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MODERATE CDK INHIBITORS TO POTENTIAL ANTITUMOR DRUGS 23. Vashisht Gopal, Y. N.; Konuru, N.; Kondapi, A. K. Arch. Biochem. Biophys. 2002
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616 MODERATE CDK INHIBITORS TO POTENTIAL ANTITUMOR DRUGS 23. Vashisht Gopal, Y. N.; Konuru, N.; Kondapi, A. K. Arch. Biochem. Biophys. 2002, 401 , 53. 24. Zeglis, B. M.; Divilov, V.; Lewis, J. S. J. Med. Chem. 2011, 54 , 2391. 25. Kurzwernhart, A.; Kandioller, W.; Bartel, C.; B¨achler, S.; Trondl, R.; M¨uhlgassner, G.; Jakupec, M. A.; Arion, V. B.; Marko, D.; Keppler, B. K.; Hartinger, C. G. Chem. Commun. 2012, 48 , 4839. 26. Shang, Y. Nat. Rev. Cancer 2006, 6 , 360. 27. Kasiotis, K. M.; Haroutounian, S. A. Curr. Org. Chem. 2012, 16 , 335. 28. Polyak, K.; Vogt, P. K. Proc. Natl. Acad. Sci. U.S.A. 2012, 109 , 2715. 29. Nguyen, A.; Vessi`eres, A.; Hillard, E. A.; Top, S.; Pigeon, P.; Jaouen, G. Chimia 2007, 61 , 716. 30. Malumbres, M.; Barbacid, M. Nat. Rev. Cancer 2001, 1 , 222. 31. Malumbres, M.; Barbacid, M. Nat. Rev. Cancer 2009, 9 , 153. 32. Kelland, L. R. Expert Opin. Investig. Drugs 2000, 9 , 2903. 33. MacPhillamy, H. B.; Dziemian, R. L.; Lucas, R. A.; Kuehne, M. E. J. Am. Chem. Soc. 1958, 80 , 2172. 34. Kunick, C. Arch. Pharm. (Weinheim) 1992, 325 , 297. 35. Sausville, E. A.; Zaharevitz, D.; Gussio, R.; Meijer, L.; Louarn-Leost, M.; Kunick, C.; Schultz, R.; Lahusen, T.; Headlee, D.; Stinson, S.; Arbuck, S. G.; Senderowicz, A. Pharmacol. Ther. 1999, 82 , 285. 36. Zaharevitz, D. W.; Gussio, R.; Leost, M.; Senderowicz, A.; Lahusen, T.; Kunick, C.; Meijer, L.; Sausville, E. A. Cancer Res. 1999, 59 , 2566. 37. Gussio, R.; Zaharevitz, D. W.; McGrath, C. F.; Pattabiraman, N.; Kellogg, G. E.; Schultz, C.; Link, A.; Kunick, C.; Leost, M.; Meijer, L.; Sausville, E. A. Anticancer Drug Des. 2000, 15 , 53. 38. McGrath, C. F.; Pattabiraman, N.; Kellogg, G. E.; Lemcke, T.; Kunick, C.; Sausville, E. A.; Zaharevitz, D. W.; Gussio, R. J. Biomol. Struct. Dyn. 2005, 22 , 493. 39. Schultz, C.; Link, A.; Leost, M.; Zaharevitz, D. W.; Gussio, R.; Sausville, E. A.; Meijer, L.; Kunick, C. J. Med. Chem. 1999, 42 , 2909. 40. Leost, M.; Schultz, C.; Link, A.; Wu, Y.-Z.; Biernat, J.; Mandelkow, E.-M.; Bibb, J. A.; Snyder, G. L.; Greengard, P.; Zaharevitz, D. W.; Gussio, R.; Senderowicz, A. M.; Sausville, E. A.; Kunick, C.; Meijer, L. Eur. J. Biochem. 2000, 267 , 5983. 41. Hartinger, C. G.; Zorbas-Seifried, S.; Jakupec, M. A.; Kynast, B.; Zorbas, H.; Keppler, B. K. J. Inorg. Biochem. 2006, 100 , 891. 42. Jakupec, M. A.; Galanski, M.; Arion, V. B.; Hartinger, C. G.; Keppler, B. K. Dalton Trans. 2008, 37 , 183. 43. Reisner, E.; Arion, V. B.; Keppler, B. K.; Pombeiro, A. J. L. Inorg. Chim. Acta 2008, 361 , 1569. 44. Kandioller, W.; Kurzwernhart, A.; Hanif, M.; Meier, S. M.; Henke, H.; Keppler, B. K.; Hartinger, C. G. J. Organomet. Chem. 2011,
45. Jungwirth, U.; Kowol, C. R.; Keppler, B. K.; Hartinger, C. G.; Berger, W.; Heffeter, P. Antioxid. Redox Signal. 2011, 15 , 1085. 46. Schmid, W. F.; Zorbas-Seifried, S.; John, R. O.; Arion, V. B.; Jakupec, M. A.; Roller, A.; Galanski, M.; Chiorescu, I.; Zorbas, H.; Keppler, B. K. Inorg. Chem. 2007, 46 , 3645. 47. Milunovic, M. N. M.; Enyedy, E. A.; Nagy, N. V.; Kiss, T.; Trondl, R.; Jakupec, M. A.; Keppler, B. K.; Krachler, R.; Novitchi, G.; Arion, V. B. Inorg. Chem. 2012, 51 , 9309. 48. Smith, G. S.; Therrien, B. Dalton Trans. 2011, 40 , 10793. 49. Chellan, P.; Land, K. M.; Shokar, A.; Au, A.; An, S. H.; Clavel, C. M.; Dyson, P. J.; de Kock, C.; Smith, P. J.; Chibale, K.; Smith, G. S. Organometallics 2012, 31 , 5791. 50. West, D. X.; Padhye, S. B.; Sonawane, P. B. Structure and Bonding 1991, 76 , 1. 51. Farrel, N. Coord. Chem. Rev. 2002, 232 , 1. 52. Beraldo, H.; Gambino, D. Mini Rev. Med. Chem. 2004, 4 , 31. 53. Hughes, M. N. The Inorganic Chemistry of Biological Processes; John Wiley & Sons, Ltd: Chichester, 1981. 54. Dobrov, A.; Arion, V. B.; Kandler, N.; Ginzinger, W.; Jakupec, M. A.; Rufi´nska, A.; Graf von Keyserlingk, N.; Galanski, M.; Kowol, C.; Keppler, B. K. Inorg. Chem. 2006, 45 , 1945. 55. Ginzinger, W.; Arion, V. B.; Giester, G.; Galanski, M.; Keppler, B. K. Cent. Eur. J. Chem. 2008, 6 , 340. 56. Schmid, W. F.; John, R. O.; M¨uhlgassner, G.; Heffeter, P.; Jakupec, M. A.; Galanski, M.; Berger, W.; Arion, V. B.; Keppler, B. K.
