Analysis of [68Ga]-DOTA-E-[c(RGDfK)]2

[68Ga]-DOTA-E-[c(RGDfK)]2 is a radioligand for PET imaging of αvβ3 integrin. It was synthesized and evaluated preclinically by Janssen et al (2002) and Dijkgraaf et al (2011), and the tracer is reviewed in MICAD by Leung. Tracer was seen to accumulate in tumour, and the binding was confirmed to be specific by co-injection of cold ligand.

Analysis methods

Currently, there are no reports on modelling or data analysis beyond SUV calculation for [68Ga]-DOTA-E-[c(RGDfK)]2, but several studies regarding other αvβ3 integrin tracers.

Two-tissue compartment model with five parameters (K1, k2, k3, k4, and VB) and plasma input has been found to best represent the measured tissue concentration curves (Ferl et al., 2009; Guo et al., 2012a; Kim et al., 2013), although reliability of model parameters may need to be improved by constraining some of the parameters, like setting k4 to a constant value (Ferl et al., 2009). Variability in model rate constants may not necessary be a major problem since the final outcome, representing receptor density, is the macroparameter VT (total volume of distribution), also marked with Vd.

The VT has also been calculated using MTGA for reversible uptake (Logan plot); the result correlated well with the VT from compartmental model analysis (Guo et al., 2012a; Kim et al., 2013; Kiugel et al., 2014). Logan plot analysis is a robust and fast method, and it has therefore been applied to compute parametric images with labeled RGD peptides (Guo et al., 2012a; Kim et al., 2013; Kiugel et al., 2014).

VT is the sum of distribution volumes of specific and nonspecific (nondisplaceable) binding (VS and VND, respectively), the VS and VND have been estimated separately from compartment model results and validated with blocking studies (Ferl et al., 2009):

Rate of internalization was assumed to be zero (Ferl et al., 2009).

The binding potential, BPND, has been calculated using Logan plot with reference tissue input; muscle was used as reference region in case of tumour studies (Zhang et al., 2006; Guo et al., 2012b; Zhu et al., 2012). Logan plot with reference input provides distribution volume ratio (DVR):

If we assume that there is no specific binding in the reference region, and that the nonspecific binding is similar in reference region and region of interest, then BPND is related to the concentration of available receptors (B'max) and the affinity of tracer to the receptor (1/KD):

In mice studies (Zhang et al., 2006) the binding potential was found to correlate well with Bmax results from autoradiography and reasonable correlation was also found with electrophoresis studies. Zhang et al. used 26.5 min as the starting point for linear regression in the Logan plot analysis.

Analysis using compartmental models and Logan plot requires that dynamic PET data is obtained. Ferl et al (2009) proposed using a simple ratio method requiring only static PET scan at 60 min after injection and plasma activity measurement at 10 min after injection. The ratio CPET(60)/CPlasma(10) was found to correlate well with VS in tumours. Beer et al (2005) used tumour-to-blood ratios. Even more simple method, tumour-to-background ratio at 60 min, showed similar correlations with Bmax as Logan plot (Zhang et al, 2006), although the authors still were in favour of Logan plot if dynamic scanning is possible.

Model input

Image-derived input

Ferl et al (2009) estimated whole-blood concentration curve from ROI drawn on the left ventricle of the heart in mice PET studies with [64Cu]-DOTA-RGD. Image-derived blood curve was then corrected for recovery error with a fixed coefficient (in this study 0.7, but the correction factor is dependent on the PET scanner, reconstruction method, and distribution of the tracer). Blood curve was converted to plasma assuming that haematocrit in mice is 0.5, that is, blood curve was divided by 0.5 (Ferl et al., 2009).

Protein binding

Dijkgraaf et al (2011) reported that plasma protein binding is low, <5%. RGD peptides are also very hydrophilic.


[68Ga]-DOTA-E-[c(RGDfK)]2, like most integrin tracers, is rapidly excreted through kidneys in its parent form. Uptake in kidneys and liver is high, compared to blood. Kidneys, lung, liver, and colon express β3 integrins, and part of uptake in these tissues is caused by specific binding.

Radioactive metabolites in plasma

The parent tracer [68Ga]-DOTA-E-[c(RGDfK)]2 is the main radioactive constituent in the plasma at least 45 min after injection in rats. After that one radioactive metabolite appears in plasma, but still one hour p.i. the contribution of parent tracer is about 2/3 of the total radioactivity in the plasma. The late appearance of metabolite in plasma may be caused by metabolism in the liver and enterohepatic circulation. In vitro stability of [68Ga]-DOTA-E-[c(RGDfK)]2 and related tracers is very good, also in human serum (Dijkgraaf et al., 2011), suggesting that metabolite analysis is reliable.

