Kangasmaa Tuija S, Constable Chris, Sohlberg Antti O
Department of Clinical Physiology and Nuclear Medicine, Vaasa Central Hospital, Hietalahdenkatu 2-4, 65130, Vaasa, Finland.
HERMES Medical Solutions, Strandbergsgatan 16, 11251, Stockholm, Sweden.
EJNMMI Phys. 2021 Jan 6;8(1):2. doi: 10.1186/s40658-020-00348-1.
Bone SPECT/CT has been shown to offer superior sensitivity and specificity compared to conventional whole-body planar scanning. Furthermore, bone SPECT/CT allows quantitative imaging, which is challenging with planar methods. In order to gain better quantitative accuracy, Bayesian reconstruction algorithms, including both image derived and anatomically guided priors, have been utilized in reconstruction in PET/CT scanning, but they have not been widely used in SPECT/CT studies. Therefore, the aim of this work was to evaluate the performance of CT-guided reconstruction in quantitative bone SPECT.
Three Bayesian reconstruction methods were evaluated against the conventional ordered subsets expectation maximization (OSEM) reconstruction method. One of the studied Bayesian methods was the relative difference prior (RDP), which has recently gained popularity in PET reconstruction. The other two methods, anatomically guided smoothing prior (AMAP-S) and anatomically guided relative difference prior (AMAP-R), utilized anatomical information from the CT scan. The reconstruction methods were evaluated in terms of quantitative accuracy with artificial lesions inserted in clinical patient studies and with 20 real clinical patients. Maximum and mean standardized uptake values (SUVs) of the lesions were defined.
The analyses showed that all studied Bayesian methods performed better than OSEM and the anatomical priors also outperformed RDP. The average relative error in mean SUV for the artificial lesion study for OSEM, RDP, AMAP-S, and AMAP-R was - 53%, - 35%, - 15%, and - 10%, when the CT study had matching lesions. In the patient study, the RDP method gave 16 ± 9% higher maximum SUV values than OSEM, while AMAP-S and AMAP-R offered increases of 36 ± 8% and 36 ± 9%, respectively. Mean SUV increased for RDP, AMAP-S, and AMAP-R by 18 ± 9%, 26 ± 5%, and 33 ± 5% when compared to OSEM.
The Bayesian methods with anatomical prior, especially the relative difference prior-based method (AMAP-R), outperformed OSEM and reconstruction without anatomical prior in terms of quantitative accuracy.
与传统的全身平面扫描相比,骨SPECT/CT已显示出更高的灵敏度和特异性。此外,骨SPECT/CT允许进行定量成像,而平面方法在这方面具有挑战性。为了获得更好的定量准确性,包括图像衍生先验和解剖学引导先验的贝叶斯重建算法已被用于PET/CT扫描的重建中,但它们在SPECT/CT研究中尚未得到广泛应用。因此,本研究的目的是评估CT引导重建在定量骨SPECT中的性能。
将三种贝叶斯重建方法与传统的有序子集期望最大化(OSEM)重建方法进行比较评估。所研究的贝叶斯方法之一是相对差异先验(RDP),它最近在PET重建中受到欢迎。另外两种方法,解剖学引导平滑先验(AMAP-S)和解剖学引导相对差异先验(AMAP-R),利用了CT扫描的解剖学信息。通过在临床患者研究中插入人工病变以及对20名真实临床患者进行评估,从定量准确性方面对重建方法进行了评价。定义了病变的最大和平均标准化摄取值(SUV)。
分析表明,所有研究的贝叶斯方法均比OSEM表现更好,并且解剖学先验方法也优于RDP。当CT研究中有匹配病变时,在人工病变研究中,OSEM、RDP、AMAP-S和AMAP-R的平均SUV相对误差分别为-53%、-35%、-15%和-10%。在患者研究中,RDP方法给出的最大SUV值比OSEM高16±9%,而AMAP-S和AMAP-R分别提高了36±8%和36±9%。与OSEM相比,RDP、AMAP-S和AMAP-R的平均SUV分别增加了18±9%、26±5%和33±5%。
具有解剖学先验的贝叶斯方法,特别是基于相对差异先验的方法(AMAP-R),在定量准确性方面优于OSEM和无解剖学先验的重建方法。