57. Arion, V. B.; Dobrov, A.; G¨oschl, S.; Jakupec, M. A.; Keppler, B. K.; Rapta, P. Chem. Commun. 2012, 48 , 8559. 58. Schmid, W. F.; John, R. O.; Arion, V. B.; Jakupec, M. A.; Keppler, B. K. Organometallics 2007, 26 , 6643. 59. Primik, M. F.; M¨uhlgassner, G.; Jakupec, M. A.; Zava, O.; Dyson, P. J.; Arion, V. B.; Keppler, B. K. Inorg. Chem. 2010, 49 , 302. 60. M¨uhlgassner, G.; Bartel, C.; Schmid, W. F.; Jakupec, M. A.; Arion, V. B.; Keppler, B. K. J. Inorg. Biochem. 2012, 116 , 180. 61. Lavrado, J.; Moreira, R.; Paulo, A. Curr. Med. Chem. 2010, 17 , 2348. REFERENCES 617 62. Zhou, J.-L.; Lu, Y.-J.; Ou, T.-M.; Zhou, J.-M.; Huang, Z.-S.; Zhu, X.-F.; Du, C.-J.; Bu, X.-Z.; Ma, L.; Gu, L.-Q.; Li, Y.-M.; Chan, A. S.-C. J. Med. Chem. 2005, 48 , 7315. 63. Hu, X.-W.; Chien, C.-M.; Yang, S.-H.; Lin, Y.-H.; Lu, C.-M.; Chen, Y.-L.; Lin, S.-R. Cell Biol. Toxicol. 2006, 22 , 417. 64. Yang, S.-H.; Chien, C.-M.; Lu, C.-M.; Chen, Y.-L.; Chang, L.-S.; Lin, S.-R. Leuk. Res. 2007, 31 , 1413. 65. Chien, C.-M.; Yang, S.-H.; Lin, K.-L.; Chen, Y.-L.; Chang, L.-S.; Lin, S.-R. Chem. Biol. Interact. 2008, 176 , 40. 66. Tzeng, C.-C.; Chen, Y.-L.; Lin, J.-J.; Lu, C.-M.; U.S. Patent Appl. U.S. 0,298,846, 2009. 67. Bergman, J.; Engqvist, R.; St˚alhandske, C.; Wallberg, H. Tetrahedron 2003, 59 , 1033. 68. Filak, L. K.; M¨uhlgassner, G.; Jakupec, M. A.; Heffeter, P.; Berger, W.; Arion, V. B.; Keppler, B. K. J. Biol. Inorg. Chem. 2010, 15 , 903.
69. Filak, L. K.; M¨uhlgassner, G.; Bacher, F.; Roller, A.; Galanski, M.; Jakupec, M. A.; Keppler, B. K.; Arion, V. B. Organometallics 2011, 30 , 273. 70. Filak, L. K.; G¨oschl, S.; Hackl, S.; Jakupec, M. A.; Arion, V. B. Inorg. Chim. Acta 2012, 393 , 252. 71. Primik, M. F.; G¨oschl, S.; Jakupec, M. A.; Roller, A.; Keppler, B. K.; Arion, V. B. Inorg. Chem. 2010, 49 , 11084. 72. Haley, B.; Frenkel, E. Urol. Oncol. 2008, 26 , 57. 73. Hawkins, M. J.; Soon-Shiong, P.; Desai, N. Adv. Drug Deliv. Rev. 2008, 60 , 876. 74. Cho, K.; Wang, X.; Nie, S.; Chen Z.; Shin, D. M. Clin. Cancer Res. 2008, 14 , 1310. 75. Haag, R.; Kratz, F. Angew. Chem. Int. Ed. 2006, 45 , 1198. 76. Sanchez-Cano, C.; Hannon, M. J. Dalton Trans. 2009, 10702. 77. Kratz, F. J. Control. Release 2008, 132 , 171. 78. Ang, W. H.; Daldini, E.; Juillerat-Jeanneret, L.; Dyson, P. J. Inorg. Chem. 2007, 46 , 9048. 79. Ang W. H.; Casini, A.; Sava, G.; Dyson, P. J. J. Organomet. Chem. 2011, 989. 80. Stepanenko, I. N.; Casini, A.; Edafe, F.; Novak, M. S.; Arion, V. B.; Dyson, P. J.; Jakupec, M. A.; Keppler, B. K. Inorg. Chem. 2011, 50 , 12669. 81. Meunier, B. Angew. Chem. Int. Ed. 2012, 51 , 8702. 82. Swensen, N.; Walton, J. G. A.; Bradley, M. Trends Pharmacol. Sci. 2012, 33 , 186. 83. Laakkonen, P.; Vuorinena, K. Integr. Biol. 2010, 2 , 326. 84. Sugahara, K. N.; Teesalu, T.; Karmali, P. P.; Kotamraju, V. R.; Agemy, L.; Greenwald, D. R.; Ruoslahti, E. Science 2010, 328 , 1031. 85. Porkka, K.; Laakkonen, P.; Hoffman, J. A.; Bernasconi, M.; Ruoslahti, E. Proc. Natl. Acad. Sci. U.S.A. 2002, 99 , 7444. 86. Christian, S.; Pilch, J.; Akerman, M. E.; Porkka, K.; Laakkonen, P.; Ruoslahti, E. J. Cell Biol. 2003, 163 , 871. 87. Gelain, F.; Silva, D.; Caprini, A.; Taraballi, F.; Natalello, A.; Villa, O.; Nam, K. T.; Zuckermann, R. N.; Diglia, S. M.; Vescovi, A. ACS Nano 2011, 5 , 1845. 88. Van Rijt, S. H.; Kostrhunova, H.; Brabec, V.; Sadler, P. J. Bioconjug. Chem. 2011, 218. 89. Noor, F.; Wustholz, A.; Kinscherf, R.; Metzler-Nolte, N. Angew. Chem. Int. Ed. 2005, 44 , 2429. 90. Paterson, B. M.; Karas, J. A.; Scanlon, D. B.; White, J. M.; Donnelly, P. S. Inorg. Chem. 2010, 49 , 1884. 91. Ma, M. T.; Karas, J. A.; White, J. M.; Scanlon, D.; Donnelly, P. S. Chem. Commun. 2009, 3237. 92. Ma, M. T.; Cooper, M. S.; Paul, R. L.; Shaw, K. P.; Karas, J. A.; Scanlon, D.; White, J. M.; Blower, P. J.; Donnelly, P. S. Inorg. Chem. 2011, 50 , 6701. 93. Driessens, G.; Beck, B.; Caauwe, A.; Simons, B. D.; Blanpain, C. Nature 2012, 488 , 527. 94. Chen, J.; Li, Y.; Yu, T.-S.; McKay, R. M.; Burns, D. K.; Kernie, S. G.; Parada, L. F. Nature 2012, 488 , 522. 95. Schepers, A. G. Science 2012, 337 , 730. 96. Baker, M. Nature 2012, 488 , 13.
