Role of Magnetic Resonance in Drug Development

  • J. D. Kaggie
  • M. V. Haase
  • S. P. Campbell
  • C. M. Wright
  • M. J. Graves
  • K. K. ChanganiEmail author
Reference work entry


The pharmaceutical industry struggles with increasing costs to confidently validate drug targets and develop optimized drug molecules that successfully and safely translate efficacy into the clinic. Clinical prediction of success is imperative to reduce and recoup the costs associated with drug development. Strategies to enable clinical prediction rely on new technologies that can be employed earlier in the drug discovery process. In vivo imaging technologies, such as MRI, PET, SPECT, CT, and optical, are being employed exponentially to almost every aspect of the drug discovery process for earlier assessments. Quantitative imaging approaches for assessing disease end points are required to provide the precision to understand the efficacy and toxicity of new medicines rather than relying on blunt measures of clinical scoring. The bidirectional translation of preclinical and clinical drugs and drug assessments has provided new insights into the profiles of disease and toxicity rather than “snapshots” of pathology that occur using conventional ex vivo techniques. MRI technology has developed significantly over the last 20 years with respect to speed of acquisition, higher resolutions, and better tissue contrast imaging techniques. MRI enables new image-based evidence to successfully translate new chemical entities into clinical practice. This imaging technique provides a means to quantify disease and detect unprecedented rare and common disease mechanisms, which enables new medicines to be developed that can improve the quality of human life.


Preclinical MRI Drug discovery Imaging Biomarkers 


  1. 1.
    DiMasi JA, Grabowski HG, Hansen RW. Innovation in the pharmaceutical industry: new estimates of R&D costs. J Health Econ. 2016;47:20–33.CrossRefGoogle Scholar
  2. 2.
    Cook D, Brown D, Alexander R, March R, Morgan P, Satterthwaite G, et al. Lessons learned from the fate of AstraZeneca’s drug pipeline: a five-dimensional framework. Nat Rev Drug Discov. 2014;13(6):419–31.CrossRefGoogle Scholar
  3. 3.
    Contag PR. Whole-animal cellular and molecular imaging to accelerate drug development. Drug Discov Today. 2002;7(10):555–62.CrossRefGoogle Scholar
  4. 4.
    Simon R. Optimal two-stage designs for phase II clinical trials. Control Clin Trials. 1989;10(1):1–10.CrossRefGoogle Scholar
  5. 5.
    Beam TR, Gilbert DN, Kunin CM. General guidelines for the clinical evaluation of anti-infective drug products. Clin Infect Dis. 1992;15(Supplement 1):S5–S32.CrossRefGoogle Scholar
  6. 6.
    Lu Z-R. Application of biomedical imaging in drug discovery and development. Pharm Res. 2007;24(6):1170–1.CrossRefGoogle Scholar
  7. 7.
    Epstein FH. MR in mouse models of cardiac disease. NMR Biomed. 2007;20(3):238–55.CrossRefGoogle Scholar
  8. 8.
    Rudin M. Imaging in drug discovery and early clinical trials. New York: Springer Science & Business Media; 2005.Google Scholar
  9. 9.
    Kluetz PG, Meltzer CC, Villemagne VL, Kinahan PE, Chander S, Martinelli MA, et al. Combined PET/CT imaging in oncology: impact on patient management. Clin Positron Imaging. 2000;3(6):223–30.CrossRefGoogle Scholar
  10. 10.
    Meikle SR, Beekman FJ, Rose SE. Complementary molecular imaging technologies: high resolution SPECT, PET and MRI. Drug Discov Today Technol. 2006;3(2):187–94.CrossRefGoogle Scholar
  11. 11.
    Atkinson DJ, Edelman R. Cineangiography of the heart in a single breath hold with a segmented turboFLASH sequence. Radiology. 1991;178(2):357–60.CrossRefGoogle Scholar
  12. 12.
    O’Connor JP, Jackson A, Parker GJ, Jayson GC. DCE-MRI biomarkers in the clinical evaluation of antiangiogenic and vascular disrupting agents. Br J Cancer. 2007;96(2):189–95.CrossRefGoogle Scholar
  13. 13.
    Golman K, Petersson JS. Metabolic imaging and other applications of hyperpolarized 13 C 1. Acad Radiol. 2006;13(8):932–42.CrossRefGoogle Scholar
  14. 14.
