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HRRT与SIGNA PET/MRI系统的PET组件之间的交叉验证研究,重点为神经成像。

Cross-validation study between the HRRT and the PET component of the SIGNA PET/MRI system with focus on neuroimaging.

作者信息

Mannheim Julia G, Cheng Ju-Chieh Kevin, Vafai Nasim, Shahinfard Elham, English Carolyn, McKenzie Jessamyn, Zhang Jing, Barlow Laura, Sossi Vesna

机构信息

Department of Physics and Astronomy, University of British Columbia, Vancouver, British Columbia, Canada.

Werner Siemens Imaging Center, Department of Preclinical Imaging and Radiopharmacy, Eberhard-Karls University Tuebingen, Tuebingen, Germany.

出版信息

EJNMMI Phys. 2021 Feb 26;8(1):20. doi: 10.1186/s40658-020-00349-0.

DOI:10.1186/s40658-020-00349-0
PMID:33635449
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7910400/
Abstract

BACKGROUND

The Siemens high-resolution research tomograph (HRRT - a dedicated brain PET scanner) is to this day one of the highest resolution PET scanners; thus, it can serve as useful benchmark when evaluating performance of newer scanners. Here, we report results from a cross-validation study between the HRRT and the whole-body GE SIGNA PET/MR focusing on brain imaging. Phantom data were acquired to determine recovery coefficients (RCs), % background variability (%BG), and image voxel noise (%). Cross-validation studies were performed with six healthy volunteers using [C]DTBZ, [C]raclopride, and [F]FDG. Line profiles, regional time-activity curves, regional non-displaceable binding potentials (BP) for [C]DTBZ and [C]raclopride scans, and radioactivity ratios for [F]FDG scans were calculated and compared between the HRRT and the SIGNA PET/MR.

RESULTS

Phantom data showed that the PET/MR images reconstructed with an ordered subset expectation maximization (OSEM) algorithm with time-of-flight (TOF) and TOF + point spread function (PSF) + filter revealed similar RCs for the hot spheres compared to those obtained on the HRRT reconstructed with an ordinary Poisson-OSEM algorithm with PSF and PSF + filter. The PET/MR TOF + PSF reconstruction revealed the highest RCs for all hot spheres. Image voxel noise of the PET/MR system was significantly lower. Line profiles revealed excellent spatial agreement between the two systems. BP values revealed variability of less than 10% for the [C]DTBZ scans and 19% for [C]raclopride (based on one subject only). Mean [F]FDG ratios to pons showed less than 12% differences.

CONCLUSIONS

These results demonstrated comparable performances of the two systems in terms of RCs with lower voxel-level noise (%) present in the PET/MR system. Comparison of in vivo human data confirmed the comparability of the two systems. The whole-body GE SIGNA PET/MR system is well suited for high-resolution brain imaging as no significant performance degradation was found compared to that of the reference standard HRRT.

摘要

背景

西门子高分辨率研究断层扫描仪(HRRT——一款专用脑部正电子发射断层扫描仪)至今仍是分辨率最高的正电子发射断层扫描仪之一;因此,在评估新型扫描仪的性能时,它可作为有用的基准。在此,我们报告一项在HRRT与通用电气全身SIGNA PET/MR之间进行的交叉验证研究结果,重点是脑部成像。采集了体模数据以确定恢复系数(RC)、背景变异百分比(%BG)和图像体素噪声(%)。使用[C]DTBZ、[C]雷氯必利和[F]氟代脱氧葡萄糖对六名健康志愿者进行了交叉验证研究。计算并比较了HRRT与SIGNA PET/MR之间的线轮廓、区域时间-活度曲线、[C]DTBZ和[C]雷氯必利扫描的区域不可置换结合电位(BP)以及[F]氟代脱氧葡萄糖扫描的放射性比值。

结果

体模数据显示,采用飞行时间(TOF)和TOF + 点扩散函数(PSF) + 滤波器的有序子集期望最大化(OSEM)算法重建的PET/MR图像,与采用带PSF和PSF + 滤波器的普通泊松-OSEM算法重建的HRRT图像相比,热球的RC相似。PET/MR的TOF + PSF重建显示所有热球的RC最高。PET/MR系统的图像体素噪声显著更低。线轮廓显示两个系统之间具有出色的空间一致性。[C]DTBZ扫描的BP值变化小于10%,[C]雷氯必利扫描的BP值变化为19%(仅基于一名受试者)。平均[F]氟代脱氧葡萄糖与脑桥的比值差异小于12%。

结论

这些结果表明,两个系统在RC方面具有可比的性能,PET/MR系统中的体素级噪声(%)更低。体内人体数据的比较证实了两个系统的可比性。通用电气全身SIGNA PET/MR系统非常适合高分辨率脑部成像,因为与参考标准HRRT相比,未发现明显的性能下降。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0147/7910400/42d7bcb2b687/40658_2020_349_Fig9_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0147/7910400/699758ec9c1e/40658_2020_349_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0147/7910400/fb5e3834d6ae/40658_2020_349_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0147/7910400/459a54ee57da/40658_2020_349_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0147/7910400/3495f018830c/40658_2020_349_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0147/7910400/643959ed6734/40658_2020_349_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0147/7910400/4565189fea96/40658_2020_349_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0147/7910400/ce0639aef5f6/40658_2020_349_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0147/7910400/99641be21fb9/40658_2020_349_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0147/7910400/42d7bcb2b687/40658_2020_349_Fig9_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0147/7910400/699758ec9c1e/40658_2020_349_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0147/7910400/fb5e3834d6ae/40658_2020_349_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0147/7910400/459a54ee57da/40658_2020_349_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0147/7910400/3495f018830c/40658_2020_349_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0147/7910400/643959ed6734/40658_2020_349_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0147/7910400/4565189fea96/40658_2020_349_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0147/7910400/ce0639aef5f6/40658_2020_349_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0147/7910400/99641be21fb9/40658_2020_349_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0147/7910400/42d7bcb2b687/40658_2020_349_Fig9_HTML.jpg

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