46 METAL-BASED CHELATES AND NANOSYSTEMS AS MRI CONTRAST AGENTS Sara Figueiredo Department of Life Sciences, University of Coimbra, Coimbra, Portugal Carlos F. G. C. Geraldes* Department of Life Sciences, University of Coimbra, Coimbra, Portugal; Center of Neurosciences and Cell Biology, University of Coimbra, Coimbra, Portugal; Coimbra Chemistry Center, University of Coimbra, Coimbra, Portugal 46.1 INTRODUCTION Molecular imaging deals with all the noninvasive imaging techniques that are able to detect and characterize biological processes, at the cellular and/or molecular level, thus allowing higher insights to be achieved from them. It is based on the single or combined use of different imaging techniques, such as optical imaging (OI; bioluminescence and fluorescence), ultrasounds, photoacoustic imaging (PAI), magnetic resonance imaging (MRI), magnetic resonance spectroscopy (MRS), nuclear medicine positron-emission tomography (PET), or single photon-emission computed tomography (SPECT) [1–3]. PET and SPECT are the most sensitive imaging techniques and use a number of radioactive tracers that are already available for experimental and clinical applications. However, patient exposure to ionizing radiation is a major drawback that, together with its inherent low spatial resolution, makes it less favorable than other imaging tools such as MRI. Unfortunately, the gain in resolution associated with an MRI is accompanied by a loss in sensitivity, which is a problem that has been tackled with the use of contrast agents (CAs), endowed with very high relaxivity, or resorting to nanotechnological tools [4]. A recent improvement in imaging modalities is the development of hybrid systems, in which the use of multimodality probes exploits the best characteristics of each system. Nowadays, imaging scanners tend to house different modalities, combining PET/CT (computed tomography) and even PET/MRI. Together with the design of new purposely tailored imaging probes, the hybrid scanners overcome the drawbacks and limitations of a single technique, thus considerably improving the overall diagnostic potential of the procedure. Over the past 10 years, models derived from nanotechnology have been used to overcome the limitations of conventional modalities, thus improving the sensitivity and accuracy of the diagnosis. Moreover, advances in nanoparticle (NP) technology have given rise to theragnostics platforms, defined as the combination of therapeutic and diagnostic agents in a single particle. These techniques unite early diagnosis and possible higher efficiency treatment methods. Typical platforms include liposomes, polymeric micelles, and dendrimers that generally accommodate surface functionalization with hydrophilic polymers and targeting ligands. Despite success in evaluating the expression of molecular markers, the imaging of the same with an MRI
First Edition. Edited by Armando J. L. Pombeiro. © 2014 John Wiley & Sons, Inc. Published 2014 by John Wiley & Sons, Inc.
620 METAL-BASED CHELATES AND NANOSYSTEMS AS MRI CONTRAST AGENTS remains a challenge mainly because of the technique’s low sensitivity. Considerable endeavor has been made in order to overcome this drawback and the encapsulation of MRI CAs in nanocarriers emerges as a strategy of great potential. This review emphasizes the importance of MRI as an imaging tool through the use of probes for enhanced MR imaging via particles as carriers for conventional CAs. 46.2 MAGNETIC RESONANCE IMAGING MRI is an outstanding noninvasive technology that allows the acquisition of anatomic images with exceptional spatial resolution. The acquisition of images uses the properties of nuclear magnetic resonance (NMR) and among all the NMR active nuclei (such as 13 C,
F, 31 P, 15 N, and
29 Si)
1 H is the most commonly used nucleus in routine MRI because of its high abundance in the human body, essentially as hydrogen atoms in water molecules. The intensity of the NMR signal is proportional to the energy difference between the two energy states of the nucleus in the external magnetic field B o , and therefore, the strength of B o strongly affects the MR image. Its increase causes an enhancement in the signal-to-noise ratio (SNR), and consequently, a higher signal per voxel allows the achievement of better spatial resolution, which leads to the final outcome of high-quality images. MR signal intensity is affected by three major parameters, namely, the proton density (PD) in a given region, the longitudinal relaxation time T 1 , and the transverse relaxation time T 2 . PD concerns the concentration of protons in a given region and T 1 and T 2 relaxation times are the time constants of the processes by which the longitudinal and transverse magnetization components, respectively, return to their equilibrium values as protons revert to their resting state, after a stimulatory radio frequency (RF) pulse. These proton characteristics reflect the local mobility of water molecules, which may change according to the tissue nature and can be different in healthy or pathological regions [5]. The differences in those parameters can be used to create image contrast in the region of interest (ROI) [6].