    Möller HE, Chen XJ, Saam B, Hagspiel KD, Johnson GA, Altes TA, et al. MRI of the lungs using hyperpolarized noble gases. Magn Reson Med. 2002;47(6):1029–51.CrossRefGoogle Scholar
  15. 15.
    Beckmann N, Cannet C, Karmouty-Quintana H, Tigani B, Zurbruegg S, Blé F-X, et al. Lung MRI for experimental drug research. Eur J Radiol. 2007;64(3):381–96.CrossRefGoogle Scholar
  16. 16.
    Sobol WT. Recent advances in MRI technology: implications for image quality and patient safety. Saudi J Ophthalmol. 2012;26(4):393–9.CrossRefGoogle Scholar
  17. 17.
    Thompson A, Montalban X, Barkhof F, Brochet B, Filippi M, Miller D, et al. Diagnostic criteria for primary progressive multiple sclerosis: a position paper. Ann Neurol. 2000;47(6):831–5.CrossRefGoogle Scholar
  18. 18.
    Dean DG. The role of MRI in musculoskeletal practice: a clinical perspective. J Man Manip Ther. 2011;19(3):152–61.CrossRefGoogle Scholar
  19. 19.
    Neubauer S, Beer M, Landschütz W, Sandstede J, Seyfarth T, Lipke C, et al. Absolute quantification of high energy phosphate metabolites in normal, hypertrophied and failing human myocardium. MAGMA. 2000;11(1–2):73–4.CrossRefGoogle Scholar
  20. 20.
    Cosmus TC, Parizh M. Advances in whole-body MRI magnets. IEEE Trans Appl Supercond. 2011;21(3):2104–9.CrossRefGoogle Scholar
  21. 21.
    Lemieux L, Hagemann G, Krakow K, Woermann FG. Fast, accurate, and reproducible automatic segmentation of the brain in T1-weighted volume MRI data. Magn Reson Med. 1999;42(1):127–35.CrossRefGoogle Scholar
  22. 22.
    Miller D, Rudge P, Johnson G, Kendall B, Macmanus D, Moseley I, et al. Serial gadolinium enhanced magnetic resonance imaging in multiple sclerosis. Brain. 1988;111(4):927–39.CrossRefGoogle Scholar
  23. 23.
    Group IMSS. Interferon beta-1b is effective in relapsing-remitting multiple sclerosis I. Clinical results of a multicenter, randomized, double-blind, placebo-controlled trial. Neurology. 1993;43(4):655–61.CrossRefGoogle Scholar
  24. 24.
    Raynauld J-P, Martel-Pelletier J, Bias P, Laufer S, Haraoui B, Choquette D, et al. Protective effects of licofelone, a 5-lipoxygenase and cyclooxygenase inhibitor, versus naproxen on cartilage loss in knee osteoarthritis: a first multicentre clinical trial using quantitative MRI. Ann Rheum Dis. 2009;68(6):938–47.CrossRefGoogle Scholar
  25. 25.
    Wullschleger S, Garcia-Martinez JM, Duce SL. Quantitative MRI establishes the efficacy of PI3K inhibitor (GDC-0941) multi-treatments in PTEN-deficient mice lymphoma. Anticancer Res. 2012;32(2):415–20.Google Scholar
  26. 26.
    Yablonskiy DA, Haacke EM. Theory of NMR signal behavior in magnetically inhomogeneous tissues: the static dephasing regime. Magn Reson Med. 1994;32(6):749–63.CrossRefGoogle Scholar
  27. 27.
    Vernooij MW, Haag MD, van der Lugt A, Hofman A, Krestin GP, Stricker BH, et al. Use of antithrombotic drugs and the presence of cerebral microbleeds: the Rotterdam Scan Study. Arch Neurol. 2009;66(6):714–20.CrossRefGoogle Scholar
  28. 28.
    Mosher TJ, Dardzinski BJ, editors. Cartilage MRI T2 relaxation time mapping: overview and applications. Semin Musculoskelet Radiol. 2004;8:355–68. Copyright© 2004 by Thieme Medical Publishers, Inc., 333 Seventh Avenue, New York, NY 10001 USA.Google Scholar
  29. 29.
