X-ray Computed Tomography (CT) is one of the most commonly utilized anatomical imaging modalities for both research and clinical purposes. CT combines high-resolution, three-dimensional data with relatively fast acquisition to provide a solid platform for non-invasive human or specimen imaging. The primary limitation of CT is its inability to distinguish many soft tissues based on native contrast. While bone has high contrast within a CT image due to its material density from calcium phosphate, soft tissue is less dense and many are homogenous in density. This presents a challenge in distinguishing one type of soft tissue from another. A couple exceptions include the lungs as well as fat, both of which have unique densities owing to the presence of air or bulk hydrocarbons, respectively. In order to facilitate X-ray CT imaging of other structures, a range of contrast agents have been developed to selectively identify and visualize the anatomical properties of individual tissues. Most agents incorporate atoms like iodine, gold, or barium because of their ability to absorb X-rays, and thus impart contrast to a given organ system. Here we review the strategies available to visualize lung, fat, brain, kidney, liver, spleen, vasculature, gastrointestinal tract, and liver tissues of living mice using either innate contrast, or commercial injectable or ingestible agents with selective perfusion. Further, we demonstrate how each of these approaches will facilitate the non-invasive, longitudinal, in vivo imaging of pre-clinical disease models at each anatomical site.
References
[1]
Raju, T. The nobel chronicles. Lancet 1999, 354, 1653.
[2]
Bushberg, J.T.; Seibert, J.A.; Leidholdt, E.M.; Boone, J.M. The Essential Physics of Medical Imaging, 3rd ed. ed.; Lippincott Williams & Wilkins: Philadelphia, PA, USA, 2012; pp. 45–47.
Loening, A.M.; Gambhir, S.S. AMIDE: A free software tool for multimodality medical image analysis. Mol. Imaging 2003, 2, 131–137.
[5]
Taschereau, R.; Chow, P.L.; Chatziioannou, A.F. Monte Carlo simulations of dose from microCT imaging procedures in a realistic mouse phantom. Med. Phys. 2006, 33, 216–224.
[6]
Willekens, I.; Buls, N.; Lahoutte, T.; Baeyens, L.; Vanhove, C.; Caveliers, V.; Deklerck, R.; Bossuyt, A.; de Mey, J. Evaluation of the radiation dose in micro-CT with optimization of the scan protocol. Contrast Media Mol. Imaging 2010, 5, 201–207.
[7]
Coolens, C.; Breen, S.; Purdie, T.G.; Owrangi, A.; Publicover, J.; Bartolac, S.; Jaffray, D.A. Implementation and characterization of a 320-slice volumetric CT scanner for simulation in radiation oncology. Med. Phys. 2009, 36, 5120–5127.
[8]
Marzola, P.; Osculati, F.; Sbarbati, A. High field MRI in preclinical research. Eur. J. Radiol. 2003, 48, 165–170.
[9]
Pandit, P.; Johnston, S.M.; Qi, Y.; Story, J.; Nelson, R.; Johnson, G.A. The utility of Micro-CT and MRI in the assessment of longitudinal growth of liver metastases in a preclinical model of colon carcinoma. Acad. Radiol. 2013, 20, 430–439.
[10]
Schmid, A.; Schmitz, J.; Mannheim, J.G.; Maier, F.C.; Fuchs, K.; Wehrl, H.F.; Pichler, B.J. Feasibility of sequential PET/MRI using state-of-the-art small animal PET and 1 T benchtop MRI. Mol. Imaging Biol. 2013, 15, 155–165.
[11]
Sasser, T.A.; Chapman, S.E.; Li, S.; Hudson, C.; Orton, S.P.; Diener, J.M.; Gammon, S.T.; Correcher, C.; Leevy, W.M. Segmentation and measurement of fat volumes in murine obesity models using X-ray computed tomography. J. Vis. Exp. 2012, 62, doi:10.3791/3680.
[12]
Aggarwal, M.; Zhang, J.; Miller, M.I.; Sidman, R.L.; Mori, S. Magnetic resonance imaging and micro-computed tomography combined atlas of developing and adult mouse brains for stereotaxic surgery. Neuroscience 2009, 162, 1339–1350.
[13]
Dzialowski, I.; Weber, J.; Doerfler, A.; Forsting, M.; Kummer, R. Brain tissue water uptake after middle cerebral artery occlusion assessed with CT. J. Neuroimaging 2004, 14, 42–48.