Although PD, T 1 , and T 2 are primary determinants of the contrast, it can be enhanced by means of applying proper pulse sequences [7–11]. Manipulating certain operational parameters (such as the repetition time T R and the echo time T E ), it is
possible to acquire three main types of MR images, namely, PD, T 1 -weighted, and T 2 -weighted images. In a T 1 -weighted image, the contrast is mainly because of differences in the T 1 values of tissues. To create this effect, both short T E and T R are necessary. When long T R is used, the tissues in a given region (e.g., water vs fat) would have already totally recovered their magnetization over the period, and so no contrast would be observed. Thus, when using short values of T R , the signal in regions with short T 1 is more intense (brighter image) than in regions with long T 1 (darker image). On the other hand, in a T 2 -weighted image, T E controls the contrast. Consequently, to perceive contrast, which depends on the transverse relaxation mechanism, a long T E must be employed thus allowing the different T 2 decays of the spins to be discriminated. If a short T E is used, almost no decay takes place and consequently no differences are detected. Thus, when short values of T E are
used, the signal coming from regions with short T 2 is less intense (darker image) than that in regions with long T 2 (brighter image). Finally, in a PD image, the effects of T 1 and T 2 are minimized and the contrast is solely dependent on the number of protons in the ROI. Therefore, a sequence with long T R (minimizing the T 1 -weighting) and short T E (reducing the T 2 effect) is used. In this case, almost all the regions of a brain are colored the same way, with the exception of the skull that presents lower PD. However, sometimes, the inherent contrast in the MR image is insufficient for the proper characterization of the tissue, even after applying the proper pulse sequences. Therefore, in these cases, the application of CAs is required in order to amplify the contrast differences between healthy and pathological regions, with the final achievement of improved diagnosis and, consequently, the outcome for the patient health. 46.4 CONTRAST AGENTS MRI CAs are paramagnetic substances that are able to modify signal intensity by altering the relaxation times of water protons in the area where they distribute. CAs are in general referred as T 1 or T 2 agents according to whether they predominantly affect the longitudinal or the transverse relaxation time. The concept of molecules that are able to change water relaxation times comes from the early times of MRI, when Bloch showed that Fe(NO 3 ) 3 had the ability to decrease water proton T 1 and T 2 [12]. Later in 1978, Paul Lauterbur considered T 1 CONTRAST AGENTS 621 paramagnetic ions as CAs, showing the potential of manganese chloride in myocardial infarction imaging, in rats and dogs [13]. However, by this time, the toxic effect of free metal ions was already known and therefore the use of stable chelate complexes was indicated as the way to reduce this effect. Actually, in the mid-1980s, [Gd(DTPA)] 2– (H
DTPA = diethylenetriaminepentaacetic acid) was proposed as a CA in clinical studies [14]. The efficiency of a particular CA is expressed by its relaxivity, r i , which corresponds to its capacity to shorten the relaxation rates R
= 1/T i of the water protons and is usually normalized to 1 μM CA concentration [CA] (Eq. 46.1) [15] R i = R dia
+ r i [CA] (i = 1, 2). (46.1)
where R dia
is the contribution measured for the system containing the same medium and a diamagnetic analog of the CA. 46.5 T 1 CONTRAST AGENTS CAs that affect T 1 are also called positive CAs, because of their ability to virtually increase the signal intensity in the T 1 -weighted images. After Lauterbur’s in vivo experiments [13], it has become clear that free Mn 2 + was highly toxic to living beings and so other paramagnetic metal ions, since then, have been considered for MR imaging. Other paramagnetic ions such as Gd 3 +
3 + , among others, are still being continuously studied. Gadolinium(III) (Gd 3 + ) is one of the most frequently used lanthanides because of its particularly favorable characteristics. With seven unpaired electrons and long electron spin relaxation, it has a high effect on nuclei T 1 relaxation times. Nevertheless, as is the case of all other lanthanides, the use of this metal ion in its free form is not compatible with in vivo use, as it is extremely toxic, even in low doses. In 1984, Laniado et al. [16] reported the first in vivo use of a Gd 3 + complex, [Gd(DTPA)] 2– , a CA that was approved for clinical application in 1988. Nowadays, complexes containing gadolinium are among the most popular CAs used regularly in Medicine, and the ligands that complex the metal ion are mainly DTPA or DOTA (1,4,7,10-tetraazacyclododecane-1,4,7,10- tetraacetic acid) derivatives. In Table 46.1, the major characteristics of several clinically approved CAs are represented.
a
1 -Relaxivity in Generic Registered Plasma, s –1 •mM –1 , Schematic Name Name
Abbreviation Manufacturer 1.5 T Representation Gadobutrol Gadovist
Gd-BT-DO3A Bayer
5.2 O O N N N N O OH OH OH OH 2 Gd O O O Gadodiamide Omniscan Gd-DTPA-BMA GE Healthcare 4.3 NH
N N N H H O O O O Gd O O
O O O Gadopentate dimeglumine Magnevist Gd-DTPA
Bayer 4.1
O O− O− O− O O Gd 3+ N N N O O O O (continued ) 622 METAL-BASED CHELATES AND NANOSYSTEMS AS MRI CONTRAST AGENTS TABLE 46.1 (Continued) T 1 -Relaxivity in Generic Registered Plasma, s –1 •mM –1 , Schematic Name Name
Abbreviation Manufacturer 1.5 T Representation Gadoterate meglumine Dotarem Gd-DOTA
Guerbet 3.6
O O O O O O N N N N Gd O O OH 2 Gadoteridol ProHance
Gd-HPDO3A Bracco
4.1 O O O O O O OH 2 OH N N N N Gd Gadoversetamine Optimark
Gd-DTPA-BMEA Mallinckrodt 4.7 O
O O O O O O O O O NH NH N N N H H Gd Gadobenate dimeglumine MultiHance Gd-BOPTA Bracco
6.3 O O O O O O O O− O− O− − O − O N N N H H Gd 3+ Gadoxetate disodium Eovist
Gd-EOB-DTPA Bayer
6.9 O O O O N N N O O O− O− O− O− O− a Adapted from Reference 17. T 1 CONTRAST AGENTS 623 As mentioned earlier, the efficiency of a particular CA is expressed by its relaxivity, r i (i = 1,2) and commercially available Gd 3 + CAs have relaxivities of circa 4–5 s –1. mM
at typical clinical magnetic field strengths (e.g., 1.5 T, Table 46.1), consequently inducing poor enhancement in an MR image. Thus, the main challenge presented to chemists in the field has been to design CAs with higher relaxivities that are able to concentrate in specific regions of the body or to respond to certain physiological stimuli. A good CA should be highly stable and have the capacity to enhance the relaxation rate of the solvent protons to their potential maxima. The total relaxivity of a Gd 3 + complex consists of the additive contributions from its inner-sphere, outer-sphere, and, sometimes, second-sphere water molecules. CA relaxivity optimization can be achieved by increasing the efficiency of several of the molecular parameters that determine the relaxivity of its inner-sphere contribution. These include the number of water molecules coordinated to the metal ion (q), the exchange lifetime of those water molecules ( τ M ), and the reorientational correlation time ( τ R ) of the complex [15]. The number of water molecules in the first coordination sphere (q) is typically equal to one because of the octadenticity of the ligands normally used and the fact that the Gd 3 + ion generally hosts nine donor atoms in its coordination sphere. This type of coordination scheme allows the formation of highly stable complexes that prevent the leakage of the metal ion [18]. Several groups have been extensively working on the preparation of coordination cages leading to Gd 3 + complexes with a higher q number and, consequently, improved relaxivity. Examples of these highly sensitive CAs have been prepared by Raymond’s group using the hexadentate HOPO (tripodal hydroxypyridinone ligand) or related ligands (e.g., HOPO-TAM), with six oxygen donor atoms, thus allowing the coordination of two (and even three) water molecules. Other solutions are represented by the use of ligands such as PCTA-[12] (3,6,9,15-tetraazabicyclo[9.3.1]pentadeca-1(15),11,13-triene-3,6,9-triacetate), DO3A (1,4,7,10-tetraazacyclododecane-tris acetic acid), or AAZTA (6-amino-6-methylperhydro-1,4-diazepinetetraacetic acid), as shown in the Fig. 46.1 [15, 18–22]. The molecular rotational correlation time, τ R
extensive internal flexibility is not present) higher molecular weight induces a lengthening of the τ R and consequently the relaxivity is higher at magnetic fields of 0.5–1.5 T. A great deal of effort has been made in order to increase the τ R parameter, for instance, by covalently or noncovalently binding the complexes to macromolecules. Vasovist ® (Bayer Schering Pharma AG, Berlin/Germany, code name MS-325) was the first clinically approved CA, which can boast this characteristic. This probe consists of a [Gd(DTPA)] cage functionalized with a diphenylcyclohexylphosphate group that confers a strong affinity to human serum albumin (HSA). Hence, after intravenous injection, Vasovist strongly and noncovalently binds to the serum protein, resulting in a significant increase in the relaxivity (Table 46.2) [23, 24]. Finally, the exchange lifetime of the water molecules, τ M , is also a crucial parameter that affects the observed relaxivity. An excessively slow τ M
1 (essentially because the effect of the paramagnetism is inefficiently passed to the bulk water), whereas a fast water exchange has the same effect on r 1 , as the water molecules are not in contact to the lanthanide ion long enough to efficiently experience its paramagnetic effect [15, 19, 25]. The water exchange lifetime is strongly affected by several factors that influence the water exchange mechanism. These include the nature of the coordination arms (e.g., carboxoamide vs carboxylate), the overall charge of the complex, and the presence of bulky substituents, which destabilize the complex structure relative to its transition state and thus promote a water dissociative mechanism [15, 26]. The τ M value can be calculated from the fitting of the temperature dependence profiles of the transverse relaxation rate of the 17 O nucleus of labeled water. Nowadays, some of the most sensitive CAs are substituted Gd-calix[4]arenes, whose r 1 relaxivity of around 70 s –1. mM –1 increases up to 100 s –1.