    Cheng HLM, Wright GA. Rapid high-resolution T1 mapping by variable flip angles: accurate and precise measurements in the presence of radiofrequency field inhomogeneity. Magn Reson Med. 2006;55(3):566–74.CrossRefGoogle Scholar
  30. 30.
    Mikac U, Sepe A, Kristl J, Baumgartner S. A new approach combining different MRI methods to provide detailed view on swelling dynamics of xanthan tablets influencing drug release at different pH and ionic strength. J Control Release. 2010;145(3):247–56.CrossRefGoogle Scholar
  31. 31.
    Detre JA, Zhang W, Roberts DA, Silva AC, Williams DS, Grandis DJ, et al. Tissue specific perfusion imaging using arterial spin labeling. NMR Biomed. 1994;7(1–2):75–82.CrossRefGoogle Scholar
  32. 32.
    Østergaard L. Principles of cerebral perfusion imaging by bolus tracking. J Magn Reson Imaging. 2005;22(6):710–7.CrossRefGoogle Scholar
  33. 33.
    Geraldes CF, Laurent S. Classification and basic properties of contrast agents for magnetic resonance imaging. Contrast Media Mol Imaging. 2009;4(1):1–23.CrossRefGoogle Scholar
  34. 34.
    Paldino MJ, Barboriak DP. Fundamentals of quantitative dynamic contrast-enhanced MR imaging. Magn Reson Imaging Clin N Am. 2009;17(2):277–89.CrossRefGoogle Scholar
  35. 35.
    Tofts PS, Brix G, Buckley DL, Evelhoch JL, Henderson E, Knopp MV, et al. Estimating kinetic parameters from dynamic contrast-enhanced T 1-weighted MRI of a diffusable tracer: standardized quantities and symbols. J Magn Reson Imaging. 1999;10(3):223–32.CrossRefGoogle Scholar
  36. 36.
    Parker GJ, Tofts PS. Pharmacokinetic analysis of neoplasms using contrast-enhanced dynamic magnetic resonance imaging. Top Magn Reson Imaging. 1999;10(2):130–42.CrossRefGoogle Scholar
  37. 37.
    Tofts PS, Kermode AG. Measurement of the blood-brain barrier permeability and leakage space using dynamic MR imaging. Fundamental concepts. Magn Reson Med. 1991;17(2):357–67.CrossRefGoogle Scholar
  38. 38.
    Backhaus M, Kamradt T, Sandrock D, Loreck D, Fritz J, Wolf K, et al. Arthritis of the finger joints: a comprehensive approach comparing conventional radiography, scintigraphy, ultrasound, and contrast-enhanced magnetic resonance imaging. Arthritis Rheum. 1999;42(6):1232–45.CrossRefGoogle Scholar
  39. 39.
    Yuan C, Kerwin WS, Ferguson MS, Polissar N, Zhang S, Cai J, et al. Contrast-enhanced high resolution MRI for atherosclerotic carotid artery tissue characterization. J Magn Reson Imaging. 2002;15(1):62–7.CrossRefGoogle Scholar
  40. 40.
    Low RN, Francis IR, 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(2):127–35.CrossRefGoogle Scholar
  41. 41.
    Roberts C, Issa B, Stone A, Jackson A, Waterton JC, Parker GJ. Comparative study into the robustness of compartmental modeling and model-free analysis in DCE-MRI studies. J Magn Reson Imaging. 2006;23(4):554–63.CrossRefGoogle Scholar
  42. 42.
    Sinkus R, Van Beers BE, Vilgrain V, DeSouza N, Waterton JC. Apparent diffusion coefficient from magnetic resonance imaging as a biomarker in oncology drug development. Eur J Cancer. 2012;48(4):425–31.CrossRefGoogle Scholar
  43. 43.
    Tatlisumak T, Carano RA, Takano K, Opgenorth TJ, Sotak CH, Fisher M. A novel endothelin antagonist, A-127722, attenuates ischemic lesion size in rats with temporary middle cerebral artery occlusion a diffusion and perfusion MRI study. Stroke. 1998;29(4):850–8.CrossRefGoogle Scholar
  44. 44.
    Mardor Y, Roth Y, Lidar Z, Jonas T, Pfeffer R, Maier SE, et al. Monitoring response to convection-enhanced taxol delivery in brain tumor patients using diffusion-weighted magnetic resonance imaging. Cancer Res. 2001;61(13):4971–3.Google Scholar
  45. 45.
