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The Application of In Vivo MRI and MRS in Phenomic Studies of Murine Models of Disease

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Modern Magnetic Resonance

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Abstract

As we enter the post-genomic era, understanding the role and function of single or group of genes in the context of a whole functioning organism, has become paramount in terms of human health. Much of this work is being carried out in rodent models of diseases, requiring the use of in vivo non-invasive imaging techniques to study the animals. Here we review the use of magnetic resonance imaging (MRI) and multi-nuclear magnetic resonance spectroscopy (MRS) for the phenotypic characterization of the ever increasing numbers of murine models of health and disease. We describe the current MRI and MRS strategies being applied to the characterization of these models and point out potential pitfalls and limitations of the available techniques. Finally, we review the latest advances in MRI and MRS and their potential application to pre-clinical studies.

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References

  1. Aitman T, Dhillon P, Guerts AR. A RATional choice for translational research?. Dis Model Mech. 2016;9:1069.

    Article  Google Scholar 

  2. Haluzik M, Colombo C, Gavrilova O, Chua S, Wolf N, Chen M, Stannard B, Dietz KR, Le Roith D, Reitman ML. Genetic background (C57BL/6J versus FVB/N) strongly influences the severity of diabetes and insulin resistance in ob/ob mice. Endocrinology. 2004;145:3258.

    Article  CAS  Google Scholar 

  3. Blackland SJ, Buckley DL, Bui JD, Phillips MI. NMR microscopy–beginnings and new directions. MAGMA. 1999;9:112.

    Google Scholar 

  4. Ma J. Dixon techniques for water and fat imaging. J Magn Reson Imaging. 2008;28(3):543.

    Article  Google Scholar 

  5. Hall AS, Barnard B, McArthur P, Gilderdale DJ, Young IR, Bydder GM. Investigation of a whole-body receiver coil operating at liquid nitrogen temperatures. Magn Reson Med. 1988;7:230.

    Article  CAS  Google Scholar 

  6. Wright AC, Song HK, Wehrli FW. In vivo MR micro imaging with conventional radiofrequency coils cooled to 77 degrees K. Magn Reson Med. 2000;43:163.

    Article  CAS  Google Scholar 

  7. Hurlston SE, Brey WW, Suddarth SA, Johnston GA. A high-temperature superconducting Helmholtz probe for microscopy at 9.4 T. Magn Reson Med. 1999;41:1032.

    Article  CAS  Google Scholar 

  8. Ginefri JC, Darasse L, Crozat P. High-temperature superconducting surface coil for in vivo microimaging of the human skin. Magn Reson Med. 2001;45:376.

    Article  CAS  Google Scholar 

  9. Darrasse L, Ginefri J-C. Perspectives with cryogenic RF probes in biomedical MRI. Biochimie. 2003;85:915.

    Article  CAS  Google Scholar 

  10. Hoult DI, Richards R. The signal-to-noise ratio of the nuclear magnetic resonance experiment. J Magn Reson. 1976;24:71.

    Google Scholar 

  11. Niendorf T, Pohlmann A, Reimann HM, Waiczies H, Peper E, Huelnhagen T, Seeliger E, Schreiber A, Kettritz R, Strobel K, Ku M-C, Waiczies S. Advancing Cardiovascular, Neurovascular, and Renal Magnetic Resonance Imaging in Small Rodents Using Cryogenic Radiofrequency Coil Technology. Front Pharmacol. 2015;6:255.

    Article  Google Scholar 

  12. Junge S. In: Vaughan JT, Griffiths JR, editors. eMagRes – Encyclopedia of magnetic resonance. Hobeken: Wiley; 2012. p. 505–12.

    Google Scholar 

  13. Kovacs H, Moskau D, Spaul M. Cryogenically cooled probes - a leap in NMR technology. Prog Nucl Magn Reson Imag. 2005;40:1310.

    Google Scholar 

  14. Baltes C, Radzwill N, Bosshard S, Marek D, Rudin M. Micro MRI of the mouse brain using a novel 400 MHz cryogenic quadrature RF probe. NMR Biomed. 2009;22(8):834.

    Article  Google Scholar 

  15. Roemer PB, Edelstein WA, Hayes CE, et al. The NMR phased array. Magn Reson Med. 1990;16:192.

    Article  CAS  Google Scholar 

  16. Carlson JW. An algorithm for NMR imaging reconstruction based on multiple RF receiver coils. J Magn Reson. 1987;42:953.

    Google Scholar 

  17. Garbow JR, McIntosh C, Conradi MS. Actively Decoupled Transmit-Receive Coil-Pair for Mouse Brain MRI. Concepts Magn Reson Part B Magn Reson Eng. 2008;33B(4):252.

    Article  Google Scholar 

  18. MacFall JR, Pele NJ, Vavrek RM. Correction of spatially dependent phase shifts for partial Fourier imaging. Magn Reson Imaging. 1988;6:143.

    Article  CAS  Google Scholar 

  19. Bock NA, Konyer NB, Henkelman RM. Multiple-mouse MRI. Magn Reson Med. 2003;49:158.

    Article  Google Scholar 

  20. Dazai J, Spring S, Cahill LS, Henkelman RM. Multiple-mouse neuroanatomical magnetic resonance imaging. J Vis Exp. 2011;48:e2497.

    Google Scholar 

  21. Walker T, Michaelides C, Ekonomou A, et al. Dissociation between iron accumulation and ferritin upregulation in the aged substantia nigra: attenuation by dietary restriction. Aging (Albany NY). 2016;8:2488.

    Article  CAS  Google Scholar 

  22. Smith BR, Johnson GA, Groman EV, Linney E. Magnetic resonance microscopy of mouse embryos. PNAS. 1994;91:3530.

    Article  CAS  Google Scholar 

  23. Munasinghe JP, Gresham GA, Carpenter TA. Magnetic resonance imaging of the normal mouse brain: comparison with histologic sections. Lab Anim Sci. 1995;45:674.

    CAS  Google Scholar 

  24. Smith BR. Magnetic resonance microscopy in cardiac development. Microsc Res Tech. 2001;52:323.

    Article  CAS  Google Scholar 

  25. Benveniste H, Kim K, Zhang L, Johnson GA. Magnetic resonance microscopy of the C57BL mouse brain. Neuroimage. 2000;11:601.

    Article  CAS  Google Scholar 

  26. Jacobs RE, Fraser SE. Imaging neuronal development with magnetic resonance imaging (NMR) microscopy. J Neurosci Methods. 1994;54(2):189.

    Article  CAS  Google Scholar 

  27. Dhenain M, Ruffins SW, Jacobs RE. Three-dimensional digital mouse atlas using high-resolution MRI. Dev Biol. 2001;232:458.

    Article  CAS  Google Scholar 

  28. Ahrens ET, Rothbacher U, Jacobs RE, Fraser SE. A model for MRI contrast enhancement using T1 agents. PNAS. 1998;95:8443.