[14]
Mortelé, K.J.; Oliva, M.R.; Ondategui, S.; Ros, P.R.; Silverman, S.G. Universal use of nonionic iodinated contrast medium for CT: Evaluation of safety in a large urban teaching hospital. AJR Am. J. Roentgenol. 2005, 184, 31–34.
[15]
Dillman, J.R.; Al-Hawary, M.; Ellis, J.H.; Cohan, R.H.; Kaza, R.; Myles, J.D.; Khalatbari, S.; Francis, I.R. Comparative investigation of IV iohexol and iopamidol: Effect on renal function in low-risk outpatients undergoing CT. Am. J. Roentgenol. 2012, 198, 392–397.
[16]
Webb, S. The Physics of Medical Imaging; Taylor & Francis: Boca Raton, FL, USA, 2010; pp. 95–96.
[17]
Ritman, E.L. Micro-computed tomography-current status and developments. Annu. Rev. Biomed. Eng. 2004, 6, 185–208.
[18]
U.S. Cancer Statistics Working Group. United States Cancer Statistics: 1999–2009 Incidence and Mortality Web-Based Report. Atlanta (GA); Department of Health and Human Services, Centers for Disease Control and Prevention and National Cancer Institute: Atlanta, GA, USA, 2013.
[19]
Centers for Disease Control and Prevention, National Center for Health Statistics. Underlying Cause of Death 1999–2010 on CDC WONDER Online Database. Released 2012. Available online: http://wonder.cdc.gov/ucd-icd10.html (accessed on 17 April 2013).
[20]
Artaechevarria, X.; Blanco, D.; de Biurrun, G.; Ceresa, M.; Perez-Martin, D.; Bastarrika, G.; de Torres, J.P.; Zulueta, J.J.; Montuenga, L.M.; de Ortiz, S.C.; et al. Evaluation of micro-CT for emphysema assessment in mice: Comparison with non-radiological techniques. Eur. Radiol. 2011, 21, 954–962.
[21]
Parameswaran, H.; Bartolák-Suki, E.; Hamakawa, H.; Majumdar, A.; Allen, P.G.; Suki, B. Three-dimensional measurement of alveolar airspace volumes in normal and emphysematous lungs using micro-CT. J. Appl. Physiol. 2009, 107, 583–592.
[22]
De Langhe, E.; Velde, G.V.; Hostens, J.; Himmelreich, U.; Nemery, B.; Luyten, F.P.; Vanoirbeek, J.; Lories, R.J. Quantification of lung fibrosis and emphysema in mice using automated micro-computed tomography. PLoS One 2012, 7, doi:10.1371/journal.pone.0043123.
[23]
Davison, C.A.; Chapman, S.E.; Sasser, T.A.; Wathen, C.A.; Diener, J.; Schafer, Z.F.; Leevy, W.M. Multimodal optical, X-ray CT, and SPECT imaging of a mouse model of breast cancer lung metasasis. Curr. Mol. Med. 2013, 13, 368–376.
[24]
Paulus, M.J.; Gleason, S.S.; Kennel, S.J.; Hunsicker, P.R.; Johnson, D.K. High resolution X-ray computed tomography: An emerging tool for small animal cancer research. Neoplasia 2000, 2, 62–70.
[25]
Sharif, M.; Lam, W.W.; Ouriadov, A.V.; Holdsworth, D.W.; Santyr, G.E. Comparison of hyperpolarized 3He MRI rat lung volume measurement with micro-computed tomography. NMR Biomed. 2010, 23, 359–367.
[26]
Tan, Y.; Schwartz, L.H.; Zhao, B. Segmentation of lung lesions on CT scans using watershed, active contours, and Markov random field. Med. Phys. 2013, 40, doi:10.1118/1.4793409.
[27]
Artaechevarria, X.; Perez-Martin, D.; Ceresa, M.; de Biurrun, G.; Blanco, D.; Montuenga, L.M.; van Ginneken, B.; Ortiz-de-Solorzano, C.; Munoz-Barrutia, A. Airway segmentation and analysis for the study of mouse models of lung disease using micro-CT. Phys. Med. Biol. 2009, 54, 7009–7024.
[28]
James, P.T.; Leach, R.; Kalamara, E.; Shayeghi, M. The worldwide obesity epidemic. Obes. Res. 2012, 9, 228S–233S.
[29]
Speakman, J.; Hambly, C.; Mitchell, S.; Krol, E. Animal models of obesity. Obes. Rev. 2007, 8, 55–61.