mM –1 when conjugated to HSA [27]. Despite their high relaxivity, it is necessary to inject several grams of CA into the blood stream to obtain satisfactory contrast, and nonspecific CAs are systematically and rapidly cleared through the kidneys. An ideal CA should also be specific to a certain body region so that the amount of probe injected into the patient could be significantly decreased. A way to overcome this problem is by using systems that are able to HOOC
HOOC HOOC
HOOC COOH
COOH COOH
COOH COOH
COOH N N N N N N N N N O O OH 2 OH 2 O 3 Gd NH N H N N N (a)
(b) (c)
(d) Figure 46.1 Schematic structure of some ligand cages used to prepare highly sensitive gadolinium-based contrast agent with q = 2. (a) PCTA-[12], (b) DO3A, (c) AAZTA, and (d) TREN-1-Me-3,2-HOPO. 624 METAL-BASED CHELATES AND NANOSYSTEMS AS MRI CONTRAST AGENTS TABLE 46.2 Comparison of Gd-DTPA and Vasovist Relaxivity Values a Field Strength 0.47 T 1.5 T
3.0 T Gd-DTPA
O O O O O N N N Gd 3+ O O− O− O− − O 3.8
4.1 3.7
Vasovist O O O P Ph Ph Gd O O N N N H H O− O O O O O O O O O 28–47
19–28 10–19
a Adapted from Reference 24. work as carriers for the CAs. Currently, different types of carriers are reported in the literature as ways of increasing the concentration of the probe in the area of diagnostic interest. This aspect will be further discussed. 46.6 T 2 CONTRAST AGENTS A successful way of decreasing T 2 is the use of iron-oxide-based CAs that, besides their ability to decrease the transverse relaxation time, are also able to cause local field inhomogeneities, thus leading to even faster NMR signal decay [28]. Consequently, in a T 2 -weighted image, the region in which the probe is accumulated becomes darker. However, it has recently been demonstrated that, using the proper sequence, iron-oxide-based CAs can also enhance the T 1 contrast in an MR image [29, 30]. In this way, it is still possible to observe the effect of superparamagnetic iron oxide NPs (SPIO), in regions without any signal, thus overcoming one of the major drawbacks of negative CAs. SPIOs usually consist of a magnetite (Fe 3 O 4 ) or maghemite ( γ Fe 2
3 ) core, coated with a natural or synthetic polymer. They can be characterized according to their mean size and are divided into three main categories, oral SPIO, standard superparamagnetic iron oxide (SSPIO), and ultrasmall superparamagnetic iron oxide (USPIO), as shown in Table 46.3. The low toxicity of SPIOs allows their application in imaging procedures, such as macrophage infiltration in inflammatory regions, cancer diagnosis, and the early detection of cardiovascular diseases. Nevertheless, the most promising application of this type of CAs concerns the detection of the fate of cells in vivo, after their previous labeling [31, 32].
Classification Trade Name Coating Material Hydrodynamic Diameter Oral SPIO Lumirem Silicon
300 nm Abdoscan
Sulphonated styrene 3.5
μm SSPIO
Endorem ® Dextran 80–180 nm Resovist
® Carboxydrextran 60 nm USPIO
Clariscan Pegylated starch 20 nm Supravist ® Carboxydextran 30 nm Sinerem
® Dextran
15–40 nm NANOCARRIERS 625 TABLE 46.4 Classification of Contrast Agents a Classification Characteristics Examples
Nonspecific extracellular agents After intravenous injection, leak from the blood pool into the interstitial space because of their small molecular weight These agents do not have the ability to cross an intact blood–brain barrier. They provide visualization of regions with abnormally high permeability, such as tumors or lesions Magnevist ® , Dotarem ® , Omniscan ® , ProHance ® , Gadovist ® , MultiHance ® , and
OptiMARK ® Blood pool agents Agents in this class have higher molecular weight than those in the previous class, a fact that prevents their release into the interstitial space and so they remain for longer periods in the blood stream This characteristic allows for the imaging of the vasculature Vasovist ® , Vistarem ® , Sinerem ® , Combidex ® , and
Supravist ® Organ-specific agents Some existing contrast agents have a natural tendency to be internalized by a specific cell type Several subclasses could be considered but one could take, for instance, some derivatives of Gd-DTPA that are already in clinical use as a tool for the diagnostic of hepatic lesions, after it was demonstrated that they are entrapped by the hepatocytes Primovist ® , Eovist
® , Tealascan ® , Feridex ® , Endorem ® ,
® Targeting agents These agents are able to recognize specific moieties on the cell surface Although this is a rather elegant methodology, it suffers from low target area concentration, making it difficult to achieve sufficient contrast. Nevertheless, targeted nanoparticles seem to be a way of overcoming this major drawback Liposomes associated with RGD moiety, for neovasculature targeting. Liposomes functionalized with folate [47, 48] Responsive agents These so-called smart agents are sensitive to certain stimuli that include pH, enzymatic activity, and redox potential, allowing the characterization of the microenvironment of the region of the interest to be achieved A typical example of this type of CAs is Egad, a Gd-DOTA derivative. In this molecule, a sugar moiety blocks the access of the water molecule to its coordination site. On enzyme activation, the sugar is released and allows the coordination of H 2 O to the paramagnetic center. In this case, the increase in the water relaxivity is directly correlated to the activity of b-galactosidase (the enzyme studied), a commonly used gene marker Egad and Gd-DOTA-serotonin a Adapted from References 35 and 36. Paramagnetic liposomes can also be included in the class of T 2 agents and their effect mainly depends on the magnetic moment of the paramagnetic complexes, the amount of agent entrapped in the vesicle, and its dimensions and the magnetic field. Still, few reports are available in the literature on such systems [33, 34]. 46.7 CLASSIFICATION OF CONTRAST AGENTS The search for the ideal CA has led to the appearance of a massive number of potential candidates and led to the need for a proper classification based on their chemical properties, mechanism of action, or biological distribution. For instance, most typical Gd 3 +
