Taniguchi Takafumi, Akamatsu Go, Kasahara Yukiko, Mitsumoto Katsuhiko, Baba Shingo, Tsutsui Yuji, Himuro Kazuhiko, Mikasa Shohei, Kidera Daisuke, Sasaki Masayuki
Division of Medical Quantum Science, Department of Health Sciences, Graduate School of Medical Sciences, Kyushu University, 3-1-1 Maidashi, Higashi-ku, Fukuoka, 812-8582, Japan.
Ann Nucl Med. 2015 Jan;29(1):71-7. doi: 10.1007/s12149-014-0912-z. Epub 2014 Sep 26.
The aim of this study was to evaluate the effect of the point spread function (PSF) and time of flight (TOF) on PET/CT images of overweight patients in relation to the iteration number and the acquisition time.
This study consisted of a phantom study and a clinical study. The NEMA IEC body phantom and a 40 cm diameter large phantom (LG phantom) simulating an overweight patient were used in this study. Both phantoms were filled with (18)F solution with a sphere to background ratio of 4:1. The PET data were reconstructed with the baseline ordered-subsets expectation maximization (OSEM) algorithm, with the OSEM + PSF model, with the OSEM + TOF model and with the OSEM + PSF + TOF model. The clinical study was a retrospective analysis of 66 patients who underwent (18)F-FDG PET/CT. The image quality was evaluated using the background variability (coefficient of variance, CVphantom and CVliver) and the contrast (CONTHOT and SNR).
In phantom study, the CVphantom of the LG phantom was higher than that of the NEMA phantom. The PSF decreased the CVphantom of the LG phantom to the NEMA phantom level. The TOF information accelerated the CVphantom plateau earlier. The best relationship between the CVphantom and the CONTHOT was observed for the OSEM + PSF + TOF. In clinical study, the combination of PSF and TOF decreased the CVliver for overweight patients to that for normal weight patients while it increased the SNR similarly between two patient groups.
The combination of the PSF and TOF correction improved the image quality of the LG phantom and overweight patients.
本研究旨在评估点扩散函数(PSF)和飞行时间(TOF)对超重患者PET/CT图像的影响,并与迭代次数和采集时间相关联。
本研究包括一项体模研究和一项临床研究。本研究使用了NEMA IEC体模和一个模拟超重患者的直径40厘米的大体模(LG体模)。两个体模均填充有(18)F溶液,球体与背景的比例为4:1。PET数据采用基线有序子集期望最大化(OSEM)算法、OSEM + PSF模型、OSEM + TOF模型以及OSEM + PSF + TOF模型进行重建。临床研究是对66例接受(18)F-FDG PET/CT检查的患者进行的回顾性分析。使用背景变异性(变异系数,CV体模和CV肝脏)和对比度(CONTHOT和SNR)评估图像质量。
在体模研究中,LG体模的CV体模高于NEMA体模。PSF将LG体模的CV体模降低到NEMA体模水平。TOF信息使CV体模平台更早出现。对于OSEM + PSF + TOF,观察到CV体模与CONTHOT之间的最佳关系。在临床研究中,PSF和TOF的组合将超重患者的CV肝脏降低到正常体重患者的水平,同时在两个患者组之间类似地提高了SNR。
PSF和TOF校正的组合改善了LG体模和超重患者的图像质量。