    Kidwell CS, Saver JL, Mattiello J, Starkman S, Vinuela F, Duckwiler G, et al. Thrombolytic reversal of acute human cerebral ischemic injury shown by diffusion/perfusion magnetic resonance imaging. Ann Neurol. 2000;47(4):462–9.CrossRefGoogle Scholar
  46. 46.
    Le Bihan D, Breton E, Lallemand D, Grenier P, Cabanis E, Laval-Jeantet M. MR imaging of intravoxel incoherent motions: application to diffusion and perfusion in neurologic disorders. Radiology. 1986;161(2):401–7.CrossRefGoogle Scholar
  47. 47.
    Koh D-M, Collins DJ, Orton MR. Intravoxel incoherent motion in body diffusion-weighted MRI: reality and challenges. Am J Roentgenol. 2011;196(6):1351–61.CrossRefGoogle Scholar
  48. 48.
    Burdette JH, Elster AD, Ricci PE. Acute cerebral infarction: quantification of spin-density and T2 shine-through phenomena on diffusion-weighted MR images. Radiology. 1999;212(2):333–9.CrossRefGoogle Scholar
  49. 49.
    Joo I, Lee JM, Han JK, Choi BI. Intravoxel incoherent motion diffusion-weighted MR imaging for monitoring the therapeutic efficacy of the vascular disrupting agent CKD-516 in rabbit VX2 liver tumors. Radiology. 2014;272(2):417–26.CrossRefGoogle Scholar
  50. 50.
    Larsson HB, Rosenbaum S, Fritz-Hansen T. Quantification of the effect of water exchange in dynamic contrast MRI perfusion measurements in the brain and heart. Magn Reson Med. 2001;46(2):272–81.CrossRefGoogle Scholar
  51. 51.
    Dalvit C, Pevarello P, Tatò M, Veronesi M, Vulpetti A, Sundström M. Identification of compounds with binding affinity to proteins via magnetization transfer from bulk water. J Biomol NMR. 2000;18(1):65–8.CrossRefGoogle Scholar
  52. 52.
    Pellecchia M, Sem DS, Wüthrich K. NMR in drug discovery. Nat Rev Drug Discov. 2002;1(3):211–9.CrossRefGoogle Scholar
  53. 53.
    Wolff SD, Balaban RS. Magnetization transfer contrast (MTC) and tissue water proton relaxation in vivo. Magn Reson Med. 1989;10(1):135–44.CrossRefGoogle Scholar
  54. 54.
    Schmitt B, Zbýň Š, Stelzeneder D, Jellus V, Paul D, Lauer L, et al. Cartilage quality assessment by using glycosaminoglycan chemical exchange saturation transfer and 23Na MR imaging at 7 T. Radiology. 2011;260(1):257–64.CrossRefGoogle Scholar
  55. 55.
    Abramson SB, Attur M, Yazici Y. Prospects for disease modification in osteoarthritis. Nat Clin Pract Rheumatol. 2006;2(6):304–12.CrossRefGoogle Scholar
  56. 56.
    Weissleder R, Cheng HC, Bogdanova A, Bogdanov A. Magnetically labeled cells can be detected by MR imaging. J Magn Reson Imaging. 1997;7(1):258–63.CrossRefGoogle Scholar
  57. 57.
    Wang Y-XJ, Hussain SM, Krestin GP. Superparamagnetic iron oxide contrast agents: physicochemical characteristics and applications in MR imaging. Eur Radiol. 2001;11(11):2319–31.CrossRefGoogle Scholar
  58. 58.
    Weissleder R, Elizondo G, Wittenberg J, Rabito C, Bengele H, Josephson L. Ultrasmall superparamagnetic iron oxide: characterization of a new class of contrast agents for MR imaging. Radiology. 1990;175(2):489–93.CrossRefGoogle Scholar
  59. 59.
    Varallyay P, Nesbit G, Muldoon LL, Nixon RR, Delashaw J, Cohen JI, et al. Comparison of two superparamagnetic viral-sized iron oxide particles ferumoxides and ferumoxtran-10 with a gadolinium chelate in imaging intracranial tumors. Am J Neuroradiol. 2002;23(4):510–9.Google Scholar
  60. 60.