    Article  CAS  Google Scholar 

  29. Johnson GA, Hedlund LW, Cofer GP, Suddarth SA. Magnetic resonance microscopy in the life sciences. Rev Magn Reson Med. 1992;4:187.

    Google Scholar 

  30. Johnson GA, Badea A, Brandenburg J, et al. Waxholm space: an image-based reference for coordinating mouse brain research. Neuroimage. 2010;53:365.

    Article  Google Scholar 

  31. MacKenzie-Graham A, et al. A multimodal, multidimensional atlas of the C57BL/6J mouse brain. J Anat. 2004;204:93.

    Article  Google Scholar 

  32. Johnson GA, Calabrese E, Badea A, et al. A multidimensional magnetic resonance histology atlas of the Wistar rat brain. Neuroimage. 2012;62:1848.

    Article  Google Scholar 

  33. Franklin K, Paxinos G. The mouse brain in stereotaxic coordinates. San Diego: Academic; 1997.

    Google Scholar 

  34. Schwarz AJ, et al. A stereotaxic MRI template set for the rat brain with tissue class distribution maps and co-registered anatomical atlas: application to pharmacological MRI. Neuroimage. 2006;32:538.

    Article  Google Scholar 

  35. Sergejeva M, Papp EA, Bakker R, et al. Anatomical landmarks for registration of experimental image data to volumetric rodent brain atlasing templates. J Neurosci Methods. 2015;240:161.

    Article  Google Scholar 

  36. Dorr AE, Lerch JP, Spring S, Kabani N, Henkelman RM. High resolution three-dimensional brain atlas using an average magnetic resonance image of 40 adult C57Bl/6J mice. Neuroimage. 2008;42:60.

    Article  CAS  Google Scholar 

  37. Ma Y, Hof PR, Grant SC, et al. A three-dimensional digital atlas database of the adult C57BL/6J mouse brain by magnetic resonance microscopy. Neuroscience. 2005;135:1203.

    Article  CAS  Google Scholar 

  38. Lerch JP, Gazdzinski L, Germann J, et al. Wanted dead or alive? The tradeoff between in-vivo versus ex-vivo MR brain imaging in the mouse. Front Neuroinform. 2012;6:6.

    Article  Google Scholar 

  39. Delora A, et al. A simple rapid process for semi-automated brain extraction from magnetic resonance images of the whole mouse head. J Neurosci Methods. 2016;257:185.

    Article  Google Scholar 

  40. Sharief AA, Badea A, Dale AM, Johnson GA. Automated segmentation of the actively stained mouse brain using multi-spectral MR microscopy. Neuroimage. 2008;39:136.

    Article  Google Scholar 

  41. Ali AA, Dale AM, Badea A, Johnson GA. Automated segmentation of neuroanatomical structures in multispectral MR microscopy of the mouse brain. Neuroimage. 2005;27:425.

    Article  Google Scholar 

  42. Oguz I, Zhang H, Rumple A, Sonka M. RATS: Rapid Automatic Tissue Segmentation in rodent brain MRI. J Neurosci Methods. 2014;221:175.

    Article  Google Scholar 

  43. Lancelot S, et al. A multi-atlas based method for automated anatomical rat brain MRI segmentation and extraction of PET activity. PLoS One. 2014;9:e109113. https://doi.org/10.1371/journal.pone.0109113.

    Article  CAS  Google Scholar 

  44. Nie J, Shen D. Automated segmentation of mouse brain images using multi-atlas multi-ROI deformation and label fusion. Neuroinformatics. 2013;11:35.

    Article  Google Scholar 

  45. Ma D, Cardoso MJ, Modat M, et al. Automatic structural parcellation of mouse brain MRI using multi-atlas label fusion. PLoS One. 2014;9:e86576. https://doi.org/10.1371/journal.pone.0086576.

    Article  CAS  Google Scholar 

  46. Jorge Cardoso M, Leung K, Modat M, et al. STEPS: Similarity and Truth Estimation for Propagated Segmentations and its application to hippocampal segmentation and brain parcelation. Med Image Anal. 2013;17(6):671.

    Article  CAS  Google Scholar 

  47. Chapon C, Franconi F, Roux J, Marescaux L, Le Jeune JJ, Lemaire L. In utero time-course assessment of mouse embryo development using high resolution magnetic resonance imaging. Anat Embryol. 2002;206(1–2):131.

    CAS  Google Scholar 

  48. Johnson GA, Cofer GP, Gewalt SL, Hedlund LW. Morphologic phenotyping with MR microscopy: the visible mouse. Radiology. 2002;222:789.

    Article  Google Scholar 

  49. Adams D, Baldock R, Bhattacharya S, et al. Bloomsbury report on mouse embryo phenotyping: recommendations from the IMPC workshop on embryonic lethal screening. Dis Model Mech. 2013;6:571.

    Article  Google Scholar 

  50. Petiet A, Kaufman MH, Goddeeris MM, et al. High-resolution magnetic resonance histology of the embryonic and neonatal mouse: a 4D atlas and morphologic database. PNAS. 2008;105:12331.

    Article  Google Scholar 

  51. Cleary JO, et al. Magnetic resonance virtual histology for embryos: 3D atlases for automated high-throughput phenotyping. Neuroimage. 2011;15:769.

    Article  Google Scholar 

  52. Smith BR. In: Low CW, editor. Development biology protocols. Totawa: Humana Press Inc.; 2000. p. 211.

    Google Scholar 

  53. Schneider JE, Bamforth SD, Farthing CR, Clarke K, Neubauer S, Bhattacharya S. High-resolution imaging of normal anatomy, and neural and adrenal malformations in mouse embryos using magnetic resonance microscopy. J Anat. 2003;202:239.

    Article  Google Scholar 

  54. Zhang X, Schneider JE, Portnoy S, et al. Comparative SNR for high-throughput mouse embryo MR microscopy. Magn Reson Med. 2010;63:1703.

    Article  Google Scholar 

  55. Zaymadi et al., Mouse embryonic phenotyping by morphometric analysis of MR images. Physiol Genomics. 2010;42A:89.

    Google Scholar 

  56. Norris FC, et al. Segmentation propagation using a 3D embryo atlas for high-throughput MRI phenotyping: comparison and validation with manual segmentation. Magn Reson Med. 2013;69(3):877.

    Article  Google Scholar 

  57. Redwine JM, Kosofsky B, Jacobs RE, Games D, Reilly JF, Morrison JH, Young WG, Bloom FE. Dentate gyrus volume is reduced before onset of plaque formation in PDAPP mice: a magnetic resonance microscopy and stereologic analysis. PNAS. 2003;100(3):1381.

    Article  CAS  Google Scholar 

  58. Lin YJ, Koretsky AP. Manganese ion enhances T1-weighted MRI during brain activation: an approach to direct imaging of brain function. Magn Reson Med. 1997;38(3):378.

