探究64Cu-FAPI-XT PET/CT不同采集条件对图像质量的影响
Exploring the effect of different acquisition conditions of 64Cu-FAPI-XT PET/CT on image quality
陈芃灏 1符乙敏 1赵睿玥 1何曦 1钟少楠 1王欣璐1
作者信息
- 1. 广州医科大学附属第一医院核医学科,广东广州 510000
- 折叠
摘要
目的:探讨在不同采集时间、注射剂量与重建算法下对64Cu-FAPI-XT正电子发射体层成像(positron emission tomography,PET)/计算机体层成像(computed tomography,CT)图像质量的影响,从而为临床实践提供参考.方法:回顾并选取2023年6-9月于广州医科大学附属第一医院行PET/CT检查的11例肿瘤患者,其中6例患者为高剂量组(64Cu-FAPI-XT剂量2.22～3.22 MBq/kg),5例患者为低剂量组(64Cu-FAPI-XT剂量1.59～2.18 MBq/kg).所有患者均在静卧60 min后行PET/CT全身扫描,采集时间均为3.0 min/床位.采用有序子集最大期望值法(ordered subset expectation maximization,OSEM)和贝叶斯惩罚似然重建法(HYPER Iterative)两种算法对3.0 min/床位图像进行时间切割重建,分为以下5组:1.0 min/床位、1.5 min/床位、2.0 min/床位、2.5 min/床位、3.0 min/床位.由2名医师对所有图像进行主观评分,比较不同组图像的图像质量、噪声水平与诊断价值.测量肝脏、纵隔血池的平均标准摄取值(mean standard uptake value,SUVmean)、标准差(standard deviation,SD)和信噪比(signal-to-noise ratio,SNR)以进行半定量分析.结果:主观评价中高剂量组,HYPER Iterative重建与OSEM重建采集2.0 min/床位图像,图像质量能达到日常诊断要求(评分均≥3分).低剂量组,HYPER Iterative重建采集2.0 min/床位图像,或OSEM重建采集2.5 min/床位图像,图像质量能达到日常诊断要求(评分均≥3分).客观半定量分析:在相同采集时间下,注射不同剂量64Cu-FAPI-XT扫描PET图像,HYPER Iterative重建图像质量均明显优于OSEM重建(P＜0.05).在高剂量组中1.5 min/床位组的图像质量明显优于1.0 min/床位组(P＜0.05),而1.5 min/床位组的图像与2.5 min/床位组的图像质量差异无统计学意义(P＞0.05).在低剂量组中2.0 min/床位组与3.0 min/床位组的图像质量差异无统计学意义(P＞0.05).结论:以64Cu-FAPI-XT为显像剂的uMI Panorama PET/CT图像采用HYPER Iterative重建方法的高剂量组需要采集1.5 min/床位PET图像质量可达到日常诊断要求;而在低剂量组中需要采集2.0 min/床位才可达到日常诊断要求.
Abstract
Objective:To explore the influence of different acquisition time,injection dose and reconstruction algorithm on the image quality of 64Cu-FAPI-XT positron emission tomography(PET)/computed tomography(CT),so as to provide empirical basis and reference for clinical practice.Methods:Eleven cancer patients from The First Affiliated Hospital of Guangzhou Medical University from June to September,2023 were retrospectively selected.Six patients were injected with high dose(2.22-3.22 Mbq/kg)of 64Cu-FAPI-XT,while other five patients were injected with low dose(1.59-2.18 Mbq/kg)of 64Cu-FAPI-XT.Ordered subset expectation maximization(OSEM)and HYPER Iterative algorithms were used to reconstruct the 3.0 min/bed image respectively to simulate the image acquisition at 1.0 min/bed,1.5 min/bed,2.0 min/bed,2.5 min/bed and 3.0 min/bed.Two doctors scored all the images subjectively and compared the image quality,noise level and diagnostic value of different groups of images.Mean standard uptake value(SUVmean),standard deviation(SD)and signal-to-noise ratio(SNR)of blood pools in liver and mediastinum were measured for semi-quantitative analysis.Results:Subjective evaluation:in the high-dose group(2.22-3.22 MBq/kg),the images of 2.0 min/bed were reconstructed respectively by HYPER Iterative and OSEM,the image quality of which met the requirements of daily diagnosis(the scores were all≥3 points).In the low-dose group(1.59-2.18 MBq/kg),the image quality of 2.0 min/bed reconstructed by HYPER Iterative and 2.5 min/bed reconstructed by OSEM reached the requirements of daily diagnosis(scores≥3).Objective semi-quantitative analysis:at the same acquisition time,injecting different doses of 64Cu-FAPI-XT to scan PET images,the image quality of HYPER Iterative reconstruction was significantly better than that of OSEM reconstruction(P＜0.05).In the high dose group(2.22-3.22 MBq/kg),the image quality of 1.5 min/bed was obviously better than that of 1.0 min/bed(P＜0.05),but there was no statistical difference between 1.5 min/bed image and 2.5 min/bed image(P＞0.05).There was no statistical difference in image quality between low dose recombinant(1.59-2.18 Mbq/kg)for 2.0 min/bed and 3.0 min/bed(P＞0.05).Conclusion:The PET/CT images of UMI Panorama were reconstructed by HYPER Iterative method,and high dose(2.22-3.22 Mbq/kg)of 64Cu-FAPI-XT was injected,and the quality of PET images collected for 1.5 min/bed met the requirements of daily diagnosis.Low dose(1.59-2.18 Mbq/kg)of 64Cu-FAPI-XT was injected and collected for 2.0 min/bed,which can meet the daily diagnosis requirements.
关键词
64Cu-FAPI-XT/正电子发射体层成像/计算机体层成像/HYPER/Iterative算法/有序子集最大期望值法Key words
64Cu-FAP-XT/Positron emission tomography/Computed tomography/HYPER Iterative algorithm/Ordered subset expectation maximization引用本文复制引用
出版年
2024
NETL
NSTL
万方数据