Ferl Gregory Z, Dumont Rebecca A, Hildebrandt Isabel J, Armijo Amanda, Haubner Roland, Reischl Gerald, Su Helen, Weber Wolfgang A, Huang Sung-Cheng
Department of Molecular and Medical Pharmacology, David Geffen School of Medicine at UCLA, University of California, Los Angeles, California 90095-6948, USA.
J Nucl Med. 2009 Feb;50(2):250-8. doi: 10.2967/jnumed.108.054049. Epub 2009 Jan 21.
Radiolabeled arginine-glycine-aspartate (RGD) peptides are increasingly used in preclinical and clinical studies to assess the expression and function of the alphavbeta3 integrin, a cellular adhesion molecule involved in angiogenesis and tumor metastasis formation. To better understand the PET signal obtained with radiolabeled RGD peptides, we have constructed a compartmental model that can describe the time-activity curves in tumors after an intravenous injection.
We analyzed 60-min dynamic PET scans obtained with 64Cu-1,4,7,10-tetraazacyclododecane-N,N',N'',N'''-tetraacetic acid (DOTA)-RGD in 20 tumor-bearing severe combined immunodeficient (SCID) mice after a bolus dose (18,500 kBq [500 microCi]), using variations of the standard 2-compartment (4k) tissue model augmented with a compartment for irreversible tracer internalization. alphavbeta3 binding sites were blocked in 5 studies with a coinjection of cold peptide. In addition, 20 h after injection, static PET was performed on 9 of 20 mice. We fitted 2k (k3=k4=0), 3k (k4=0), 4k, and 4kc (k4=constant) models to the PET data and used several criteria to determine the best model structure for describing 64Cu-DOTA-RGD kinetics in mice. Akaike information criteria (AIC), calculated from model fits and the ability of each model to predict tumor concentration 20 h after tracer injection, were considered.
The 4kc model has the best profile in terms of AIC values and predictive ability, and a constant k4 is further supported by Logan-Patlak analysis and results from iterative Bayesian parameter estimation. The internalization compartment allows quantification of the putative tracer internalization rate for each study, which is estimated here to be approximately an order of magnitude less than k3 and thus does not confound the apparent specific binding of the tracer to the tumor integrin during the first 60 min of the scan. Analysis of specific (S) and nonspecific or nondisplaceable (ND) binding using fitted parameter values showed that the 4kc model provided expected results when comparing alphavbeta3 blocked and nonblocked studies. That is, specific volume of distribution, [VS=(K1k3)/(k2k4)], is much higher than is nondisplaceable volume of distribution, [VND=(K1/k2)], in nonblocking studies (2.2+/-0.6 vs. 0.85+/-0.14); VS and VND are about the same in the blocking studies (0.46+/-1.6 vs. 0.56+/-0.09). Also, the ratio of static tumor and plasma measurements at 60 and 10 min [CT(60)/CP(10)] is highly correlated (RS=0.92) to tumor VS.
We have developed and tested a compartmental model for use with the 64Cu-DOTA-RGD PET tracer and demonstrated its potential as a tool for analysis and design of preclinical and clinical imaging studies.
放射性标记的精氨酸 - 甘氨酸 - 天冬氨酸(RGD)肽越来越多地用于临床前和临床研究,以评估αvβ3整合素的表达和功能,αvβ3整合素是一种参与血管生成和肿瘤转移形成的细胞粘附分子。为了更好地理解放射性标记的RGD肽获得的PET信号,我们构建了一个房室模型,该模型可以描述静脉注射后肿瘤中的时间 - 活度曲线。
我们分析了20只荷瘤严重联合免疫缺陷(SCID)小鼠在给予大剂量(18,500 kBq [500 μCi])后用64Cu - 1,4,7,10 - 四氮杂环十二烷 - N,N',N'',N''' - 四乙酸(DOTA) - RGD获得的60分钟动态PET扫描,使用标准的两房室(4k)组织模型的变体,并增加了一个用于不可逆示踪剂内化的房室。在5项研究中通过共同注射冷肽来阻断αvβ3结合位点。此外,注射后20小时,对20只小鼠中的9只进行静态PET检查。我们将2k(k3 = k4 = 0)、3k(k4 = 0)、4k和4kc(k4 =常数)模型拟合到PET数据,并使用几个标准来确定描述小鼠中64Cu - DOTA - RGD动力学的最佳模型结构。考虑了根据模型拟合计算的赤池信息准则(AIC)以及每个模型预测示踪剂注射后20小时肿瘤浓度的能力。
就AIC值和预测能力而言,4kc模型具有最佳表现,并且Logan - Patlak分析和迭代贝叶斯参数估计的结果进一步支持了常数k4。内化房室允许对每项研究中假定的示踪剂内化率进行量化,在此估计其比k3大约小一个数量级,因此在扫描的前60分钟内不会混淆示踪剂与肿瘤整合素的表观特异性结合。使用拟合参数值分析特异性(S)和非特异性或不可置换性(ND)结合表明,在比较αvβ3阻断和未阻断研究时,4kc模型提供了预期结果。也就是说,在非阻断研究中,特异性分布容积[VS =(K1k3)/(k2k4)]远高于不可置换分布容积[VND =(K1 / k2)](2.2±0.6对0.85±0.14);在阻断研究中VS和VND大致相同(0.46±1.6对0.56±0.09)。此外,60分钟和10分钟时静态肿瘤与血浆测量值的比值[CT(60)/ CP(10)]与肿瘤VS高度相关(RS = 0.92)。
我们开发并测试了一种用于64Cu - DOTA - RGD PET示踪剂的房室模型,并证明了其作为临床前和临床成像研究分析和设计工具的潜力。