hepatobiliary system agents tend to accumulate in the hepatocytes, as represented in Table 46.4. 46.8 NANOCARRIERS The interest in nanosystems arose from the need to enhance the in vivo efficiency of many drugs once it was proven that the optimal concentration of the therapeutic agents in cell cultures needs to be increased to higher concentrations in vivo, resulting in more intense side effects. Actually, several pharmaceuticals display poor solubility, instability, or short half-life 626 METAL-BASED CHELATES AND NANOSYSTEMS AS MRI CONTRAST AGENTS in blood, resulting in inefficient treatment and higher toxicity risks. Indeed, nanocarriers offer several advantages when working as drug delivery vehicles and an extensive number of NPs have been reported in the literature of which liposomes are one of the most cited types. Nowadays, more than 20 nanosystems are in clinical use and several more under clinical trials or preclinical development [37]. More recently, the ability of NPs to work as carriers for a variety of molecules has come into play, in a new strategy in which therapeutics and diagnostics are combined in a single particle, giving rise to new theragnostic agents. The word theragnostics is derived from the Greek words therapeia (to treat) and gnosis (knowledge) referring to the monitorization of the response to a specific treatment and, for this reason, molecular imaging is providing new opportunities in the preclinical and clinical development of new and improved therapies. Several types of NPs have been constructed to generate MRI contrast, such as lipid-based systems including micelles, liposomes, and lipoproteins; polymer-based systems including dendrimers, nanospheres, nanocapsules, perfluorocarbon emulsions, inorganic NPs based on iron oxide particles, lanthanide(III), and manganese(II) oxides; nanozeolites; nanoMOFs (MOF, metal-organic frameworks); quantum dots (QDs); silica NPs; carbon nanotubes; and nanocomposites [18, 39, 40]. Some of these systems are schematically illustrated in Fig. 46.2 [40, 41]. All these types of particles can be passively targeted or functionalized by the association of targeting ligands to the outer surface of the NP, as, for example, VCAM (an inflammatory marker), annexin-5 (to detect apoptosis), or even RGD (Arg-Gly-Asp) peptides (for α-v-β-3-integrin). Lipid-based NPs are among the most intensively studied groups of NPs and liposomes are the vehicles most frequently used. The diversity present within this type of systems is illustrated in Table 46.5. Bangham first referred to liposomes in 1964, while he was studying red blood cell membranes, and often these particles are “affectionately” called Bangasomes. Liposomes can be described as nanosized artificial unilamellar vesicles of a commonly spherical shape, prepared with either natural or chemically modified lipids, which can be loaded with a variety of water- soluble or water-insoluble drugs [44]. The entrapment of the chosen drug can be achieved through several different processes, including (i) the incorporation of the drug in the aqueous solution, (ii) the use of lipophilic drugs, (iii) active entrapment methods such as pH gradient protocols, and (iv) electrostatic interactions between drug and the liposome membrane. The characteristics of the liposome membrane can be tuned by changing the lipid composition, thus achieving certain physicochemical properties, as size, surface charge (defined by the zeta potential), stability, bilayer rigidity, and permeability. In this way, liposomes can be classified according to their structural properties, that is, size and number of lamellae or charge. The MRI CA can be either incorporated in the lipidic membrane, either through the use of lipophilic chelates, or entrapped in the core of the particle. The bigger the particle, the higher the amplification of the MR signal; thus several micrometer-sized particles have also been considered, as will be further discussed. Legend
Targeting lignad Emulsion
Perflurocarbon gas Iron oxide Gd-chelate Lipid bubble Fluorescent lipid
QDot Dextran
Phospholipid PEG-phospholipid Streptavidin/avidin Biotin
(a) (e)
(b) (c)
(f) (g)
(d) (h)
Figure 46.2 Schematic representation of various types of targeted nanoparticle platforms proposed for multimodal molecular imaging applications. (a) CLIO, (b) MCIO, (c) SPIO, (d) micelle, (e) liposome, (f) emulsion, (g) Qdot micelle, and (h) microbubble. Reproduced from Reference 40 with permission from the publisher. NANOCARRIERS 627 TABLE 46.5 Characteristics of Lipid-Based Nanoparticles a Carrier Size Range Composition Common Preparation Technique Liposomes 25 nm to few micrometers Natural or synthetic phospholipids Passive and active loading Solid lipid nanoparticles 50–1000 nm Fats with high melting points of natural origin High pressure homogenization, microemulsion , and precipitation Oily suspensions 10 nm to few micrometers Natural or synthetic oils Dispersion technique Lipid microbubles Few micrometers Lipids, phospholipids polymers, and proteins Sonication Lipid microspheres 0.2–100
μm Lipids or phospholipids with high melting points Melt method, multiple microemulsions, and preincorporation into lipophilic carriers a Adapted from References 42 and 43. The fate of liposomes after their intravenous injection is determined by a subset of properties. Shortly after they were proposed as drug carriers, it became apparent that liposomes were rapidly recognized and removed from the circulation by the reticuloendothelial system (RES). To avoid detection by the immune system, “stealth liposomes” were purposed. These are functionalized with a hydrophilic coating on the outside of the liposome membrane, which enables longer blood half-life. The first approach consisted in preparing liposomes with characteristics similar to red blood cells by adding monosialoganglioside (GM1) to the liposome surface. Later, liposomes coated with a synthetic lipid derivative of poly(ethylene glycol) (PEG) were also proposed and this is nowadays the most widely used method of increasing the circulation time of liposomes [45–47]. However, although PEG is able to decrease the extent of liposomal uptake by the RES, recent reports have shown evidence that, after a second dose, PEG-coated liposomes were rapidly cleared from the blood [48]. The use of positive (T 1 ) CAs appears promising [38] but it requires the entrapment of 10 7 –10
8 complexes per cell, to achieve a sufficient imaging response for the visualization of the labeled cells. Thus, the search for a labeling procedure for which one particle is sufficient for a single cell led to the use of carriers that can be loaded with large payloads of Gd 3 +