[30]
Marchadier, A.; Vidal, C.; Tafani, J.P.; Ordureau, S.; Lédée, R.; Léger, C. Quantitative CT imaging for adipose tissue analysis in mouse model of obesity. Proc. SPIE 2011, 7963, 1–8.
[31]
Lubura, M.; Hesse, D.; Neumann, N.; Scherneck, S.; Wiedmer, P.; Schürmann, A. Non-invasive quantification of white and brown adipose tissues and liver fat content by computed tomography in mice. PloS One 2012, 7, doi:10.1371/journal.pone.0037026.
[32]
Luu, Y.K.; Lublinsky, S.; Ozcivici, E.; Capilla, E.; Pessin, J.E.; Rubin, C.T.; Judex, S. In vivo quantification of subcutaneous and visceral adiposity by micro-computed tomography in a small animal model. Med. Eng. Phys. 2009, 31, 34–41.
[33]
Judex, S.; Luu, Y.K.; Ozcivici, E.; Adler, B.; Lublinsky, S.; Rubin, C.T. Quantification of adiposity in small rodents using micro-CT. Methods 2010, 50, 14–19.
[34]
Granton, P.V.; Norley, C.J.; Umoh, J.; Turley, E.A.; Frier, B.C.; Noble, E.G.; Holdsworth, D.W. Rapid in vivo whole body composition of rats using cone beam μCT. J. Appl. Physiol. 2010, 109, 1162–1169.
[35]
Hildebrandt, A.L.; Kelly-Sullivan, D.M.; Black, S.C. Validation of a high-resolution X-ray computed tomography system to measure murine adipose tissue depot mass in situ and longitudinally. J. Pharmacol. Toxicol. Method. 2002, 47, 99–106.
[36]
Mini？o, A.M.; Murphy, S.L.; Xu, J.; Kochanek, K.D. Deaths: Final data for 2008. Natl. Vital Stats. Rep. 2011, 59, 1–127.
[37]
Dzialowski, I.; Klotz, E.; Goericke, S.; Doerfler, A.; Forsting, M.; von Kummer, R. Ischemic brain tissue water content: CT monitoring during middle cerebral artery occlusion and reperfusion in rats. Radiology 2007, 243, 720–726.
[38]
Lythgoe, M.F.; Sibson, N.R.; Harris, N.G. Neuroimaging of animal models of brain disease. Br. Med. Bull. 2003, 65, 235–257.
Chalela, J.A.; Kidwell, C.S.; Nentwich, L.M.; Luby, M.; Butman, J.A.; Demchuk, A.M.; Hill, M.D.; Patronas, N.; Latour, L.; Warach, S. Magnetic resonance imaging and computed tomography in emergency assessment of patients with suspected acute stroke: A prospective comparison. Lancet 2007, 369, 293–298.
[41]
Dillavou, E.D.; Muluk, S.C.; Makaroun, M.S. A decade of change in abdominal aortic aneurysm repair in the United States: Have we improved outcomes equally between men and women? J. Vasc. Surg. 2006, 43, 230–238.
Casteleyn, C.; Trachet, B.; van Loo, D.; Devos, D.G.; van den Broeck, W.; Simoens, P.; Cornillie, P. Validation of the murine aortic arch as a model to study human vascular diseases. J. Anat. 2010, 216, 563–571.
[44]
Keung, E.Z.; Nelson, P.J.; Conrad, C. Concise review: Genetically engineered stem cell therapy targeting angiogenesis and tumor stroma in gastrointestinal malignancy. Stem Cells 2013, 31, 227–235.
[45]
Vandeghinste, B.; Trachet, B.; Renard, M.; Casteleyn, C.; Staelens, S.; Loeys, B.; Segers, P.; Vandenberghe, S. Replacing vascular corrosion casting by in vivo micro-CT imaging for building 3D cardiovascular models in mice. Mol. Imaging Biol. 2011, 13, 78–86.
[46]
Kiessling, F.; Greschus, S.; Lichy, M.P.; Bock, M.; Fink, C.; Vosseler, S.; Moll, J.; Mueller, M.M.; Fusenig, N.E.; Traupe, H.; et al. Volumetric computed tomography (VCT): A new technology for noninvasive, high-resolution monitoring of tumor angiogenesis. Nat. Med. 2004, 10, 1133–1138.