    Article  CAS  Google Scholar 

  59. Natt O, Watanbe T, Boretius S, Radulovic J, Frahm J, Michaelis T. High-resolution 3D MRI of mouse brain reveals small cerebral structures in vivo. J Neurosci Methods. 2001;120:203.

    Article  Google Scholar 

  60. Watanabe T, Natt O, Boretius S, Frahm J, Michaelis T. Mapping of retinal projections in the living rat using high-resolution 3D gradient-echo MRI with Mn2+-induced contrast. Magn Reson Med. 2001;46:424.

    Article  CAS  Google Scholar 

  61. Aoki I, Lin Wu YJ, Silva AC, Lynch RM, Koretsky AP. In vivo detection of neuroarchitecture in the rodent brain using manganese-enhanced MRI. Neuroimage. 2004;22:1046.

    Article  Google Scholar 

  62. Kamsu JM, et al. Structural layers of ex vivo rat hippocampus at 7T MRI. PLoS One. 2013;8:e76135. https://doi.org/10.1371/journal.pone.0076135.

    Article  CAS  Google Scholar 

  63. Kooy FR, Verhoye M, Lemmon V, van Der Linden A. Brain studies of mouse models for neurogenetic disorders using in vivo magnetic resonance imaging (MRI). Eur J Hum Genet. 2001;9:153.

    Article  CAS  Google Scholar 

  64. Benveniste H, Blackband S. MR microscopy and high resolution small animal MRI: applications in neuroscience research. Prog Neurobiol. 2002;67:393.

    Article  Google Scholar 

  65. Spring S, Lerch JP, Henkelman RM. Sexual dimorphism revealed in the structure of the mouse brain using three-dimensional magnetic resonance imaging. Neuroimage. 2007;35:1424.

    Article  Google Scholar 

  66. Spring S, Lerch JP, Wetzel MK, Evans AC, Henkelman RM. Cerebral asymmetries in 12-week-old C57Bl/6J mice measured by magnetic resonance imaging. Neuroimage. 2010;50:409.

    Article  Google Scholar 

  67. Maheswaran S, et al. Longitudinal regional brain volume changes quantified in normal aging and Alzheimer's APP x PS1 mice using MRI. Brain Res. 2009;1270:19.

    Article  CAS  Google Scholar 

  68. Driscoll I, et al. The aging hippocampus: a multi-level analysis in the rat. Neuroscience. 2006;139:1173.

    Article  CAS  Google Scholar 

  69. Chen CC, Tung YY, Chang C. A lifespan MRI evaluation of ventricular enlargement in normal aging mice. Neurobiol Aging. 2011;32:2299.

    Article  Google Scholar 

  70. Hebert F, et al. Cortical atrophy and hypoperfusion in a transgenic mouse model of Alzheimer’s disease. Neurobiol Aging. 2013;34:1644.

    Article  Google Scholar 

  71. Mengler L, Khmelinskii A, Diedenhofen M, et al. Brain maturation of the adolescent rat cortex and striatum: changes in volume and myelination. Neuroimage. 2014;84:35.

    Article  Google Scholar 

  72. Hammelrath L, et al. Morphological maturation of the mouse brain: An in vivo MRI and histology investigation. Neuroimage. 2016;125:144.

    Article  Google Scholar 

  73. Lau JC, Lerch JP, Sled JG, et al. Longitudinal neuroanatomical changes determined by deformation-based morphometry in a mouse model of Alzheimer’s disease. Neuroimage. 2008;42:19.

    Article  Google Scholar 

  74. Ward RJ, Zucca FA, Duyn JH, Crichton RR, Zecca L. The role of iron in brain ageing and neurodegenerative disorders. Lancet Neurol. 2014;13:1045.

    Article  CAS  Google Scholar 

  75. Neiman BJ, Lerch JP, Bock NA, et al. Mouse behavioral mutants have neuroimaging abnormalities. Hum Brain Mapp. 2007;28:567.

    Article  Google Scholar 

  76. Lerch JP, Yiu AP, et al. Maze training in mice induces MRI-detectable brain shape changes specific to the type of learning. Neuroimage. 2011;54:2086.

    Article  Google Scholar 

  77. Ellegood J, Anagnostou E, Babineau BA, et al. Clustering autism: using neuroanatomical differences in 26 mouse models to gain insight in to the heterogeneity. Mol Psychiatry. 2015;20:118.

    Article  CAS  Google Scholar 

  78. Ellegood J, Babineau BA, Henkelman RM, Lerch JP, Crawley JN. Neuroanatomical analysis of the BTBR mouse model of autism using magnetic resonance imaging and diffusion tensor imaging. Neuroimage. 2013;70:288.

    Article  Google Scholar 

  79. Hollander E, Anagnostou E, Chaplin W, et al. Striatal volume on magnetic resonance imaging and repetitive behaviors in autism. Biol Psychiatry. 2005;58:226.

    Article  Google Scholar 

  80. Langen M, Bos D, Noordermeer SD, et al. Changes in the development of striatum are involved in repetitive behavior in autism. Biol Psychiatry. 2014;76:405.

    Article  Google Scholar 

  81. Cheung C, Yu K, Fung G, et al. Autistic disorders and schizophrenia: related or remote? An anatomical likelihood estimation. PLoS One. 2010;5:e12233.

    Article  CAS  Google Scholar 

  82. Fenlon LR, et al. Formation of functional areas in the cerebral cortex is disrupted in a mouse model of autism spectrum disorder. Neural Dev. 2015;10:10.

    Article  Google Scholar 

  83. Dodero L, Damiano M, Galbusera A, et al. Neuroimaging evidence of major morpho-anatomical and functional abnormalities in the BTBR T+TF/J mouse model of autism. PLoS One. 2013;8:e76655. https://doi.org/10.1371/journal.pone.00766551.

    Article  CAS  Google Scholar 

  84. Sforazzini F, Bertero A, Dodero L, et al. Altered functional connectivity networks in acallosal and socially impaired BTBR mice. Brain Struct Funct. 2016;221:941. https://doi.org/10.1007/s00429-014-0948-9.

    Article  Google Scholar 

  85. Kana RK, Uddin LQ, Kenet T, Chugani D, Muller RA. Brain connectivity in autism. Front Hum Neurosci. 2014;8:349.

    Article  Google Scholar 

  86. Michalon A, Bruns A, Risterucci C, et al. Chronic metabotropic glutamate receptor 5 inhibition corrects local alterations of brain activity and improves cognitive performance in fragile X mice. Biol Psychiatry. 2014;75:189.

    Article  CAS  Google Scholar 

  87. Ross R, Leger L, Guardo R, De Guise J, Pike BG. Adipose tissue volume measured by magnetic resonance imaging and computerized tomography in rats. J Appl Physiol. 1991;70:2164.

