University of Milan-Bicocca, School of Medicine and Surgery, Milan, Italy.
University of Milan-Bicocca, School of Medicine and Surgery, Milan, Italy.
Phys Med. 2019 Jan;57:177-182. doi: 10.1016/j.ejmp.2018.12.038. Epub 2019 Jan 10.
To investigate influences of reconstruction algorithms and count statistics variation on quantification and treatment response assessment in cancer patients, by using a large field of view-FOV scanner.
54 cancer patients underwent PET/CT scan: 1) at baseline: 1.5 min/FOV, reconstructed by ordered-subset expectation maximization + point-spread-function-OSEM-PSF and bayesian penalised-likelihood-BPL algorithm 2) at restaging: 2 min/FOV, reconstructed also at 1.5 and 1 min/FOV, using OSEM-PSF and BPL. SUL (lean-body mass SUV) peak and max were measured for each target-lesion (n = 59). Differences in quantification obtained from datasets with different reconstruction algorithms and different time/FOV were evaluated. For any pair of PET datasets, metabolic response was assessed by using SULpeak, with a threshold of 30% in variation considered as significant.
Both at baseline and restaging, SULpeak and max values were higher in BPL reconstructions than in OSEM-PSF (p < 0.0001). SULpeak at different time/FOV reconstructions showed no statistically significant differences both with OSEM-PSF and BPL; SULmax depended on acquisition time (p < 0.05). In 56/59 lesions (95%) therapy response was concordant regardless count statistics variation and reconstruction algorithm; 2/59 (3%) showed different responses according to count statistics, both for OSEM-PSF and BPL; in 1/59 lesion (2%) response was different depending on reconstruction algorithm used.
BPL provided higher SULpeak and max than OSEM-PSF. With a large FOV/high sensitivity scanner, variation of time/FOV in restaging PET scans gave stable and reproducible results in terms of SULpeak, both for OSEM-PSF and BPL. Thus, metabolic response defined by SULpeak variation proved to be quite independent from count statistics.
使用大视野（FOV）扫描仪研究重建算法和计数统计变化对癌症患者定量和治疗反应评估的影响。
54 名癌症患者接受了 PET/CT 扫描：1）基线时：1.5 分钟/ FOV，采用有序子集期望最大化+点扩散函数-OSEM-PSF 和贝叶斯惩罚似然-BPL 算法重建；2）在重新分期时：2 分钟/ FOV，也在 1.5 分钟和 1 分钟/ FOV 时使用 OSEM-PSF 和 BPL 重建。对于每个靶病变（n=59），均测量了瘦肉质量 SUV 峰值（SULpeak）和最大值（SULmax）。评估了不同重建算法和不同时间/ FOV 获得的定量数据之间的差异。对于任何一对 PET 数据集，均使用 SULpeak 评估代谢反应，将 30%的变化视为显著。
在基线和重新分期时，BPL 重建的 SULpeak 和 SULmax 值均高于 OSEM-PSF（p<0.0001）。不同时间/ FOV 重建的 SULpeak 在 OSEM-PSF 和 BPL 中均无统计学差异；SULmax 取决于采集时间（p<0.05）。在 56/59 个病变（95%）中，无论计数统计变化和重建算法如何，治疗反应均一致；2/59（3%）个病变根据计数统计结果显示出不同的反应，OSEM-PSF 和 BPL 均如此；在 1/59 个病变（2%）中，反应因使用的重建算法而异。
BPL 提供的 SULpeak 和 SULmax 值高于 OSEM-PSF。使用大 FOV/高灵敏度扫描仪，在重新分期 PET 扫描中，时间/ FOV 的变化为 OSEM-PSF 和 BPL 提供了稳定且可重复的 SULpeak 结果。因此，通过 SULpeak 变化定义的代谢反应与计数统计结果相当独立。