[47]
Seo, Y.; Hashimoto, T.; Nuki, Y.; Hasegawa, B.H. In vivo microCT imaging of rodent cerebral vasculature. Phys. Med. Biol. 2008, 53, N99–N107.
Bree, R.L.; Parisky, Y.R.; Bernardino, M.E.; Costello, P.; Leder, R.; Brown, P.C. Cost-effective use of low-osmolality contrast media for CT of the liver: Evaluation of liver enhancement provided by various doses of iohexol. Am. J. Roentgenol. 1994, 163, 579–583.
[50]
Langheinrich, A.C.; Yeniguen, M.; Ostendorf, A.; Marhoffer, S.; Kampschulte, M.; Bachmann, G.; Stolz, E.; Gerriets, T. Evaluation of the middle cerebral artery occlusion techniques in the rat by in vitro 3-dimensional micro-and nano computed tomography. BMC Neurol. 2010, 10, doi:10.1186/1471-2377-10-36.
[51]
Hayaska, N.; Nagai, N.; Kawao, N.; Niwa, A.; Yoshioka, Y.; Mori, Y.; Shigeta, H.; Kashiwagi, N.; Miyazawa, M.; Satou, T.; et al. In Vivo Diagnostic imaging using Micro-CT: Sequential and comparative evaluation of rodent models for hepatic/brain ischemia and stroke. PLoS One 2012, 7, doi:10.1371/journal.pone.0032342.
[52]
Dorr, A.; Sled, J.G.; Kabani, N. Three-dimensional cerebral vasculature of the CBA mouse brain: A magnetic resonance imaging and micro computed tomography study. Neuroimage 2007, 35, 1409–1423.
[53]
Holdsworth, D.W.; Thornton, M.M. Micro-CT in small animal and specimen imaging. Trends Biotechnol. 2002, 20, S34–S39.
[54]
Sproule, T.J.; Sled, J.G.; Wentzell, J.; Wang, B.; Henkelman, R.M.; Roopenian, D.C.; Burgess, R.W. A mouse model of heritable cerebrovascular disease. PLoS One 2010, 5, doi:10.1371/journal.pone.0015327.
Chien, C.C.; Chen, H.H.; Lai, S.F.; Wu, K.C.; Cai, X.; Hwu, Y.; Petibois, C.; Chu, Y.; Margaritondo, G. Gold nanoparticles as high-resolution X-ray imaging contrast agents for the analysis of tumor-related micro-vasculature. J. Nanobiotechnol. 2012, 10, 10–11.
[57]
Lim, E.K.; Jang, E.; Kim, J.; Lee, T.; Kim, E.; Suh, J.S.; Park, H.S.; Huh, Y.M.; Haam, S. Self-fabricated dextran-coated gold nanoparticles using pyrenyl dextran as a reducible stabilizer and their application as CT imaging agents for atherosclerosis. J. Mater. Chem. 2012, 22, 17518–17524.
[58]
Wang, H.; Zheng, L.; Guo, R.; Peng, C.; Shen, M.; Shi, X.; Zhang, G. Dendrimer-entrapped gold nanoparticles as potential CT contrast agents for blood pool imaging. Nanoscale. Res. Lett. 2012, 7, 190–191.
[59]
Hainfeld, J.F.; Slatkin, D.N.; Focella, T.M.; Smilowitz, H.M. Gold nanoparticles: A new X-ray contrast agent. Br. J. Radiol. 2006, 79, 248–253.
[60]
Trachet, B.; Renard, M.; de Santis, G.; Staelens, S.; de Backer, J.; Antiga, L.; Loeys, B.; Segers, P. An integrated framework to quantitatively link mouse-specific hemodynamics to aneurysm formation in angiothensin II-infused ApoE？/？ Mice. Ann. Biomed. Eng. 2011, 39, 2430–2444.
[61]
Missbach-Fuentner, J.; Hunia, J.; Alves, F. Tumor blood vessel visualization. Int. J. Dev. Biol. 2011, 55, 535–546.
[62]
Vasquez, S.X.; Gao, F.; Su, F.; Grijalva, V.; Pope, J.; Martin, B.; Stinstra, J.; Masner, M.; Shah, N.; Weinstein, D.M.; et al. Optimization of microCT imaging and blood vessel diameter quantitation of preclinical specimen vasculature with radiopaque polymer injection medium. PLoS One 2011, 6, doi:10.1371/journal.pone.0019099.