(Fig. 46.3) [49]. Attempts to include hydrophilic molecules in the particle core failed because of the high porosity of the wall but the peculiar chemical stability of yeast walls could undertake a loading procedure in which the inner cavity of the particle acts as a microreactor, allowing the formation of large emulsions that remain entrapped in the particle. Paramagnetic liposomes also appear to have a good potential for being considered. These systems are able to dephase the magnetization of water protons around them. As this aspect depends on the paramagnetism of the CA, Dy 3 + -containing complexes appear to be the most efficient agents to be used in liposomes [19]. Recently, Eric Ahrens and coworkers were able to label in vivo immune cells with the commercially available perfluoro- 15-crown-5-ether (PCE), and track them by means of 19 F MRI to organs experiencing rejection. Although 19 F MRI is able to provide unambiguous detection of fluorine because of the complete absence of background signal, 19 F MR images may take up to 60 min per scan and the detection of low levels of inflammation remains a challenge. Moreover, the proposed in vivo cell labeling does not allow the identification of the cell type involved in the inflammatory process, as it is a nonspecific labeling procedure and it is time consuming, as the animals are imaged 24–48 h post injection [50, 51]. Inorganic NPs are another important class of CAs, such as the iron-oxide-based SPIOs, previously presented, which represent by far the most commonly used T 2 agents [39]. They have been fuctionalized at the surface to be made multimodal by covalent conjugation to additional probes, such as for MRI/ OI by coupling to fluorophores such as rhodamine and Cy5.5, and eventually targeting moieties such as RGD peptides and annexin V. By far, the largest body of work in the literature is for cross-linked iron oxide (CLIO)–Cy5.5 conjugates from the group of Weissleder [52]. Before the conjugation, the iron oxide NPs can be coated with a layer of amphiphilic polymers or PEG. In addition to adding an optical functionality, iron oxides can also be modified for PET or SPECT. NPs have been radiolabeled with, for example, 64 Cu 2 + , 111 In 3 + , or
18 F. DOTA or DTPA chelates have been introduced for the cationic radioisotopic species. Iron oxide NPs can be enclosed in a shell (core–shell NPs), such as dextran, lipids, or silica. The porosity of silica allows noncovalent entrapment of many other kinds of probes, such as rhodamine dyes and inorganic complexes, or covalently conjugating probes and/or targeting functions. They can also be doped with other ions, such as luminescent Tb 3 + or Co 2 + in ferrite NPs. 628 METAL-BASED CHELATES AND NANOSYSTEMS AS MRI CONTRAST AGENTS 1 2
25 μm
Confocal image of macrophage (J777A.1) showing nucleus (1) with yeast cell-wall particles (2). (See insert for color
QDs are another important platform for bimodal MRI/OI [18]. QDs are nanoparticulate clusters of semiconductor material, for example, CdSe (smaller than the Bohr exciton radius), that show quantum confinement effects, meaning that their optical properties are controlled by their size rather than their composition, which makes them useful OI agents. They have bright fluorescence, photostability and a narrow and size-tunable emission spectrum [53]. The surface of the QD can be coated with micelar pegylated phospholipids (PEG-DSPE) and derivatized with paramagnetic chelates (Gd-DTPA-bis(stearylamide)), giving high relaxivity agents for MRI/OI. The QDs have also been bioconjugated, for example, with cyclic RGD [54]. Rigid inorganic nanostructures have been applied as matrices of paramagnetic ions (e.g., Gd 3 +
silica NPs, and nanoporous silicas [55]. Zeolites can include Gd 3 + ions in their cavities with high relaxivities [56], and carbon nanotubes may act as a framework to hold Gd 3 +
Other examples are nanosized particles of gadolinium salts, such as oxide, fluoride, or phosphate, useful as T 1 MRI CAs [38]. Gold NPs have also been derivatized in their surface with Gd 3 + chelates, leading to high relaxivities [58]. Many other examples can be found in the literature, in particular in specialized reviews [18, 39]. In summary, nanotechnology plays an extraordinary role in the development of imaging, diagnosis, and drug delivery tools. Newly developed systems offer the possibility of achieving an improved knowledge of their interaction with biological systems. Moreover, there is the hope that the increasing research in this field will contribute to the translation of the technology to the clinics. REFERENCES 1. Cai, W.; Chen, X. Small 2007, 3 , 1840. 2. Frullano, L.; Meade, T. J. J. Biol. Inorg. Chem. 2007, 12 , 939. 3. Wang, X.; Fowlkes, J. B.; Cannata, J. M.; Hu, C.; Carson, P. L. Ultrasound Med. Biol. 2011, 37 , 484. 4. Massoud, T. F.; Gambhir, S. S. Genes Dev. 2003, 17 , 545. 5. Damadian, R. Science 1971, 171 , 1151. 6. Lauterbur, P. C. Nature 1973, 242 , 190. 7. Brown, M. A.; Semelka, R. C. MRI: Basic Principles and Applications; 2010, Wiley-Blackwell: Oxford. 8. Westbrook, C.; Roth, C. K.; Talbot, J. MRI in Practice, 3rd ed.; Wiley-Blackwell: Oxford, 2007. 9. Hashemi, R. H.; Bradley, W. G. MRI—The Basics; Lippincott Williams & Wilkins: Baltimore, 1997. REFERENCES 629 10. Rinck, P. A., Magnetic Resonance in Medicine, 4th ed.; Wiley-Blackwell: Oxford, 2001. 11. McRobbie, D. W.; Moore, E. A.; Graves, M. J.; Prince, M. R. MRI from Picture to Proton; Cambridge University Press: Cambridge,
12. Bloch, F. Phys. Rev. 1946, 70 , 460. 13. Mendonc¸a-Dias, M. H.; Gaggelli, E.; Lauterbur, P. C. Semin. Nucl. Med. 1983, 13 , 364. 14. Carr, D. H. J. Thorac. Imaging 1985, 1 , 74. 15. Aime, S.; Botta, M.; Terreno, E. Adv. Inorg. Chem. 2005, 57 , 173. 16. Laniado, M.; Weinmann, H. J.; Sch¨orner, W.; Felix, R.; Speck, U. Physiol. Chem. Phys. Med. NMR 1984, 16 ,157. 17. Aime, S.; Caravan, P. J. Magn. Reson. Imaging 2009, 30 , 1259. 18. Bottrill, M.; Kwok, L.; Long, N. J. Chem. Soc. Rev. 2006, 35 , 557. 19. Terreno, E.; Castelli, D. D.; Viale, A.; Aime S., Chem. Rev. 2010, 110 , 3019. 20. Aime, S.; Botta, M.; Geninatti C. S.; Giovenzana, G.; Pagliarin, R.; Sisti, M; Terreno, E. Magn. Reson. Chem. 1998, 36 , S200. 21. Aime, S.; Calabi, L.; Cavallotti, C.; Gianolio, E.; Giovenzana, G. B.; Losi, P.; Maiocchi, A.; Palmisano, G.; Sisti, M. Inorg. Chem.