    Reimer P, Balzer T. Ferucarbotran (Resovist): a new clinically approved RES-specific contrast agent for contrast-enhanced MRI of the liver: properties, clinical development, and applications. Eur Radiol. 2003;13(6):1266–76.Google Scholar
  61. 61.
    Wang Y-XJ. Superparamagnetic iron oxide based MRI contrast agents: current status of clinical application. Quant Imaging Med Surg. 2011;1(1):35–40.Google Scholar
  62. 62.
    McAteer MA, Schneider JE, Ali ZA, Warrick N, Bursill CA, von zur Muhlen C, et al. Magnetic resonance imaging of endothelial adhesion molecules in mouse atherosclerosis using dual-targeted microparticles of iron oxide. Arterioscler Thromb Vasc Biol. 2008;28(1):77–83.CrossRefGoogle Scholar
  63. 63.
    Lanza GM, Lorenz CH, Fischer SE, Scott MJ, Cacheris WP, Kaufmann RJ, et al. Enhanced detection of thrombi with a novel fibrin-targeted magnetic resonance imaging agent. Acad Radiol. 1998;5:S173–S6.CrossRefGoogle Scholar
  64. 64.
    Botnar RM, Perez AS, Witte S, Wiethoff AJ, Laredo J, Hamilton J, et al. In vivo molecular imaging of acute and subacute thrombosis using a fibrin-binding magnetic resonance imaging contrast agent. Circulation. 2004;109(16):2023–9.CrossRefGoogle Scholar
  65. 65.
    Winter PM, Morawski AM, Caruthers SD, Fuhrhop RW, Zhang H, Williams TA, et al. Molecular imaging of angiogenesis in early-stage atherosclerosis with αvβ3-integrin–targeted nanoparticles. Circulation. 2003;108(18):2270–4.CrossRefGoogle Scholar
  66. 66.
    Sipkins DA, Cheresh DA, Kazemi MR, Nevin LM, Bednarski MD, Li K. Detection of tumor angiogenesis in vivo by alphaVbeta3-targeted magnetic resonance imaging. Nat Med. 1998;4(5):623–6.CrossRefGoogle Scholar
  67. 67.
    Anderson SA, Rader RK, Westlin WF, Null C, Jackson D, Lanza GM, et al. Magnetic resonance contrast enhancement of neovasculature with αvβ3-targeted nanoparticles. Magn Reson Med. 2000;44(3):433–9.CrossRefGoogle Scholar
  68. 68.
    Beckmann N, Mueggler T, Allegrini PR, Laurent D, Rudin M. From anatomy to the target: contributions of magnetic resonance imaging to preclinical pharmaceutical research. Anat Rec. 2001;265(2):85–100.CrossRefGoogle Scholar
  69. 69.
    McAteer MA, Akhtar AM, von zur Muhlen C, Choudhury RP. An approach to molecular imaging of atherosclerosis, thrombosis, and vascular inflammation using microparticles of iron oxide. Atherosclerosis. 2010;209(1):18–27.CrossRefGoogle Scholar
  70. 70.
    McAteer MA, Mankia K, Ruparelia N, Jefferson A, Nugent HB, Stork L-A, et al. A leukocyte-mimetic magnetic resonance imaging contrast agent homes rapidly to activated endothelium and tracks with atherosclerotic lesion macrophage content. Arterioscler Thromb Vasc Biol. 2012;32(6):1427–35.CrossRefGoogle Scholar
  71. 71.
    McAteer MA, Choudhury RP. Targeted molecular imaging of vascular inflammation in cardiovascular disease using nano- and micro-sized agents. Vascul Pharmacol. 2013;58(1):31–8.CrossRefGoogle Scholar
  72. 72.
    Bergin C, Pauly J, Macovski A. Lung parenchyma: projection reconstruction MR imaging. Radiology. 1991;179(3):777–81.CrossRefGoogle Scholar
  73. 73.
    Gold GE, Thedens DR, Pauly JM, Fechner K, Bergman G, Beaulieu CF, et al. MR imaging of articular cartilage of the knee: new methods using ultrashort TEs. AJR Am J Roentgenol. 1998;170(5):1223–6.CrossRefGoogle Scholar
  74. 74.