[63]
Givvimani, S.; Sen, U.; Tyagi, N.; Munjal, C.; Tyagi, S.C. X-ray imaging of differential vascular density in MMP？9？/？, PAR？1？/+, hyperhomocysteinemic (CBS？/+) and diabetic (Ins2-/+) mice*. Arch. Physiol. Biochem. 2011, 117, 1–7.
[64]
Jemal, A.; Bray, F.; Center, M.M.; Ferlay, J.; Ward, E.; Forman, D. Global cancer statistics. CA Cancer J. Clin. 2011, 61, 69–90.
[65]
Anstee, Q.M.; Goldin, R.D. Mouse models in non-alcoholic fatty liver disease and steatohepatitis research. Int. J. Exp. Pathol. 2006, 87, 1–16.
[66]
Iredale, J.P. Models of liver fibrosis: Exploring the dynamic nature of inflammation and repair in a solid organ. J. Clin. Invest. 2007, 117, 539–540.
[67]
Washburn, M.L.; Bility, M.T.; Zhang, L.; Kovalev, G.I.; Buntzman, A.; Frelinger, J.A.; Barry, W.; Ploss, A.; Rice, C.M.; Su, L. A humanized mouse model to study hepatitis C virus infection, immune response, and liver disease. Gastroenterology 2011, 140, 1334–1344.
[68]
Leenders, M.W.; Nijkamp, M.W.; Borel, R.I.H. Mouse models in liver cancer research: A review of current literature. World J. Gastroenterol. 2011, 14, 6915–6916.
[69]
Weber, S.M.; Peterson, K.A.; Durkee, B.; Qi, C.; Longino, M.; Warner, T.; Lee, F.T., Jr; Weichert, J.P. Imaging of murine liver tumor using microCT with a hepatocyte-selective contrast agent: Accuracy is dependent on adequate contrast enhancement. J. Surg. Res. 2004, 119, 41–45.
Boll, H.; Nittka, S.; Doyon, F.; Neumaier, M.; Marx, A.; Kramer, M.; Groden, C.; Brockmann, M.A. Micro-CT based experimental liver imaging using a nanoparticulate contrast agent: A longitudinal study in mice. PLoS One 2011, 6, doi:10.1371/journal.pone.0025692.
[72]
Fiebig, T.; Boll, H.; Figueiredo, G.; Kerl, H.U.; Nittka, S.; Groden, C.; Kramer, M.; Brockmann, M.A. Three-dimensional in vivo imaging of the murine liver: A micro-computed tomography-based anatomical study. PLoS One 2012, 7, doi:10.1371/journal.pone.0031179.
[73]
Badea, C.T.; Drangova, M.; Holdsworth, D.W.; Johnson, G.A. In vivo small-animal imaging using micro-CT and digital subtraction angiography. Phys. Med. Biol. 2008, 53, R319–R350.
[74]
Martiniova, L.; Schimel, D.; Lai, E.W.; Limpuangthip, A.; Kvetnansky, R.; Pacak, K. In vivo micro-CT imaging of liver lesions in small animal models. Methods 2010, 50, 20–25.
[75]
Collins, A.J.; Foley, R.N.; Herzog, C.; Chavers, B.; Gilbertson, D.; Ishani, A.; Kasiske, B.; Liu, J.; Mau, L.W.; Agodoa, L.; et al. US renal data system 2010 annual data report. Am. J. Kid. Dis. 2011, 57, doi:10.1053/j.ajkd.2010.10.007.
[76]
Murphy, S.L.; Xu, J.Q.; Kochanek, K.D. Deaths: Preliminary data for 2010. Natl. Vital Stat. Rep. 2010, 60, 1–52.
[77]
Xu, R.; Franchi, F.; Miller, B.; Crane, J.A.; Peterson, K.M.; Psaltis, P.J.; Rodriguez-Porcel, M. Polycystic kidneys have decreased vascular density: A microCT study. Microcirculation 2012, 20, 183–189.
Jensen, H.; Doughty, R.W.; Grant, D.; Myhre, O. The effects of the iodinated X-ray contrast media iodixanol, iohexol, iopromide, and ioversol on the rat kidney epithelial cell line NRK 52-E. Ren. Fail. 2011, 33, 426–433.
[80]
Maffei, E.; Martini, C.; Arcadi, T.; Clemente, A.; Seitun, S.; Zuccarelli, A.; Tori, T.; Mollet, N.R.; Rossi, A.; Catalano, O.; et al. Plaque imaging with CT coronary angiography: Effect of intra-vascular attenuation on plaque type classification. World J. Radiol. 2012, 4, 265–272.
