvongthai Yothin
Biomedical Engineering Program, Faculty of Engineering, Chulalongkorn University, Bangkok, Thailand.
Chulalongkorn University Biomedical Imaging Group, Faculty of Medicine, Department of Radiology, Chulalongkorn University, Bangkok, Thailand.
Nucl Med Mol Imaging. 2023 Jun;57(3):126-136. doi: 10.1007/s13139-022-00787-x. Epub 2023 Jan 16.
We assessed the lesion detection performance of the dual-tracer parathyroid SPECT imaging using the joint reconstruction method.
Thirty-six noise realizations were created from SPECT projections collected from an in-house neck phantom to emulate Tc-pertechnetate/Tc-sestamibi parathyroid SPECT datasets. Difference images representing parathyroid lesions were reconstructed using the subtraction and the joint methods whose corresponding optimal iteration was defined as the iteration which maximized the channelized Hotelling observer signal-to-noise ratio (CHO-SNR). The joint method whose initial estimate was derived from the subtraction method at optimal iteration (the joint-AltInt method) was also assessed. In a study of 36 patients, a human-observer lesion-detection study was performed using difference images from the three methods at optimal iteration and the subtraction method with four iterations. The area under the receiver operating characteristic curve (AUC) was calculated for each method.
In the phantom study, both the joint-AltInt method and the joint method improved SNR compared to the subtraction method at their optimal iteration by 444% and 81%, respectively. In the patient study, the joint-AltInt method yielded the highest AUC of 0.73 as compared with 0.72, 0.71, and 0.64 from the joint method, the subtraction method at optimal iteration, and the subtraction method at four iterations. At a specificity of at least 0.70, the joint-AltInt method yielded significantly higher sensitivity than the other methods (0.60 vs 0.46, 042, and 0.42; < 0.05).
The joint reconstruction method yielded higher lesion detectability than the conventional method and holds promise for dual-tracer parathyroid SPECT imaging.
我们使用联合重建方法评估了双示踪剂甲状旁腺SPECT成像的病变检测性能。
从内部颈部模型采集的SPECT投影中创建36个噪声实现,以模拟高锝酸盐/锝-司他比甲状旁腺SPECT数据集。使用减法和联合方法重建代表甲状旁腺病变的差异图像,其相应的最佳迭代定义为使通道化霍特林观察者信噪比(CHO-SNR)最大化的迭代。还评估了初始估计值来自最佳迭代减法方法的联合方法(联合-AltInt方法)。在一项对36例患者的研究中,使用三种方法在最佳迭代时的差异图像以及四次迭代的减法方法进行了人工观察者病变检测研究。计算每种方法的受试者操作特征曲线下面积(AUC)。
在模型研究中,联合-AltInt方法和联合方法在最佳迭代时的信噪比分别比减法方法提高了444%和81%。在患者研究中,联合-AltInt方法的AUC最高,为0.73,而联合方法、最佳迭代减法方法和四次迭代减法方法的AUC分别为0.72、0.71和0.64。在特异性至少为0.70时,联合-AltInt方法的灵敏度显著高于其他方法(0.60对0.46、0.42和0.42;P<0.05)。
联合重建方法比传统方法具有更高的病变可检测性,在双示踪剂甲状旁腺SPECT成像方面具有前景。