22. Pierre, V. C.; Botta, M.; Aime, S.; Raymond, K. N. Inorg. Chem. 2006, 45 , 8355. 23. Fink, C.; Goyen, M.; Lotz, J. Eur. Radiol. 2007, 17 (Suppl 2), B38. 24. Goyen, M. Vasc. Health Risk Manag. 2008, 4 , 1. 25. Caravan, P. Chem. Soc. Rev. 2006, 35 , 512. 26. Merbach, A. E.; T´oth, ´ E. The Chemistry of Contrast Agents in Medical Magnetic Resonance Imaging; John Wiley & Sons, Inc.: New York, 2001. 27. Sch¨uhle, D. T.; Schatz, J.; Laurent, S.; Vander, E. L.; Muller, R. N.; Stuart, M. C.; Peters, J. A. Chem. Eur. J. 2009, 15 , 3290. 28. Makowski, M. R.; Wiethoff, A. J.; Jansen, C. H.; Botnar, R. M. Top. Magn. Reson. Imaging 2009, 20 , 247. 29. Saleh, A.; Schroeter, M.; Jonkmanns, C.; Hartung, H. P.; M¨odder, U.; Jander, S. Brain 2004, 127 , 1670. 30. Bjornerud, A.; Johansson, L. NMR Biomed. 2004, 17 , 465. 31. Mahmoudi, M.; Hosseinkhani, H.; Hosseinkhani, M.; Boutry, S.; Simchi, A.; Journeay, W. S.; Subramani, K.; Laurent, S. Chem. Rev.
32. Huang, C.; Neoh, K. G.; Wang, L.; Kang, E. T.; Shuter, B. Contrast Media Mol. Imaging 2011, 6 , 298. 33. Castelli, D. D.; Terreno, E.; Cabella, C.; Chaabane, L.; Lanzardo, S.; Tei, L.; Visigalli, M.; Aime S. NMR Biomed. 2009, 22 , 1084. 34. Castelli, D. D.; Dastr`u, W.; Terreno, E.; Cittadino, E.; Mainini, F.; Torres, E.; Spadaro, M.; Aime, S. J. Control. Release 2010, 144 (3), 271. 35. Bellin, M. F. Eur. J. Radiol. 2006, 60 , 314. 36. Geraldes, C. F. G. C.; Laurent, S. Contrast Media Mol. Imaging 2009, 4 , 1. 37. Zhang, L.; Gu, F. X.; Chan, J. M.; Wang, A. Z.; Langer, R. S.; Farokhzad, O. C. Clin. Pharmacol. Ther. 2008, 83 , 761. 38. Na, H. B.; Hyeon, T. J. Mater. Chem. 2009, 19 , 6267. 39. Louie, A. Chem. Rev. 2010, 110 , 3146. 40. Agrawal, P.; Strijkers, G. J.; Nicolay, K. Adv. Drug Deliv. Rev. 2010, 62 , 42. 41. Strijkers, G. J.; van Tilborg, G. A. F.; Geelen, T.; Reutelingsperger, C. P. M.; Nicolay, K. Cancer Nanotechnol. 2010, 10 , 325. 42. Mulder, W. J.; Strijkers, G. J.; van Tilborg, G. A.; Griffioen, A. W.; Nicolay, K. NMR Biomed. 2006, 19 , 142. 43. Rawat, M.; Singh, D.; Saraf, S. J. Pharm. Soc. Jpn. 2008, 128 , 269. 44. Lasic, D. D., Liposomes in Gene Delivery , 1st ed.; CRC-Press: London, 1997. 45. Drulis-Kawa, Z.; Dorotkiewicz-Jach, A.; Gubernator, J.; Gula, G.; Bocer, T.; Doroszkiewicz, W. A. Int. J. Pharm. 2009, 387 , 187. 46. Gabizon, G.; Papahadjopoulos, D. Proc. Natl. Acad. Sci. U.S.A 1988, 85 , 6949. 47. Allen, T. M.; Hansen, C.; Martin, F.; Redemann, C.; Yau-Young, A. Biochim. Biophys. Acta 1991, 1066 , 29. 48. Ishida, T.; Harada, M.; Wang, X. Y.; Ichihara, M.; Irimura, K.; Kiwada, H. J. Control. Release 2005, 105 , 305. 49. Figueiredo, S.; Moreira, J. N.; Geraldes, C. F. G. C.; Rizzitelli, S.; Aime, S.; Terreno E. Chem. Commun. 2011, 47 , 10635. 50. Hitchens, T. K.; Ye, Q.; Eytan, D. F.; Janjic, J. M.; Ahrens, E. T.; Ho, C., Magn. Reson. Med. 2011, 65 , 1144. 51. Ahrens, E. T.; Young, W. B.; Xu, H.; Pusateri, L. K., Biotechniques 2011, 50 , 229. 52. Pittet, M. J.; Swirski, F. K.; Reynolds, F.; Josephson, L.; Weissleder, R., Nat. Protoc. 2006, 1 , 73. 53. Sutherland, A. J. Curr. Opin. Solid State Mater.Sci. 2002, 6 , 365. 54. Mulder, W. J. M.; Koole, R.; Brandwijk, R. J.; Storm, G.; Chin, P. T. K.; Strijkers, G. J. and Donega, C. M.; Nicolay, K.; Griffioen, A. W., Nano Lett. 2006, 6 , 1. 630 METAL-BASED CHELATES AND NANOSYSTEMS AS MRI CONTRAST AGENTS 55. Rocca, J. D.; Lin, W. Eur. J. Inorg. Chem. 2010, 3725. 56. Platas-Iglesias, C.; Elst L. V.; Zhou, W.; Muller, R. N.; Geraldes, C. F.; Maschmeyer, T.; Peters, J. A. Chem. Eur. J. 2002, 8 , 5121. 57. Sitharaman, B.; Kissell, K. R.; Hartman, K. B.; Tran, L. A.; Baikalov, A.; Rusakova, I.; Sun, Y.; Khant, H. A.; Ludtke, S. J.; Chiu, W.; Laus, S.; T´oth, E.; Helm, L.; Merbach, A. E.; Wilson, L. J. Chem. Commun. 2005, 3915. 58. Ferreira, M. F.; Mousavi, B.; Ferreira, P. M.; Martins, C. I. O.; Helm, L.; Martins, J. A.; Geraldes, C. F. G. C. Dalton Trans. 2012,
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