[81]
Almajdub, M.; Magnier, L.; Juillard, L.; Janier, M. Kidney volume quantification using contrast-enhanced in vivo X-ray micro-CT in mice. Contrast Media Mol. Imaging 2008, 3, 120–126.
[82]
Henning, A.L.; Jiang, M.X.; Yalcin, H.C.; Butcher, J.T. Quantitative three-dimensional imaging of live avian embryonic morphogenesis via micro-computed tomography. Dev. Dyn. 2011, 240, 1949–1957.
[83]
Michigoshi, Y.; Katayama, R.; Yamagishi, N.; Kato, M.; Saito, J.; Satoh, H.; Furuhama, K. Estimation of glomerular filtration rate in rabbits by a single-sample method using iodixanol. Lab. Anim. 2012, 46, 341–344.
[84]
Loftus, E.V., Jr. Clinical epidemiology of inflammatory bowel disease: Incidence, prevalence, and environmental influences. Gastroenterology 2004, 126, 1504–1517.
[85]
Fredin, M.F.; Hultin, L.; Hyberg, G.; Rehnstr？m, E.; Hultgren, H.E.; Melgar, S.; Jansson, L. Predicting and monitoring colitis development in mice by micro-computed tomography. Inflamm. Bowel Dis. 2008, 14, 491–499.
[86]
Pickhardt, P.J.; Halberg, R.B.; Taylor, A.J.; Durkee, B.Y.; Fine, J.; Lee, F.T., Jr; Weichert, J.P. Microcomputed tomography colonography for polyp detection in an in vivo mouse tumor model. Proc. Natl. Acad. Sci. USA 2005, 102, 3419–3422.
[87]
Durkee, B.Y.; Mudd, S.R.; Roen, C.N.; Clipson, L.; Newton, M.A.; Weichert, J.P.; Pickhardt, P.J.; Halberg, R.B. Reproducibility of tumor volume measurement at microCT colonography in living mice. Acad. Radiol. 2008, 15, 334–341.
[88]
Choquet, P.; Calon, A.; Breton, é.; Beck, F.; Domon-Dell, C.; Freund, J.N.; Constantinesco, A. Multiple-contrast X-ray micro-CT visualization of colon malformations and tumours in situ in living mice. C. R. Biol. 2007, 330, 821–827.
[89]
Boll, H.; Bag, S.; N？lte, I.S.; Wilhelm, T.; Kramer, M.; Groden, C.; Bocker, U.; Brockmann, M.A. Double-contrast micro-CT colonoscopy in live mice. Int. J. Colorectal Dis. 2011, 26, 721–727.
[90]
Widmark, J.M. Imaging-related medications: A class overview. Proc. Bayl. Univ. Med. Cent. 2007, 20, 408–417.
[91]
Low, R.N.; Francis, I.R.; Politoske, D.; Bennett, M. Crohn's disease evaluation: Comparison of contrast-enhanced MR imaging and single-phase helical CT scanning. J. Magn. Reson. Imaging 2000, 11, 127–135.
Sovak, M.; Terry, R.; Abramjuk, C.; Faberová, V.; Fiserova, M.; Laznicek, M.; Leuschner, J.; Malinak, J.; Zahradnik, P.; Seligson, A. Iosimenol, a low-viscosity nonionic dimer: Preclinical physicochemistry, pharmacology, and pharmacokinetics. Invest. Radiol. 2004, 39, 171–181.
[94]
Chai, C.M.; Rasmussen, H.; Eriksen, M.; Hvoslef, A.M.; Evans, P.; Newton, B.B.; Videm, S. Predicting cardiotoxicity propensity of the novel iodinated contrast medium GE-145: Ventricular fibrillation during left coronary arteriography in pigs. Acta Radiol. 2010, 51, 1007–1013.
[95]
Guo, R.; Wang, H.; Peng, C.; Shen, M.; Pan, M.; Cao, X.; Guixiang, Z.; Shi, X. X-ray attenuation property of dendrimer-entrapped gold nanoparticles. J. Phys. Chem. 2009, 114, 50–56.
[96]
Hainfeld, J.F.; O'Connor, M.J.; Dilmanian, F.A.; Slatkin, D.N.; Adams, D.J.; Smilowitz, H.M. Micro-CT enables microlocalization and quantification of Her2-targeted gold nanoparticles within tumor regions. Br. J. Radiol. 2011, 84, 526–533.