    Article  CAS  Google Scholar 

  88. Fowler PA, Fuller MF, Glasbey CA, Cameron GG, McNeill G, Foster MA. Validation of the in vivo measurement of adipose tissue by magnetic resonance imaging of lean and obese pigs. Am J Clin Nutr. 1992;56:7.

    Article  CAS  Google Scholar 

  89. Ishikawa M, Koga K. Measurement of abdominal fat by magnetic resonance imaging of OLETF rats, an animal model of NIDDM. Magn Reson Imag. 1998;16:45.

    Article  CAS  Google Scholar 

  90. Tang H, Vasselli JR, Wu EX, Boozer CN, Gallagher D. High-resolution magnetic resonance imaging tracks changes in organ and tissue mass in obese and aging rats. Am J Physiol Regul Integr Comp Physiol. 2002;282:R890.

    Article  CAS  Google Scholar 

  91. Changani KK, Nicholson A, White A, Latcham JK, Reid DG, Clapham JC. A longitudinal magnetic resonance imaging (MRI) study of differences in abdominal fat distribution between normal mice, and lean overexpressers of mitochondrial uncoupling protein-3 (UCP-3). Diabetes Obes Metab. 2003;5:99.

    Article  CAS  Google Scholar 

  92. Leonardsson G, Steel JH, Christian M, Pocock V, Milligan S, Bell J, So P-W, Medina-Gomez G, Vidal-Puig A, White R, Parker MG. Nuclear receptor corepressor RIP140 regulates fat accumulation. PNAS. 2004;101:8437.

    Article  CAS  Google Scholar 

  93. Borga M, Thomas EL, Romu T, Rosander J, Fitzpatrick J, Dahlqvist Leinhard O, Bell JD. Validation of a fast method for quantification of intra-abdominal and subcutaneous adipose tissue for large-scale human studies. NMR Biomed. 2015;28:1747.

    Article  CAS  Google Scholar 

  94. Leporq B, Lambert SA, Ronot M, et al. Hepatic fat fraction and visceral adipose tissue fatty acid composition in mice: Quantification with 7.0T MRI. Magn Reson Med. 2016;76:510.

    Article  CAS  Google Scholar 

  95. Reeder SB, Sirlin C. Quantification of liver fat with magnetic resonance imaging. Magn Reson Imaging Clin N Am. 2010;18:337.

    Article  Google Scholar 

  96. Beckmann N, Tigani B, Mazzoni L, Fozard JR. MRI of lung parenchyma in rats and mice using a gradient-echo sequence. NMR Biomed. 2001;14:297.

    Article  CAS  Google Scholar 

  97. 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;24:550.

    Article  CAS  Google Scholar 

  98. Garbow JR, Zhang Z, You M. Detection of primary lung tumors in rodents by magnetic resonance imaging. Cancer Res. 2004;64:2740.

    Article  CAS  Google Scholar 

  99. Dugas JP, Garbow JR, Kobayshi DK, Conradi MS. Hyperpolarized (3)He MRI of mouse lung. Magn Reson Med. 2004;52:1310.

    Article  CAS  Google Scholar 

  100. Guenther D, Hanisch G, Kauczor HU. Functional MR imaging of pulmonary ventilation using hyperpolarized noble gases. Acta Radiol. 2000;41:519.

    Article  CAS  Google Scholar 

  101. Peces-Barba G, Ruiz-Cabello J, Cremillieux Y, Rodriguez I, Dupuich D, Callot V, Ortega M, Rubio Arbo ML, et al. Helium-3 MRI diffusion coefficient: correlation to morphometry in a model of mild emphysema. Eur Respir J. 2003;22:14.

    Article  CAS  Google Scholar 

  102. Thomas SR, Clark Jr LC, Ackerman KL, Pratt RG, Hoffman RE, Busse L, Kinsey RA, Samaratunga RC. MR imaging of the lung using liquid perfluorocarbons. J Comput Assist Tomogr. 1986;10:1.

    Article  CAS  Google Scholar 

  103. Thomas SR, Millard RW, Pratt RG, Shiferaw Y, Samaratunga RC. Quantitative pO2 imaging in vivo with perfluorocarbon F-19 NMR: tracking oxygen from the airway through the blood to organ tissues. Artif Cells Blood Substit Immobil Biotechnol. 1994;22:1029.

    Article  CAS  Google Scholar 

  104. Thomas SR, Gradon L, Pratsinis SE, Pratt RG, Fotou GP, McGoron AJ, Podgorski AL, Millard RW. Perfluorocarbon compound aerosols for delivery to the lung as potential 19F magnetic resonance reporters of regional pulmonary pO2. Invest Radiol. 1997;32:29.

    Article  CAS  Google Scholar 

  105. Takahashi M, et al. MR microscopy of the lung in small rodents. Eur J Radiol. 2007;64:367.

    Article  Google Scholar 

  106. Bianchi A, et al. Three-dimensional accurate detection of lung emphysema in rats using ultra-short and zero echo time MRI. NMR Biomed. 2015;28:1471.

    Article  Google Scholar 

  107. Kveder M, et al. Water proton NMR relaxation mechanisms in lung tissue. Magn Reson Med. 1988;7:432.

    Article  CAS  Google Scholar 

  108. Siri F, Jelicks L, Leinwand L, Gardin J. Gated magnetic resonance imaging of normal and hypertrophied murine hearts. Am. J. Physiol. 1997;272:H2394.

    CAS  Google Scholar 

  109. Slawson S, Roman B, Williams D, Koretsky A. Cardiac MRI of the normal and hypertrophied mouse heart. Magn Reson Med. 1998;39:980.

    Article  CAS  Google Scholar 

  110. Ruff J, Wiesmann F, Hiller K, Voll S, Von Kienlin M, Bauer W, Neubauer S, Haase A. Magnetic resonance microimaging for noninvasive quantification of myocardial function and mass in the mouse. Magn Reson Med. 1998;40:43.

    Article  CAS  Google Scholar 

  111. Franco F, Thomas GD, Giroir B, Bryant D, Bullock MC, Chwialkowski MC, Victor RG, Peshock RM. Magnetic resonance imaging and invasive evaluation of development of heart failure in transgenic mice with myocardial expression of tumor necrosis factor-alpha. Circulation. 1999;99:448.

    Article  CAS  Google Scholar 

  112. Wiesmann F, Ruff J, Hiller K, Rommel E, Haase A, Neubauer S. Developmental changes of cardiac function and mass assessed with MRI in neonatal, juvenile, and adult mice. Am J Physiol Heart Circ Physiol. 2000;278:H652.

    Article  CAS  Google Scholar 

  113. Ruff J, Wiesmann F, Lanz T, Haase A. Magnetic resonance imaging of coronary arteries and heart valves in a living mouse: techniques and preliminary results. J Magn Reson. 2000;146:290.

    Article  CAS  Google Scholar 

  114. Schneider JE, Bamforth SD, Farthing CR, Clarke K, Neubauer S, Bhattacharya S. Rapid identification and 3D reconstruction of complex cardiac malformations in transgenic mouse embryos using fast gradient echo sequence magnetic resonance imaging. J Mol Cell Cardiol. 2003;35:217.