    Weiger M, Pruessmann KP, Hennel F. MRI with zero echo time: hard versus sweep pulse excitation. Magn Reson Med. 2011;66(2):379–89.CrossRefGoogle Scholar
  75. 75.
    Ahn C, Kim J, Cho Z. High-speed spiral-scan echo planar NMR imaging-I. IEEE Trans Med Imaging. 1986;5(1):2–7.CrossRefGoogle Scholar
  76. 76.
    Irarrazabal P, Nishimura DG. Fast three dimensional magnetic resonance imaging. Magn Reson Med. 1995;33(5):656–62.CrossRefGoogle Scholar
  77. 77.
    Nielles-Vallespin S, Weber M-A, Bock M, Bongers A, Speier P, Combs SE, et al. 3D radial projection technique with ultrashort echo times for sodium MRI: clinical applications in human brain and skeletal muscle. Magn Reson Med. 2007;57(1):74–81.CrossRefGoogle Scholar
  78. 78.
    Beckmann N, Tigani B, Mazzoni L, Fozard JR. Techniques: magnetic resonance imaging of the lung provides potential for non-invasive preclinical evaluation of drugs. Trends Pharmacol Sci. 2003;24(10):550–4.CrossRefGoogle Scholar
  79. 79.
    Takahashi M, Togao O, Obara M, van Cauteren M, Ohno Y, Kuro-O M, et al. Ultra-short echo time (UTE) MR imaging of the lung: comparison between normal and emphysematous lungs in mutant mice. J Magn Reson Imaging. 2010;32(2):326–33.CrossRefGoogle Scholar
  80. 80.
    Strobel K, Hoerr V, Schmid F, Wachsmuth L, Löffler B, Faber C. Early detection of lung inflammation: exploiting T1-effects of iron oxide particles using UTE MRI. Magn Reson Med. 2012;68(6):1924–31.CrossRefGoogle Scholar
  81. 81.
    Mentore K, Froh DK, de Lange EE, Brookeman JR, Paget-Brown AO, Altes TA. Hyperpolarized He 3 MRI of the lung in cystic fibrosis: assessment at baseline and after bronchodilator and airway clearance treatment. Acad Radiol. 2005;12(11):1423–9.CrossRefGoogle Scholar
  82. 82.
    Bianchi A, Ozier A, Ousova O, Raffard G, Crémillieux Y. Ultrashort-TE MRI longitudinal study and characterization of a chronic model of asthma in mice: inflammation and bronchial remodeling assessment. NMR Biomed. 2013;26(11):1451–9.CrossRefGoogle Scholar
  83. 83.
    Bianchi MC, Tosetti M, Battini R, Manca ML, Mancuso M, Cioni G, et al. Proton MR spectroscopy of mitochondrial diseases: analysis of brain metabolic abnormalities and their possible diagnostic relevance. Am J Neuroradiol. 2003;24(10):1958–66.Google Scholar
  84. 84.
    Rajagopalan B, Blackledge M, McKenna W, Bolas N, Radda G. Measurement of phosphocreatine to ATP ratio in normal and diseased human heart by 31P magnetic resonance spectroscopy using the rotating frame-depth selection techniques. Ann N Y Acad Sci. 1987;508(1):321–32.CrossRefGoogle Scholar
  85. 85.
    Li X, Jin H, Lu Y, Oh J, Chang S, Nelson SJ. Identification of MRI and 1H MRSI parameters that may predict survival for patients with malignant gliomas. NMR Biomed. 2004;17(1):10–20.CrossRefGoogle Scholar
  86. 86.
    Hoang T, Bluml S, Dubowitz D, Moats R, Kopyov O, Jacques D, et al. Quantitative proton-decoupled 31P MRS and 1H MRS in the evaluation of Huntington’s and Parkinson’s diseases. Neurology. 1998;50(4):1033–40.CrossRefGoogle Scholar
  87. 87.
    Neubauer S, Horn M, Cramer M, Harre K, Newell JB, Peters W, et al. Myocardial phosphocreatine-to-ATP ratio is a predictor of mortality in patients with dilated cardiomyopathy. Circulation. 1997;96(7):2190–6.CrossRefGoogle Scholar
  88. 88.