See also:


Alam IS, Witney TH, Tomasi G, Carroll L, Twyman FJ, Nguyen QD, Aboagye EO. Radiolabeled RGD tracer kinetics annotates differential αvβ3 integrin expression linked to cell intrinsic and vessel expression. Mol Imaging Biol. 2014; 16(4): 558-566. doi: 10.1007/s11307-013-0710-3.

Beer AJ, Haubner R, Goebel M, Luderschmidt S, Spilker ME, Wester H-J, Weber WA, Schwaiger M. Biodistribution and pharmacokinetics of the αvβ3-selective tracer 18F-galacto-RGD in cancer patients. J Nucl Med. 2005; 46: 1333-1341. PMID: 16085591.

Dijkgraaf I, Yim CB, Franssen GM, Schuit RC, Luurtsema G, Liu S, Oyen WJ, Boerman OC. PET imaging of αvβ3 integrin expression in tumours with Ga-labelled mono-, di- and tetrameric RGD peptides. Eur J Nucl Med Mol Imaging 2011; 38(1): 128–137. doi: 10.1007/s00259-010-1615-x.

Ferl GZ, Dumont RA, Hildebrandt IJ, Armijo A, Haubner R, Reischl G, Su H, Weber WA, Haung S-C. Derivation of a compartmental model for quantifying 64Cu-DOTA-RGD kinetics in tumor-bearing mice. J Nucl Med. 2009; 50: 250-258. doi: 10.2967/jnumed.108.054049.

Guo N, Lang L, Gao H, Niu G, Kiesewetter DO, Xie Q, Chen X. Quantitative analysis of 18F-labeled monomeric and dimeric RGD peptides using compartmental model. Mol Imaging Biol. 2012a; 14: 743-752. doi: 10.1007/s11307-012-0541-7.

Guo N, Lang L, Li W, Kiesewetter DO, Gao H, Niu G, Xie Q, Chen X. Quantitative analysis and comparison study of [18F]AIF-NOTA-PRGD2, [18F]FPPRGD2 and [68Ga]Ga-NOTA-PRGD2 using a reference tissue model. PLoS ONE 2012b; 7(5): e37506. doi: 10.1371/journal.pone.0037506.

Janssen ML, Oyen WJ, Dijkgraaf I, Massuger LF, Frielink C, Edwards DS, Rajopadhye M, Boonstra H, Corstens FH, Boerman OC. Tumor targeting with radiolabeled αvβ3 integrin binding peptides in a nude mouse model. Cancer Res. 2002; 62(21): 6146–6151. PMID: 12414640.

Kim JH, Kim YH, Kim YJ, Yang BY, Jeong JM, Youn H, Lee DS, Lee JS. Quantitative positron emission tomography imaging of angiogenesis in rats with forelimb ischemia using 68Ga-NOTA-c(RGDyK). Angiogenesis 2013; 16(4): 837-846. doi: 10.1007/s10456-013-9359-4.

Kiugel M, Dijkgraaf I, Kytö V, Helin S, Liljenbäck H, Saanijoki T, Yim C-B, Oikonen V, Saukko P, Knuuti J, Roivainen A, Saraste A. Dimeric [68Ga]DOTA-RGD peptide targeting αvβ3 integrin reveals extracellular matrix alterations after myocardial infarction. Mol Imaging Biol. 2014; 16(6): 793-801. doi: 10.1007/s11307-014-0752-1.

Leung K. 68Ga-Tetraazacyclododecane-N,N',N'',N'''-tetraacetic acid-Glu-[cyclo(Arg-Gly-Asp-D-Phe-Lys)]2. In: Molecular Imaging and Contrast Agent Database (MICAD) [Internet].

Niu G, Chen X. PET imaging of angiogenesis. PET Clin. 2009; 4(1): 17-38. doi: 10.1016/j.cpet.2009.04.011.

Zhang X, Xiong Z, Wu Y, Cai W, Tseng JR, Gambhir SS, Chen X. Quantitative PET imaging of tumor integrin αvβ3 expression with 18F-FRGD2. J Nucl Med. 2006; 47: 113-121. PMID: 16391195.

Zhu L, Guo N, Li Q, Ma Y, Jacobson O, Lee S, Choi HS, Mansfield JR, Niu G, Chen X. Dynamic PET and optical imaging and compartment modeling using a dual-labeled cyclic RGD peptide probe. Theranostics 2012; 2(8): 746-756. doi: 10.7150/thno.4762.

Tags: , , ,

Updated at: 2014-10-31
Created at: 2013-06-13
Written by: Vesa Oikonen