    Article  CAS  Google Scholar 

  115. Wessig C, Koltzenburg M, Reiners K, Solymosi L, Bendszus M. Muscle magnetic resonance imaging of denervation and reinnervation: correlation with electrophysiology and histology. Exp Neurol. 2004;185:254.

    Article  Google Scholar 

  116. Streif JU, Hiller KH, Waller C, Nahrendorf M, Wiesmann F, Bauer WR, Rommel E, Haase A. In vivo assessment of absolute perfusion in the murine skeletal muscle with spin labeling MRI. Magnetic resonance imaging. J Magn Reson Imaging. 2003;17:147.

    Article  Google Scholar 

  117. Damon BM, Ding Z, Anderson AW, Freyer AS, Gore JC. Validation of diffusion tensor MRI-based muscle fiber tracking. Magn Reson Med. 2002;48:97.

    Article  Google Scholar 

  118. Ruiz-Cabello J, Regadera J, Santisteban C, Grana M, Perez de Alejo R, Echave I, Aviles P, Rodriguez I, Santos I, Gargallo D, Cortijo M. Monitoring acute inflammatory processes in mouse muscle by MR imaging and spectroscopy: a comparison with pathological results. NMR Biomed. 2002;15:204.

    Article  Google Scholar 

  119. Sciorati C, Esposito A, Campana L, et al. 7-Tesla magnetic resonance imaging precisely and noninvasively reflects inflammation and remodeling of the skeletal muscle in a mouse model of antisynthetase syndrome. Biomed Res Int. 2014. https://doi.org/10.1155/2014/879703.

    Article  Google Scholar 

  120. Feng S, Chen D, Kushmerick M, Lee D. Multiparameter MRI analysis of the time course of induced muscle damage and regeneration. J Magn Reson Imaging. 2014;40:779.

    Article  Google Scholar 

  121. Bryant ND, Li K, Does MD, et al. Multi-parametric MRI characterization of inflammation in murine skeletal muscle. NMR Biomed. 2014;27:716.

    Article  Google Scholar 

  122. Kosaka M, Owatari N, Seo Y, Kawakubo H, Harada S, Katsumata T, Ida H, Lehmann V. In vivo NMR micro-imaging of kidney and liver of mouse at 9.4 T. Jpn J Physiol. 2000;50:463.

    Article  CAS  Google Scholar 

  123. Garbow JR, Kataoka M, Flye MW. MRI measurement of liver regeneration in mice following partial hepatectomy. Magn Reson Med. 2004;52:177.

    Article  CAS  Google Scholar 

  124. Banerjee R, Pavlides M, Tunnicliffe EM, Piechnik SK, Sarania N, Philips R, Collier JD. Multiparametric magnetic resonance for the non-invasive diagnosis of liver disease. J Hepatol. 2014;60:69.

    Article  Google Scholar 

  125. Chow AM, Gao DS, Fan SJ, et al. Measurement of liver T1 and T2 relaxation times in an experimental mouse model of liver fibrosis. J Magn Reson Imaging. 2012;36:152.

    Article  Google Scholar 

  126. Fabry ME, Kennan RP, Pàszty C, Costantini F, Rubin EM, Gore JC. Magnetic resonance evidence of hypoxia in a homozygous alpha-knockout of a transgenic mouse model for sickle cell disease. J Clin Invest. 1996;98:2450.

    Article  CAS  Google Scholar 

  127. Zhang JL, Rusinek H, et al. Functional MRI of the kidneys. J Magn Reson Imaging. 2013;37:282.

    Article  Google Scholar 

  128. Hadjidemetriou S, Reichardt W, Hennig J, et al. Volumetric analysis of MRI data monitoring the treatment of polycystic kidney disease in a mouse model. MAGMA. 2011;24:109.

    Article  Google Scholar 

  129. Economopoulos V, Noad JC, Krishnamoorthy S, Rutt BK, Foster PJ. Comparing the MRI appearance of the lymph nodes and spleen in wild-type and immuno-deficient mouse strains. PLoS One. 2011;6:e27508. https://doi.org/10.1371/journal.pone.0027508.

    Article  CAS  Google Scholar 

  130. Solomon A, Weiss DT, Schell M, Hrncic R, Murphy CL, Wall J, McGavin MD, Pan HJ, Kabalka GW, Paulus MJ. Transgenic mouse model of AA amyloidosis. Am J Pathol. 1999;154:1267.

    Article  CAS  Google Scholar 

  131. Tkatchenko TV, Shen Y, Tkatchenko AV. Analysis of postnatal eye development in the mouse with high-resolution small animal magnetic resonance imaging. Invest Opthalmol Vis Sci. 2010;51:21.

    Article  Google Scholar 

  132. Moshkelgosha S, So P-W, Deasy N, Daiz-Cano S, Banga JP. Cutting edge: retrobulbar inflammation, adipogenesis, and acute orbital congestion in a preclinical female mouse model of Graves’ orbitopathy induced by thyrotropin receptor plasmid-in vivo electroporation. Endocrinology. 2013;154:3008.

    Article  CAS  Google Scholar 

  133. Chan KC, Cheung MM, Wu EX. In vivo multiparametric magnetic resonance imaging and spectroscopy of rodent visual system. J Integr Neurosci. 2010;9:477.

    Article  Google Scholar 

  134. de Graff RA. In vivo NMR spectroscopy, principles and techniques. Chichester: Wiley; 1998.

    Google Scholar 

  135. Mystkowski P, Shankland E, Schreyer SA, LeBoeuf RC, Schwartz RS, Cummings DE, Kushmerick M, Schwartz MW. Validation of whole-body magnetic resonance spectroscopy as a tool to assess murine body composition. Int J Obes Relat Metab Disord. 2000;24:719.

    Article  CAS  Google Scholar 

  136. Pierson Jr RN, Wang J, Thornton JC. Measurement of body composition: applications in hormone research. Horm Res. 1997;48(suppl 1):56.

    Article  CAS  Google Scholar 

  137. So P-W, Furmanski A, Herlihy H, Bell JD. Modulation of Adipose Tissue Content and Composition by Omega-3-Fatty Acids in a Murine Model of Obesity. Proc Intl Soc Magn Med. 2004;12:949.

    Google Scholar 

  138. So P-W, Muckett P, Herlihy AH, Bell JD. Control of Adiposity by Environment Enrichment. Proc. Intl. Soc. Magn. Med. 2004;12:948.

    Google Scholar 

  139. Jones ME, Thorburn AW, Britt K, Hewitt KN, Wreford NG, Proietto J, Oz OK, Leury BJ, Robertson KM, Yao S, Simpson ER. Aromatase-deficient (ArKO) mice have a phenotype of increased adiposity. PNAS. 2000;97:12735.