    Gupta R, Pandey R, Khan E, Mittal P, Gujral R, Chhabra D. Intracranial tuberculomas: MRI signal intensity correlation with histopathology and localised proton spectroscopy. Magn Reson Imaging. 1993;11(3):443–9.CrossRefGoogle Scholar
  89. 89.
    Yeung DK, Yang W-T, Tse GM. Breast cancer: in vivo proton MR spectroscopy in the characterization of histopathologic subtypes and preliminary observations in axillary node metastases 1. Radiology. 2002;225(1):190–7.CrossRefGoogle Scholar
  90. 90.
    Lanza GM, Yu X, Winter PM, Abendschein DR, Karukstis KK, Scott MJ, et al. Targeted antiproliferative drug delivery to vascular smooth muscle cells with a magnetic resonance imaging nanoparticle contrast agent implications for rational therapy of restenosis. Circulation. 2002;106(22):2842–7.CrossRefGoogle Scholar
  91. 91.
    Berglund M, Wieser ME. Isotopic compositions of the elements 2009 (IUPAC technical report). Pure Appl Chem. 2011;83(2):397–410.CrossRefGoogle Scholar
  92. 92.
    Walker TG, Happer W. Spin-exchange optical pumping of noble-gas nuclei. Rev Mod Phys. 1997;69(2):629.CrossRefGoogle Scholar
  93. 93.
    Appelt S, Baranga AB-A, Erickson C, Romalis M, Young A, Happer W. Theory of spin-exchange optical pumping of 3 He and 129 Xe. Phys Rev A. 1998;58(2):1412.CrossRefGoogle Scholar
  94. 94.
    Hausser K, Stehlik D. Dynamic nuclear polarization in liquids. Adv Magn Reson. 1968;3:79–139.CrossRefGoogle Scholar
  95. 95.
    McCarney ER, Armstrong BD, Lingwood MD, Han S. Hyperpolarized water as an authentic magnetic resonance imaging contrast agent. Proc Natl Acad Sci. 2007;104(6):1754–9.CrossRefGoogle Scholar
  96. 96.
    Rzedzian R, Mansfield P, Doyle M, Guilfoyle D, Chapman B, Coupland R, et al. Real-time nuclear magnetic resonance clinical imaging in paediatrics. Lancet. 1983;322(8362):1281–2.CrossRefGoogle Scholar
  97. 97.
    Glöggler S, Raue M, Colell J, Türschmann P, Liebisch A, Mang T, et al. Online monitoring of intelligent polymers for drug release with hyperpolarized xenon. ChemPhysChem. 2012;13(18):4120–3.CrossRefGoogle Scholar
  98. 98.
    Edwards R, Wilkie D, Dawson MJ, Gordon R, Shaw D. Clinical use of nuclear magnetic resonance in the investigation of myopathy. Lancet. 1982;319(8274):725–31.CrossRefGoogle Scholar
  99. 99.
    Bottomley PA, Hardy CJ, Roemer PB, Mueller OM. Proton-decoupled, overhauser-enhanced, spatially localized carbon-13 spectroscopy in humans. Magn Reson Med. 1989;12(3):348–63.CrossRefGoogle Scholar
  100. 100.
    Khemtong C, Carpenter NR, Lumata LL, Merritt ME, Moreno KX, Kovacs Z, et al. Hyperpolarized 13C NMR detects rapid drug-induced changes in cardiac metabolism. Magn Reson Med. 2015;74(2):312–9.CrossRefGoogle Scholar
  101. 101.
    Buckler AJ, Bresolin L, Dunnick NR, Sullivan DC, Group. A collaborative enterprise for multi-stakeholder participation in the advancement of quantitative imaging. Radiology. 2011;258(3):906–14.CrossRefGoogle Scholar
  102. 102.
    Ellingson BM, Bendszus M, Boxerman J, Barboriak D, Erickson BJ, Smits M, et al. Consensus recommendations for a standardized Brain Tumor Imaging Protocol in clinical trials. Neuro Oncol. 2015;17(9):1188–98.Google Scholar
  103. 103.
    Woodcock J, Woosley R. The FDA critical path initiative and its influence on new drug development. Annu Rev Med. 2008;59:1–12.CrossRefGoogle Scholar
  104. 104.
    McGibney G, Smith M, Nichols S, Crawley A. Quantitative evaluation of several partial fourier reconstruction algorithms used in MRI. Magn Reson Med. 1993;30(1):51–9.CrossRefGoogle Scholar
  105. 105.
