Hybrid Imaging: From Anatomy to Function

  • David García Juan
  • Sara Trombella
  • Osman RatibEmail author


Medical imaging has progressively grown into a variety of different imaging modalities and technologies that allow for the visualization and analysis of the human body for diagnosis, and for monitoring of a variety of diseases and for the assessment of treatments or therapeutic interventions efficacy. Technical innovations have led to the development of multimodal, or hybrid, imaging devices that combine different imaging methods in a simultaneous or sequential way. The underlying idea of hybrid imaging devices is to combine functional and metabolic information (positron emission tomography, PET, or single-photon positron emission tomography, SPECT) together with anatomical and morphological characterization (x-ray computed tomography, CT, or magnetic resonance imaging, MRI). The first hybrid device applied for clinical use was the combination of SPECT with CT. Nowadays PET/CT plays the role of an important diagnostic tool in clinical routine. Concurrently, the concepts for combining PET with MRI were explored, but only recently a first generation of hybrid PET/MRI scanners has been developed and tested in clinical applications. The first clinical data obtained from the emerging PET/MRI imaging technique are showing their potential and defining their role in clinical routine, and it may supersede PET/CT in many applications and practical aspects in the future.


Molecular imaging Hybrid imaging PET PET/MRI PET/CT SPECT/CT. 


  1. 1.
    Kuhl, D. E., Hale, J., & Eaton, W. (1966). Transmission scanning: A useful adjunct to conventional emission scanning for accurately keying isotope depositation to radiographic anatomy. Radiology, 87, 278–284.Google Scholar
  2. 2.
    Bailey, D. L., Hutton, B. F., & Walker, P. J. (1987). Improved SPECT using emission and transmission tomography. Journal of Nuclear Medicine, 28, 844–851.Google Scholar
  3. 3.
    Tsui, B. M., Gullberg, G. T., Edgerton, E. R., et al. (1989). Correction of nonuniform attenuation in cardiac SPECT imaging. Journal of Nuclear Medicine, 30, 497–507.Google Scholar
  4. 4.
    Hudson, H., & Larkin, R. S. (1994). Accelerated image reconstruction using ordered subsets of projection data. IEEE Transactions on Medical Imaging, 13, 100–107.CrossRefGoogle Scholar
  5. 5.
    Hasegawa, B. H., Reilly, S. M., Gingold, E. L., et al. (1989). Design considerations for a simultaneous emission-transmission CT scanner. Radiology, 173, 414.Google Scholar
  6. 6.
    Hasegawa, B. H., Gingold, E. L., Reilly, S. M., et al. (1990). Description of a simultaneous emission-transmission CT system. Proceedings of SPIE, 1231, 50–60.CrossRefGoogle Scholar
  7. 7.
    Hasegawa, B. H., Stebler, B., Rutt, B. K., et al. (1991). A prototype high-purity germanium detector system with fast photon-counting circuitry for medical imaging. Medical Physics, 18, 900–909.CrossRefGoogle Scholar
  8. 8.
    Pietrzyk, U., Herholz, K., & Heiss, W. D. (1990). Three-dimensional alignment of functional and morphological tomograms. Journal of Computer Assisted Tomography, 14, 51–59.CrossRefGoogle Scholar
  9. 9.
    Woods, R. P., Cherry, S. R., & Mazziotta, J. C. (1992). Rapid automated algorithm for aligning and reslicing PET images. Journal of Computer Assisted Tomography, 16, 620–633.CrossRefGoogle Scholar
  10. 10.
    Beyer, T., Townsend, D. W., Brun, T., et al. (2000). A combined PET/CT scanner for clinical oncology. Journal of Nuclear Medicine, 41, 1369–1379.Google Scholar
  11. 11.
    Townsend, D. W. (2001). A combined PET/CT scanner: The choices. Journal of Nuclear Medicine, 42, 533–534.Google Scholar
  12. 12.
    Kinahan, P. E., Townsend, D. W., Beyer, T., et al. (1998). Attenuation correction for a combined 3D PET/CT scanner. Medical Physics, 25, 2045–2053.CrossRefGoogle Scholar
  13. 13.
    Patton, J. A., Townsend, D. W., & Hutton, B. F. (2009). Hybrid imaging technology: From dreams and vision to clinical devices. Seminars in Nuclear Medicine, 39, 247–263.CrossRefGoogle Scholar
  14. 14.
