Kinetic analysis of 3'-deoxy-3'-fluorothymidine PET studies: validation studies in patients with lung cancer.
Kinetic analysis of 3'-deoxy-3'-fluorothymidine PET studies: validation studies in patients with lung cancer.
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2005-02
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通讯作者：
M. Muzi;H. Vesselle;J. Grierson;D. Mankoff;R. Schmidt;L. Peterson;J. Wells;K. Krohn
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作者：
M. Muzi;H. Vesselle;J. Grierson;D. Mankoff;R. Schmidt;L. Peterson;J. Wells;K. Krohn
评估细胞增殖提供了一种直接的方法来测量癌症的体内生长。我们评估了3'-脱氧-3'-(18)f -氟胸苷（(18)F-FLT）动力学模型在肺癌患者FLT PET图像数据分析中的应用。采用区室模型分析来估计肿瘤、骨髓和肌肉中FLT磷酸化的总通量常数（K(FLT)）。将通量估计值与应用于手术切除组织的体外增殖测定（Ki-67）进行比较。将分区建模结果与估算FLT摄取的简单模型无关方法进行了比较。方法17例18个肿瘤部位的患者接受了长达2小时的动态PET和血液采样。血浆样品的代谢物分析校正了标记代谢物的总血液活性，并提供了FLT模型输入函数。对2室4参数模型（4P）进行检验，并与2室3参数模型（3P）进行比较，估算K（FLT）。结果骨髓为增殖性正常组织，K（FLT）值最高，肌肉为非增殖性组织，K（FLT）值最低。通过区室分析估计的肿瘤K（FLT）与修正图形分析估计的肿瘤K（FLT）具有良好的相关性（r = 0.86），与肿瘤平均标准化摄取值的相关性较差（r = 0.62）。与使用4P模型分析的90或120分钟动态数据相比，使用3P模型从60分钟动态PET数据中得出的K（FLT）估计值低估了K（FLT）。通量估计值与细胞增殖的独立测量值的比较表明，K（FLT）与Ki-67高度相关（Spearman rho = 0.92, P < 0.001）。忽略FLT在血液中的代谢产物，低估了K（FLT）高达47%。结论：对FLT PET图像数据的区隔分析得出了与肿瘤增殖的体外测量相关的K（FLT）的可靠估计。该方法经参数误差验证后，可普遍应用于其他不同癌症的影像学研究。磷酸化FLT核苷酸（k(4)）的肿瘤损失是显著的，当使用忽略k(4)的模型独立方法（如图形分析或SUV）评估FLT摄取时，会导致错误。
UNLABELLED Assessing cellular proliferation provides a direct method to measure the in vivo growth of cancer. We evaluated the application of a model of 3'-deoxy-3'-(18)F-fluorothymidine ((18)F-FLT) kinetics described in a companion report to the analysis of FLT PET image data in lung cancer patients. Compartmental model analysis was performed to estimate the overall flux constants (K(FLT)) for FLT phosphorylation in tumor, bone marrow, and muscle. Estimates of flux were compared with an in vitro assay of proliferation (Ki-67) applied to tissue derived from surgical resection. Compartmental modeling results were compared with simple model-independent methods of estimating FLT uptake. METHODS Seventeen patients with 18 tumor sites underwent up to 2 h of dynamic PET with blood sampling. Metabolite analysis of plasma samples corrected the total blood activity for labeled metabolites and provided the FLT model input function. A 2-compartment, 4-parameter model (4P) was tested and compared with a 2-compartment, 3-parameter (3P) model for estimating K(FLT). RESULTS Bone marrow, a proliferative normal tissue, had the highest values of K(FLT), whereas muscle, a nonproliferating tissue, showed the lowest values. The K(FLT) for tumors estimated by compartmental analysis had a fair correlation with estimates by modified graphical analysis (r = 0.86) and a poorer correlation with the average standardized uptake value (r = 0.62) in tumor. Estimates of K(FLT) derived from 60 min of dynamic PET data using the 3P model underestimated K(FLT) compared with 90 or 120 min of dynamic data analyzed using the 4P model. Comparison of flux estimates with an independent measure of cellular proliferation showed that K(FLT) was highly correlated with Ki-67 (Spearman rho = 0.92, P < 0.001). Ignoring the metabolites of FLT in blood underestimated K(FLT) by as much as 47%. CONCLUSION Compartmental analysis of FLT PET image data yielded robust estimates of K(FLT) that correlated with in vitro measures of tumor proliferation. This method can be applied generally to other imaging studies of different cancers after validation of parameter error. Tumor loss of phosphorylated FLT nucleotides (k(4)) is notable and leads to errors when FLT uptake is evaluated using model-independent approaches that ignore k(4), such as graphical analysis or the SUV.