    Article  CAS  Google Scholar 

  140. Wang Z, Deurenberg P, Wang W, Pietrobelli A, Baumgartner RN, Heymsfield SB. Hydration of fat-free body mass: review and critique of a classic body-composition constant. Am J Clin Nutr. 1999;69:833.

    Article  CAS  Google Scholar 

  141. Garbow JR, Lin X, Sakata N, Chen Z, Koh D, Schonfeld G. In vivo MRS measurement of liver lipid levels in mice. J Lipid Res. 2004;45:1364.

    Article  CAS  Google Scholar 

  142. Hockings PD, Changani KK, Saeed N, Reid DG, Birmingham J, O’Brien P, Osborne J, Toseland CN, Buckingham RE. Rapid reversal of hepatic steatosis, and reduction of muscle triglyceride, by rosiglitazone: MRI/S studies in Zucker fatty rats. Diabetes Obes Metab. 2003;5:234.

    Article  CAS  Google Scholar 

  143. In’t Zandt HJ, de Groof AJ, Renema WK, Oerlemans FT, Klomp DW, Wieringa B, Heerschap A. Presence of (phospho)creatine in developing and adult skeletal muscle of mice without mitochondrial and cytosolic muscle creatine kinase isoforms. J Physiol. 2003;548(Pt 3):847.

    Article  Google Scholar 

  144. Machann J, Haring H, Schick F, Stumvoll M. Intramyocellular lipids and insulin resistance. Diabetes Obes Metab. 2004;6:239.

    Article  CAS  Google Scholar 

  145. Brateman L. Chemical shift imaging: a review. Am J Roentgenol. 1986;146:971.

    Article  CAS  Google Scholar 

  146. Wunderlich C, Flogel U, Godecke A, Heger J, Schrader J. Acute inhibition of myoglobin impairs contractility and energy state of iNOS-overexpressing hearts. Circ Res. 2003;92:1352.

    Article  CAS  Google Scholar 

  147. Saupe KW, Spindler M, Tian R, Ingwall JS. Impaired cardiac energetics in mice lacking muscle-specific isoenzymes of creatine kinase. Circ Res. 1998;82:898.

    Article  CAS  Google Scholar 

  148. Hoehn M, Nicolay K, Franke C, van der Sanden B. Application of magnetic resonance to animal models of cerebral ischemia. J Magn Reson Imaging. 2001;14:491.

    Article  CAS  Google Scholar 

  149. Choi IY, Lee SP, Guilfoyle DN, Helpern JA. In vivo NMR studies of neurodegenerative diseases in transgenic and rodent models. Neurochem Res. 2003;28:987.

    Article  CAS  Google Scholar 

  150. Baslow MH, Suckow RF, Gaynor K, Bhakoo KK, Marks N, Saito M, Duff K, Matsuoka Y, Berg MJ. Brain damage results in down-regulation of N-acetylaspartate as a neuronal osmolyte. Neruomol Med. 2003;3:95.

    Article  CAS  Google Scholar 

  151. Jenkins BG, Klivenyi P, Kustermann E, Andreassen OA, Ferrante RJ, Rosen BR, Beal MF. Nonlinear decrease over time in N-acetyl aspartate levels in the absence of neuronal loss and increases in glutamine and glucose in transgenic Huntington’s disease mice. J Neurochem. 2000;74:2108.

    Article  CAS  Google Scholar 

  152. Van Dellan A, Welch J, Dixon RM, Cordery P, York D, Styles P, Blakemore C, Hannan AJ. N-Acetylaspartate and DARPP-32 levels decrease in the corpus striatum of Huntington’s disease mice. Neuroreport. 2000;11:3751.

    Article  Google Scholar 

  153. Matalon R, Rady PL, Platt KA, Skinner HB, Quast MJ, Campbell GA, Matalon K, Ceci JD, Tyring SK, Nehls M, Surendran S, Wei J, Ezell EL, Szucs S. Knock-out mouse for Canavan disease: a model for gene transfer to the central nervous system. J Gene Med. 2000;2:165.

    Article  CAS  Google Scholar 

  154. Tracey I, Dunn JF, Parkes HG, Radda GK. An in vivo and in vitro H-magnetic resonance spectroscopy study of mdx mouse brain: abnormal development or neural necrosis?. J Neurol Sci. 1996;141:13.

    Article  CAS  Google Scholar 

  155. Huang W, Galdzicki Z, van Gelderen P, Balbo A, Chikhale E, Schapiro MB, Rapoport SI. Brain myo-inositol level is elevated in Ts65Dn mouse and reduced after lithium treatment. Neuroreport. 2000;11:445.

    Article  CAS  Google Scholar 

  156. In’t Zandt HJ, Renema WK, Streijer F, Jost C, Klomp DW, Oerlemans F, Van der Zee CE, Wieringa B, Heerschap A. Cerebral creatine kinase deficiency influences metabolite levels and morphology in the mouse brain: a quantitative in vivo 1H and 31P magnetic resonance study. J Neurochem. 2004;90:1321.

    Article  CAS  Google Scholar 

  157. Schmidt A, Marescau B, Boehm EA, Renema KJ, Peco R, Das A, Steinfeld R, Chan S, Wallis J, Davidoff M, Ullrich K, Waldschütz R, Heerschap A, De Deyn PP, Neubauer S, Isbrandt D. Severely altered guanidino compound levels, disturbed body weight homeostasis and impaired fertility in a mouse model of guanidinoacetate N-methyltransferase (GAMT) deficiency. Hum Mol Genet. 2004;13:905.

    Article  CAS  Google Scholar 

  158. Dedeoglu A, Choi J-K, Cormier K, Kowall NW, Jenkins BG. Magnetic resonance spectroscopic analysis of Alzheimer’s disease mouse brain that express mutant human APP shows altered neurochemical profile. Brain Res. 2004;1012:60.

    Article  CAS  Google Scholar 

  159. Hesselbarth D, Franke C, Hata R, Brinker G, Hoehn-Berlage M. High resolution MRI and MRS: a feasibility study for the investigation of focal cerebral ischemia in mice. NMR Biomed. 1998;11:423.

    Article  CAS  Google Scholar 

  160. Schwarcz A, Natt O, Watanabe T, Boretius S, Frahm J, Michaelis T. Localized proton MRS of cerebral metabolite profiles in different mouse strains. Magn Reson Med. 2003;49:822.

    Article  CAS  Google Scholar 

  161. Rubenstein JL, Merzenich MM. Model of autism: increased ratio of excitation/inhibition in key neural systems. Genes Brain Behav. 2003;2:255.

    Article  CAS  Google Scholar 

  162. Coghlan S, Horder J, Inkster B, et al. GABA system dysfunction in autism and related disorders: from synapse to symptoms. Neurosci Biobehav Rev. 2012;36:2044.

