Kinetic Modeling and Graphical Analysis of 18F-Fluoromethylcholine (FCho), 18F-Fluoroethyltyrosine (FET) and 18F-Fluorodeoxyglucose (FDG) PET for the Fiscrimination between High-Grade Glioma and Radiation Necrosis in Rats
Kinetic Modeling and Graphical Analysis of 18F-Fluoromethylcholine (FCho), 18F-Fluoroethyltyrosine (FET) and 18F-Fluorodeoxyglucose (FDG) PET for the Fiscrimination between High-Grade Glioma and Radiation Necrosis in Rats
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DOI：
10.1371/journal.pone.0161845
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发表时间：
2016-08-25
期刊：
影响因子：
3.7
通讯作者：
Goethals, Ingeborg
中科院分区：
文献类型：
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作者：
Bolcaen, Julie;Lybaert, Kelly;Goethals, Ingeborg
背景胶质母细胞瘤（GB）和放射性坏死（RN）之间的区别仍然具有挑战性，但对进一步的治疗和预后有很大的影响。在这项研究中，18F-FDG的摄取机制，18F-氟乙基酪氨酸（18F-FET）和18F-氟甲基胆碱应用动力学模型（KM）和图形分析（GA）在F98 GB和RN大鼠模型中研究了（18F-FCho）正电子发射断层扫描（PET）示踪剂，以澄清我们以前的结果。18F-FET（GB n = 5，RN n = 5）和18F-FCho PET（GB n = 5，RN n = 5）。结果通过2房室模型（CM）或Patlak GA描述的18F-FDG摄取的内流率（Ki）显示GB（0.07 min（-1））比RN（0.04 min（-1））具有更多的捕获（k（3））（p = 0.017）。GB中18F-FET的K-1（0.06 ml/ccm/min）显著高于RN（0.02 ml/ccm/min），使用1-CM和Logan GA进行定量（p = 0.036）。18F-FCho迅速氧化，使数据解释复杂化。使用1-CM和Logan GA没有明显的差异被发现区分GB从RN.ConclusionsBased我们的研究结果，我们得出结论，使用KM和GA 18F-FDG和18F-FET都能够区分GB从RN。使用2-CM模型，与RN相比，在GB中发现更多的18F-FDG捕获。其次，使用1-CM模型，GB中18F-FET的内流高于RN。SUV与18F-FDG和18F-FET的动力学或图形测量之间存在重要相关性。18F-FCho PET不允许区分GB和RN。
BackgroundDiscrimination between glioblastoma (GB) and radiation necrosis (RN) post-irradiation remains challenging but has a large impact on further treatment and prognosis. In this study, the uptake mechanisms of 18F-fluorodeoxyglucose (18F-FDG), 18F-fluoroethyltyrosine (18F-FET) and 18F-fluoromethylcholine (18F-FCho) positron emission tomography (PET) tracers were investigated in a F98 GB and RN rat model applying kinetic modeling (KM) and graphical analysis (GA) to clarify our previous results.MethodsDynamic 18F-FDG (GB n = 6 and RN n = 5), 18F-FET (GB n = 5 and RN n = 5) and 18F-FCho PET (GB n = 5 and RN n = 5) were acquired with continuous arterial blood sampling. Arterial input function (AIF) corrections, KM and GA were performed.ResultsThe influx rate (Ki) of 18F-FDG uptake described by a 2-compartmental model (CM) or using Patlak GA, showed more trapping (k(3)) in GB (0.07 min(-1)) compared to RN (0.04 min(-1)) (p = 0.017). K-1 of 18F-FET was significantly higher in GB (0.06 ml/ccm/min) compared to RN (0.02 ml/ccm/min), quantified using a 1-CM and Logan GA (p = 0.036). 18F-FCho was rapidly oxidized complicating data interpretation. Using a 1-CM and Logan GA no clear differences were found to discriminate GB from RN.ConclusionsBased on our results we concluded that using KM and GA both 18F-FDG and 18F-FET were able to discriminate GB from RN. Using a 2-CM model more trapping of 18F-FDG was found in GB compared to RN. Secondly, the influx of 18F-FET was higher in GB compared to RN using a 1-CM model. Important correlations were found between SUV and kinetic or graphical measures for 18F-FDG and 18F-FET. 18F-FCho PET did not allow discrimination between GB and RN.