    McKenzie CA, Yeh EN, Ohliger MA, Price MD, Sodickson DK. Self-calibrating parallel imaging with automatic coil sensitivity extraction. Magn Reson Med. 2002;47(3):529–38.CrossRefGoogle Scholar
  106. 106.
    Lustig M, Donoho DL, Santos JM, Pauly JM. Compressed sensing MRI. IEEE Signal Process Mag. 2008;25(2):72–82.CrossRefGoogle Scholar
  107. 107.
    Lustig M, Donoho D, Pauly JM. Sparse MRI: the application of compressed sensing for rapid MR imaging. Magn Reson Med. 2007;58(6):1182–95.CrossRefGoogle Scholar
  108. 108.
    Cheng JY, Hanneman K, Zhang T, Alley MT, Lai P, Tamir JI, et al. Comprehensive motion-compensated highly accelerated 4D flow MRI with ferumoxytol enhancement for pediatric congenital heart disease. J Magn Reson Imaging. 2016;43(6):1355–68.CrossRefGoogle Scholar
  109. 109.
    Misiak M, Koźmiński W, Chmurski K, Kazimierczuk K. Study of near-symmetric cyclodextrins by compressed sensing 2D NMR. Magn Reson Chem. 2013;51(2):110–5.Google Scholar
  110. 110.
    Davis ME, Brewster ME. Cyclodextrin-based pharmaceutics: past, present and future. Nat Rev Drug Discov. 2004;3(12):1023–35.CrossRefGoogle Scholar
  111. 111.
    Ma D, Gulani V, Seiberlich N, Liu K, Sunshine JL, Duerk JL, et al. Magnetic resonance fingerprinting. Nature. 2013;495(7440):187–92.CrossRefGoogle Scholar
  112. 112.
    Lesko LJ, Rowland M, Peck CC, Blaschke TF. Optimizing the science of drug development: opportunities for better candidate selection and accelerated evaluation in humans. J Clin Pharmacol. 2000;40(8):803–14.CrossRefGoogle Scholar
  113. 113.
    (ESR) ESoR. Magnetic Resonance Fingerprinting – a promising new approach to obtain standardized imaging biomarkers from MRI. Insights Imaging. 2015;6(2):163–5.CrossRefGoogle Scholar
  114. 114.
    Freeborough PA, Fox NC. MR image texture analysis applied to the diagnosis and tracking of Alzheimer’s disease. IEEE Trans Med Imaging. 1998;17(3):475–8.CrossRefGoogle Scholar
  115. 115.
    Sutton RN, Hall EL. Texture measures for automatic classification of pulmonary disease. IEEE Trans Comput. 1972;21(7):667–76.CrossRefGoogle Scholar
  116. 116.
    Kjaer L, Ring P, Thomsen C, Henriksen O. Texture analysis in quantitative MR imaging: tissue characterisation of normal brain and intracranial tumours at 1.5 T. Acta Radiol. 1995;36(2):127–35.CrossRefGoogle Scholar
  117. 117.
    Chen G, Jespersen S, Pedersen M, Pang Q, Horsman MR, Stødkilde JH. Evaluation of anti-vascular therapy with texture analysis. Anticancer Res. 2005;25(5):3399–405.Google Scholar
  118. 118.
    Goh V, Ganeshan B, Nathan P, Juttla JK, Vinayan A, Miles KA. Assessment of response to tyrosine kinase inhibitors in metastatic renal cell cancer: CT texture as a predictive biomarker. Radiology. 2011;261(1):165–71.CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • J. D. Kaggie
    • 1
    • 3
  • M. V. Haase
    • 2
  • S. P. Campbell
    • 2
  • C. M. Wright
    • 2
  • M. J. Graves
    • 1
    • 3
  • K. K. Changani
    • 2
    Email author
  1. 1.Department of Radiology, Box 218University of CambridgeCambridgeUK
  2. 2.In Vivo Imaging (UK), Bioimaging, Platform Technology and SciencesGlaxoSmithKline, Medicines Research CentreStevenage, HertfordshireUK
  3. 3.Cambridge University Hospitals NHS Foundation TrustAddenbrooke’s HospitalCambridgeUK

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