    Article  CAS  Google Scholar 

  163. Brix MK, Ersland L, Hugdahl K, et al. Brain MR spectroscopy in autism spectrum disorder-the GABA excitatory/inhibitory imbalance theory revisited. Front Hum Neurosci. 2015;9:365.

    Article  CAS  Google Scholar 

  164. Kehrer C, Maziashvili N, Dugladze T, Gloveli T. Altered Excitatory-Inhibitory Balance in the NMDA-Hypofunction Model of Schizophrenia. Front Mol Neurosci. 2008;1:6.

    Article  Google Scholar 

  165. Moghaddam B, Javitt D. From revolution to evolution: the glutamate hypothesis of schizophrenia and its implication for treatment. Neuropsychopharmacology. 2012;37:4.

    Article  CAS  Google Scholar 

  166. Maltezos S, et al. Glutamate/glutamine and neuronal integrity in adults with ADHD: a proton MRS study. Transl Psychiatry. 2014;4:e373.

    Article  CAS  Google Scholar 

  167. Purkayastha P, Malapati A, Yogeeswari P, Sriram DA. A Review on GABA/Glutamate Pathway for Therapeutic Intervention of ASD and ADHD. Curr Med Chem. 2015;22:1850. https://doi.org/10.2174/0929867322666150209152712.

    Article  CAS  Google Scholar 

  168. Grados MA, Specht MW, Sung HM, Fortune D. Glutamate drugs and pharmacogenetics of OCD: a pathway-based exploratory approach. Expert Opin Drug Discovery. 2013;8:1515. https://doi.org/10.1517/17460441.2013.845553.

    Article  CAS  Google Scholar 

  169. Naaijen J, Lythgoe DJ, Amiri H, Buitelaar JK, Glennon JC. Fronto-striatal glutamatergic compounds in compulsive and impulsive syndromes: a review of magnetic resonance spectroscopy studies. Neurosci Biobehav Rev. 2015;52:74.

    Article  CAS  Google Scholar 

  170. Sanacora G, Treccani G, Popoli M. Towards a glutamate hypothesis of depression: an emerging frontier of neuropsychopharmacology for mood disorders. Neuropharmacology. 2012;62:63.

    Article  CAS  Google Scholar 

  171. Mathews DC, Henter ID, Zarate CA. Targeting the glutamatergic system to treat major depressive disorder: rationale and progress to date. Drugs. 2012;72:1313.

    Article  CAS  Google Scholar 

  172. Lener MS, Niciu MJ, Ballard ED, et al. Glutamate and Gamma-Aminobutyric Acid Systems in the Pathophysiology of Major Depression and Antidepressant Response to Ketamine. Biol Psychiatry. 2016. https://doi.org/10.1016/j.biopsych.2016.05.005.

  173. Chen G, Henter ID, Manji HK. Presynaptic glutamatergic dysfunction in bipolar disorder. Biol Psychiatry. 2010;67:1007.

    Article  Google Scholar 

  174. Maletic V, Raison C. Integrated neurobiology of bipolar disorder. Front Psych. 2014;5:98.

    Google Scholar 

  175. Javitt DC. Glutamate as a therapeutic target in psychiatric disorders. Mol Psychiatry. 2004;9:984.

    Article  CAS  Google Scholar 

  176. Mullins PG, McGonigle DJ, O’Gorman RL, et al. Current practice in the use of MEGA-PRESS spectroscopy for the detection of GABA. Neuroimage. 2012. https://doi.org/10.1016/j.neuroimage.2012.12.004.

    Article  Google Scholar 

  177. Saywell V, et al. Brain magnetic resonance study of Mecp2 deletion effects on anatomy and metabolism. Biochem Biophys Res Commun. 2006;340:776.

    Article  CAS  Google Scholar 

  178. Horder J, Lavender T, Mendez MA, et al. Reduced subcortical glutamate/glutamine in adults with autism spectrum disorders: a [1H]MRS study. Transl Psychiatry. 2013;3:e279.

    Article  CAS  Google Scholar 

  179. Das Neves Duarte JM, Kulak A, Gholam-Razaee MM, et al. N-acetylcysteine normalizes neurochemical changes in the glutathione-deficient schizophrenia mouse model during development. Biol. Psychiatry. 2012;71:1006.

    Article  CAS  Google Scholar 

  180. Waschkies CF, Bruns A, Muller S, et al. Neuropharmacological and neurobiological relevance of in vivo 1H-MRS of GABA and glutamate for preclinical drug discovery in mental disorders. Neuropsychopharmacology. 2014;39:2331.

    Article  CAS  Google Scholar 

  181. Hardan AY, Fung LK, Libove R, et al. A randomized controlled pilot trial of oral N-acetylcysteine in children with autism. Biol Psychiatry. 2012;71:956.

    Article  CAS  Google Scholar 

  182. Durieux AMS, Fernandes C, Murphy D, et al. Targeting Glia with N-Acetylcysteine Modulates Brain Glutamate and Behaviors Relevant to Neurodevelopmental Disorders in C57BL/6J Mice. Front Behav Neurosci. 2015;9. https://doi.org/10.3389/fnbeh.2015.00343.

  183. Meyer U, Feldon J, Schedlowski M, Yee BK. Towards an immuno-precipitated neurodevelopmental animal model of schizophrenia. Neurosci Biobehav Rev. 2005;29:913.

    Article  CAS  Google Scholar 

  184. Li Q, Leung YO, Zhou I, Ho LC, Kong W, et al. Dietary supplementation with n-3 fatty acids from weaning limits brain biochemistry and behavioural changes elicited by prenatal exposure to maternal inflammation in the mouse model. Transl Psychiatry. 2015;5:e641.

    Article  CAS  Google Scholar 

  185. Vernon AC, So P-W, Lythgoe DJ, Chege W, et al. Longitudinal in vivo maturational changes of metabolites in the prefrontal cortex of rats exposed to polyinosinic-polycytidylic acid in utero. Eur Neuropsychopharmacol. 2015;25:2210.

    Article  CAS  Google Scholar 

  186. Provencher SW. Automatic quantitation of localized in vivo 1H spectra with LCModel. NMR Biomed. 2001;14(4):260.

    Article  CAS  Google Scholar 

  187. Reynolds G, Wilson M, Peet A, Arvanitis TN. An algorithm for the automated quantification of metabolites in in vitro NMR signals. Magn Reson Med. 2006;56(6):1211.

    Article  CAS  Google Scholar 

  188. Tkáč I, Henry P-G, Andersen P, Kenne CD, Low WC, Gruetter R. Highly resolved in vivo 1H NMR spectroscopy of the mouse brain at 9.4 T. Magn Reson Med. 2004;52:478.

    Article  CAS  Google Scholar 

  189. Zwingmann C, Liebfritz D. Regulation of glial metabolism studied by 13C-NMR. NMR Biomed. 2003;16:370.

    Article  CAS  Google Scholar 

  190. Sibson NR, Mason GF, Shen J, Cline GW, Herskovits AZ, Wall JE, Behar KL, Rothman DL, Shulman RG. In vivo (13)C NMR measurement of neurotransmitter glutamate cycling, anaplerosis and TCA cycle flux in rat brain during. J Neurochem. 2001;76:975.