    Hicks, R. J., & Lau, E. W. F. (1998). Attenuation correction for a combined 3D PET/CT scanner. Medical Physics, 25, 2045–2053.Google Scholar
  15. 15.
    von Schulthess, G. K., Kuhn, F. P., Kaufmann, P., et al. (2013). Clinical positron emission tomography/magnetic resonance imaging applications. Seminars in Nuclear Medicine, 43, 3–10.CrossRefGoogle Scholar
  16. 16.
    Pichler, B. J., Kolb, A., Nagele, T., et al. (2009). PET/MRI: Paving the way for the next generation of clinical multymodality imaging applications. Journal of Nuclear Medicine, 51, 333–336.CrossRefGoogle Scholar
  17. 17.
    Shao, I., Cherry, S. R., Farahani, K., et al. (1997). Simultaneous PET and MR imaging. Physics in Medicine and Biology, 42, 1965–1970.CrossRefGoogle Scholar
  18. 18.
    Schlemmer, H. P., Pichler, B. J., Shmand, M., et al. (2008). Simultaneous MR/PET imaging of the human brain: Feasibility study. Radiology, 248, 1028–1035.CrossRefGoogle Scholar
  19. 19.
    Heesakkers, R. A., Hoevels, A. M., Jager, G. J., van den Bosch, H. C., Witjes, J. A., Raat, H. P., et al. (2008). MRI with a lymph-node-specific contrast agent as an alternative to CT scan limph-node dissection in patients with prostate cancer: A prospective multicohort study. The Lancet Oncology, 9, 850–856.CrossRefGoogle Scholar
  20. 20.
    Goerres, G. W., Burger, C., Schwitter, M. R., et al. (2003). PET/CT of the abdomen: Optimizing the patient breathing pattern. European Radiology, 13, 734–739.CrossRefGoogle Scholar
  21. 21.
    Goerres, G. W., Kamel, E., Heidelberg, T. N., et al. (2002). PET/CT image co-registration in the thorax: Influence of respiration. European Journal of Nuclear Medicine and Molecular Imaging, 29, 351–360.CrossRefGoogle Scholar
  22. 22.
    Brechtel, K., Klein, M., Vogel, M., et al. (2006). Optimized contrast-enhanced CT protocols for diagnostic whole-body 18F-FDG PET/CT: Technical aspects of single- phase versus multiphase CT imaging. Journal of Nuclear Medicine, 47, 470–476.Google Scholar
  23. 23.
    Beyer, T., Antoch, G., Blodgett, T., et al. (2003). Dual-modality PET/CT imaging: The effect of respiratory motion on combined image quality in clinical oncology. European Journal of Nuclear Medicine and Molecular Imaging, 30, 588–596.CrossRefGoogle Scholar
  24. 24.
    Hong, S.J., Song, I.C., Ito, N., et al. (2008) An investigation into the use of Geiger/Mode Solid/State Photomultipliers for simultaneous PET and MRI acquisition. IEEE Transactions on Nuclear Sciences, 55, 882–888.Google Scholar
  25. 25.
    Judenhofer, M. S., Wehrl, H. F., Newport, D. F., et al. (2008). Simultaneous PET-MRI: A new approach for functional and morphological imaging. Nature Medicine, 14, 459–465.CrossRefGoogle Scholar
  26. 26.
    Yoon, H. S., Ko, G. B., Kwon, S. I., et al. (2012). Initial results of simultaneous PET/MRI experiments with an MRI-compatible silicon photomultiplier PET scanner. Journal of Nuclear Medicine, 53, 608–614.CrossRefGoogle Scholar
  27. 27.
    Yamamoto, S., Watabe, T., Watabe, H., et al. (2012). Simultaneous imaging using Si- PM-based PET and MRI for development of an integrated PET/MRI system. Physics in Medicine and Biology, 57, N1–N13.Google Scholar
  28. 28.
    Tatsumi, M., Yamamoto, S., Imaizumi, M., et al. (2012). Simultaneous PET/MR body imaging in rats: Initial experiences with an integrated PET/MRI scanner. Annals of Nuclear Medicine, 26, 444–449.Google Scholar
  29. 29.
    Judenhofer, M. S., & Cherry, S. R. (2013). Applications for preclinical PET/MRI. Seminars in Nuclear Medicine, 43, 19–29.CrossRefGoogle Scholar
  30. 30.
