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新型心肌PET显像剂F-FPTP参数映射算法的比较评估

Comparative evaluation of the algorithms for parametric mapping of the novel myocardial PET imaging agent F-FPTP.

作者信息

Kim Ji Who, Seo Seongho, Kim Hyeon Sik, Kim Dong-Yeon, Lee Ho-Young, Kang Keon Wook, Lee Dong Soo, Bom Hee-Seung, Min Jung-Joon, Lee Jae Sung

机构信息

Department of Nuclear Medicine, Seoul National University College of Medicine, Daehak-ro 101, Chongnogu, Seoul, 03080, Korea.

Department of Cardiology, Chonnam National University Hwasun Hospital, 160 Ilsimri, Hwasun, 519-809, Jeonnam, Korea.

出版信息

Ann Nucl Med. 2017 Jul;31(6):469-479. doi: 10.1007/s12149-017-1171-6. Epub 2017 Apr 25.

DOI:10.1007/s12149-017-1171-6
PMID:28444503
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5486518/
Abstract

OBJECTIVE

(F-fluoropentyl)triphenylphosphonium salt (F-FPTP) is a new promising myocardial PET imaging tracer. It shows high accumulation in cardiomyocytes and rapid clearance from liver. We performed compartmental analysis of F-FPTP PET images in rat and evaluated two linear analyses: linear least-squares (LLS) and a basis function method (BFM) for generating parametric images. The minimum dynamic scan duration for kinetic analysis was also investigated and computer simulation undertaken.

METHODS

F-FPTP dynamic PET (18 min) and CT images were acquired from rats with myocardial infarction (MI) (n = 12). Regions of interest (ROIs) were on the left ventricle, normal myocardium, and MI region. Two-compartment (K and k ; 2C2P) and three-compartment (K -k ; 3C3P) models with irreversible uptake were compared for goodness-of-fit. Partial volume and spillover correction terms (V and α = 1 - V ) were also incorporated. LLS and BFM were applied to ROI- and voxel-based kinetic parameter estimations. Results were compared with the standard ROI-based nonlinear least-squares (NLS) results of the corresponding compartment model. A simulation explored statistical properties of the estimation methods.

RESULTS

The 2C2P model was most suitable for describing F-FPTP kinetics. Average K , k , and V values were, respectively, 6.8 (ml/min/g), 1.1 (min), and 0.44 in normal myocardium and 1.4 (ml/min/g), 1.1 (min), and 0.32, in MI tissue. Ten minutes of data was sufficient for the estimation. LLS and BFM estimations correlated well with NLS values for the ROI level (K : y = 1.06x + 0.13, r  = 0.96 and y = 1.13x + 0.08, r  = 0.97) and voxel level (K : y = 1.22x - 0.30, r  = 0.90 and y = 1.26x + 0.00, r  = 0.92). Regional distribution of kinetic parametric images (αK , K , k , V ) was physiologically relevant. LLS and BFM showed more robust characteristics than NLS in the simulation.

CONCLUSIONS

Fast kinetics and highly specific uptake of F-FPTP by myocardium enabled quantitative analysis with the 2C2P model using only the initial 10 min of data. LLS and BFM were feasible for estimating voxel-wise parameters. These two methods will be useful for quantitative evaluation of F-FPTP distribution in myocardium and in further studies with different conditions, disease models, and species.

摘要

目的

(F - 氟戊基)三苯基鏻盐(F - FPTP)是一种新型且有前景的心肌PET成像示踪剂。它在心肌细胞中显示出高积聚,且从肝脏快速清除。我们对大鼠的F - FPTP PET图像进行了房室分析,并评估了两种线性分析方法:线性最小二乘法(LLS)和用于生成参数图像的基函数法(BFM)。还研究了动力学分析的最短动态扫描持续时间并进行了计算机模拟。

方法

从患有心肌梗死(MI)的大鼠(n = 12)获取F - FPTP动态PET(18分钟)和CT图像。感兴趣区域(ROI)位于左心室、正常心肌和MI区域。比较了具有不可逆摄取的两房室(K 和k ;2C2P)和三房室(K - k ;3C3P)模型的拟合优度。还纳入了部分容积和溢出校正项(V 和α = 1 - V )。将LLS和BFM应用于基于ROI和体素的动力学参数估计。将结果与相应房室模型基于标准ROI的非线性最小二乘法(NLS)结果进行比较。通过模拟探索了估计方法的统计特性。

结果

2C2P模型最适合描述F - FPTP动力学。正常心肌中的平均K 、k 和V 值分别为6.8(ml/min/g)、1.1(min)和0.44,MI组织中的平均K 、k 和V 值分别为1.4(ml/min/g)、1.1(min)和0.32。十分钟的数据就足以进行估计。在ROI水平(K :y = 1.06x + 0.13,r = 0.96和y = 1.13x + 0.08,r = 0.97)和体素水平(K :y = 1.22x - 0.30,r = 0.90和y = 1.26x + 0.00,r = 0.92),LLS和BFM估计值与NLS值具有良好的相关性。动力学参数图像(αK 、K 、k 、V )的区域分布具有生理相关性。在模拟中,LLS和BFM显示出比NLS更稳健的特性。

结论

心肌对F - FPTP的快速动力学和高特异性摄取使得仅使用最初10分钟的数据就能通过2C2P模型进行定量分析。LLS和BFM对于估计体素级参数是可行的。这两种方法将有助于定量评估F - FPTP在心肌中的分布,并用于不同条件、疾病模型和物种的进一步研究。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/296d/5486518/f0273e609b64/12149_2017_1171_Fig7_HTML.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/296d/5486518/f0273e609b64/12149_2017_1171_Fig7_HTML.jpg
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