    Article  CAS  Google Scholar 

  191. Gruetter R, Seaquist ER, Ugurbil K. A mathematical model of compartmentalized neurotransmitter metabolism in the human brain. Am J Physiol Endocrinol Metab. 2001;281:E100.

    Article  CAS  Google Scholar 

  192. Shen J, Petersen KF, Behar KL, Brown P, Nixon TW, Mason GF, Petroff OA, Shulman GI, Shulman RG, Rothman DL. Determination of the rate of the glutamate/glutamine cycle in the human brain by in vivo 13C NMR. PNAS. 1999;96:8235.

    Article  CAS  Google Scholar 

  193. Gruetter R, Adriany G, Choi IY, Henry PG, Lei H, Öz G. Localized in vivo 13C NMR spectroscopy of the brain. NMR Biomed. 2003;16:313.

    Article  CAS  Google Scholar 

  194. Shonat RD, Koretsky AP. Expression of myoglobin in the transgenic mouse brain. Adv Exp Med Biol. 2003;530:331.

    Article  CAS  Google Scholar 

  195. Giannesini B, Izquierdo M, Confort-Gouny S, Cozzone PJ, Bendahan D. Time-dependent and indirect effect of inorganic phosphate on force production in rat gastrocnemius exercising muscle determined by 31P-MRS. FEBS Lett. 2001;507:25.

    Article  CAS  Google Scholar 

  196. Giannesini B, Izquierdo M, Le Fur Y, Cozzone PJ, Bendahan D. In vivo reduction in ATP cost of contraction is not related to fatigue level in stimulated rat gastrocnemius muscle. J Physiol. 2001; 536(Pt 3):905.

    Article  CAS  Google Scholar 

  197. Westerblad H, Allen DG, Bruton JD, Andrade FH, Lannergren J. Mechanisms underlying the reduction of isometric force in skeletal muscle fatigue. Acta Physiol Scand. 1998;162:253.

    Article  CAS  Google Scholar 

  198. Debold EP, Dave H, Fitts RH. Fiber type and temperature dependence of inorganic phosphate: implications for fatigue. Am J Physiol Cell Physiol. 2004;287:C673.

    Article  CAS  Google Scholar 

  199. Lara TM, Wong MS, Rounds J, Robinson MK, Wilmore DW, Jacobs DO. Skeletal muscle phosphocreatine depletion depresses myocellular energy status during sepsis. Arch Surg. 1998;133:1316.

    Article  CAS  Google Scholar 

  200. Bloch G, Chase JR, Avison MJ, Shulman RG. In vivo 31P NMR measurement of glucose-6-phosphate in the rat muscle after exercise. Magn Reson Med. 1993;30:347.

    Article  CAS  Google Scholar 

  201. Chase JR, Rothman DL, Shulman RG. Flux control in the rat gastrocnemius glycogen synthesis pathway by in vivo 13C/31P NMR spectroscopy. Am J Physiol Endocrinol Metab. 2001;280:E598.

    Article  CAS  Google Scholar 

  202. Rothman DL, Shulman RG, Shulman GI. 31P nuclear magnetic resonance measurements of muscle glucose-6-phosphate. Evidence for reduced insulin-dependent muscle glucose transport or phosphorylation activity in non-insulin-dependent diabetes mellitus. J Clin Invest. 1992;89:1069.

    Article  CAS  Google Scholar 

  203. Kan HE, Renema WK, Isbrandt D, Heerschap A. Phosphorylated guanidinoacetate partly compensates for the lack of phosphocreatine in skeletal muscle of mice lacking guanidinoacetate methyltransferase. J Physiol. 2004;560:219.

    Article  CAS  Google Scholar 

  204. Cohen SM. Application of nuclear magnetic resonance to the study of liver physiology and disease. Hepatology. 1983;3:738.

    Article  CAS  Google Scholar 

  205. Choi IY, Wu C, Okar DA, Lange AJ, Gruetter R. Elucidation of the role of fructose 2,6-bisphosphate in the regulation of glucose fluxes in mice using in vivo (13)C NMR measurements of hepatic carbohydrate metabolism. Eur J Biochem. 2002;269:4418.

    Article  CAS  Google Scholar 

  206. Dimicoli J-L, Patry J, Blouquit Y, Nedelec J-F, Adam R. Multinuclear NMR investigations on the metabolic recovery of the isolated perfused mouse liver after cold preservation. Biochimie. 2003;85:891.

    Article  CAS  Google Scholar 

  207. Brosnan MJ, Chen L, Van Dyke TA, Koretsky AP. Free ADP levels in transgenic mouse liver expressing creatine kinase. Effects of enzyme activity, phosphagen type, and substrate concentration. J Biol Chem. 1990;265:20849.

    CAS  Google Scholar 

  208. Brosnan MJ, Chen LH, Wheeler CE, Van Dyke TA, Koretsky AP. Phosphocreatine protects ATP from a fructose load in transgenic mouse liver expressing creatine kinase. Am J Phys. 1991;260:C1191.

    Article  CAS  Google Scholar 

  209. Miller K, Halow J, Koretsky AP. Phosphocreatine protects transgenic mouse liver expressing creatine kinase from hypoxia and ischemia. Am J Phys. 1993;265:C1544.

    Article  CAS  Google Scholar 

  210. Askenasy N, Koretsky AP. Transgenic livers expressing mitochondrial and cytosolic CK: mitochondrial CK modulates free ADP levels. Am J Phys. 2002;282:C338.

    Article  CAS  Google Scholar 

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Acknowledgments

The authors would like acknowledge the BBSRC, MRC, and EPSRC for financial support.

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Authors and Affiliations

  1. Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, Maurice Wohl Clinical Neuroscience Institute, 5, Cutcombe Road, London, UK

    Po-Wah So & Azhaar Ashraf

  2. Department of Forensic and neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK

    Alice Marie Sybille Durieux

  3. Institute of Translational Medicine and Therapeutics, Imperial College London, Hammersmith Hospital, Du Cane Road, London, UK

    William Richard Crum

  4. Research Centre for Optimal Health, Department of Life Sciences, Faculty of Science and Technology, University of Westminster, London, UK

    Jimmy David Bell

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  1. Po-Wah So
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  2. Azhaar Ashraf
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Correspondence to Po-Wah So .

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  1. Royal Society of Chemistry, London, United Kingdom

    Graham A. Webb

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So, PW., Ashraf, A., Durieux, A.M., Crum, W.R., Bell, J.D. (2018). The Application of In Vivo MRI and MRS in Phenomic Studies of Murine Models of Disease. In: Webb, G. (eds) Modern Magnetic Resonance. Springer, Cham. https://doi.org/10.1007/978-3-319-28388-3_95

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