    Gallagher, F. A. (2010). An introduction to functional and molecular imaging with MRI. Clinical Radiology, 65, 557–566.CrossRefGoogle Scholar
  31. 31.
    Meguro, K., LeMestric, C., Landeau, B., et al. (2001). Relations between hypometabolism in the posterior association neocortex and hippocampal atrophy in Alzheimers disease: A PET/MRI correlative study. Journal of Neurology, Neurosurgery and Psychiatry, 71, 315–321.Google Scholar
  32. 32.
    Borgwardt, L., Hojgaard, L., Carstensen, H., et al. (2005). Increased fluorine-18 2-fluoro- 2-deoxy-D-glucose (FDG) uptake in childhood CNS tumors is correlated with malignancy grade: A study with FDG positron emission tomography/magnetic resonance imaging coregistration and image fusion. Journal of Clinical Oncology, 23, 3030–3037.CrossRefGoogle Scholar
  33. 33.
    Pauleit, D., Floeth, F., Hamacher, K., et al. (2005). O-(2-[18F]fluoroethyl)-L-tyrosine PET combined with MRI improves the diagnostic assessment of cerebral gliomas. Brain, 128, 678–687.CrossRefGoogle Scholar
  34. 34.
    Floeth, F. W., Pauleit, D., Wittsack, H. J., et al. (2005). Multimodal metabolic imaging of cerebral gliomas: Positron emission tomography with [18F]fluoroethyl-L-tyrosine and magnetic resonance spectroscopy. Physics in Medicine and Biology, 102, 318–327.Google Scholar
  35. 35.
    Seemann, M. D., Meisetschlaeger, G., Gaa, J., et al. (2006). Assessment of the extent of metastases of gastrointestinal carcinoid tumors using whole-body PET, CT, MRI, PET/CT and PET/MRI. European Journal of Medical Research, 11, 58–65.Google Scholar
  36. 36.
    Stadlbauer, A., Prante, O., Nimsky, C., et al. (2008). Metabolic imaging of cerebral gliomas: Spatial correlation of changes in O-(218F-fluoroethyl)-L-tyrosine PET and proton magnetic resonance spectroscopic imaging. Journal of Nuclear Medicine, 49, 721–729.CrossRefGoogle Scholar
  37. 37.
    Phelps, M. E. (2004). PET—Molecular imaging and its biological applications. NewYork: Springer.Google Scholar
  38. 38.
    Ollinger, J. M. (1996). Model-based scatter correction for fully 3D PET. Physics in Medicine and Biology, 41, 153–176.CrossRefGoogle Scholar
  39. 39.
    Watson, C. C., Casey, M. E., Michel, C., et al. (2004). Advances in scatter correction for 3D PET/CT. IEEE Nuclear Science Symposium Conference Record, 5, 3008–3012.Google Scholar
  40. 40.
    Polycarpou, I., Thielemans, K., Manjeshwar, R., et al. (2011). Comparative evaluation of scatter correction in 3D PET using different scatter-level approximations. Annals of Nuclear Medicine, 25, 643–649.CrossRefGoogle Scholar
  41. 41.
    Le Goff-Rougetet, R., Frouin, V., Mangin, J. F., et al. (1994). Segmented MR images for brain attenuation correction in PET. Proceedings of SPIE, 2167, 725–736.CrossRefGoogle Scholar
  42. 42.
    Keereman, V., Fierens, Y., Broux, T., et al. (2010). MRI-based attenuation correction for PET/MRI using ultrashort eco time sequences. Journal of Nuclear Medicine, 51, 812–818.CrossRefGoogle Scholar
  43. 43.
    Malone, I. B., Ansorge, R. E., Williams, G. B., et al. (2011). Attenuation correction methods suitable for brain imaging with a PET/MRI scanner: A comparison of tissue atlas and template attenuation map approaches. Journal of Nuclear Medicine, 52, 1142–1149.CrossRefGoogle Scholar
  44. 44.
    Wagenknecht, G., Rota Kops, E., Mantlik, F., et al. (2011). Attenuation correction in MR-BrainPET with segmented T1-weighte MR images of the patient’s head—A comparative study with CT. Proceedings of IEEE Medical Imaging Conference (pp. 2261–2266).Google Scholar
  45. 45.
    Berker, Y., Franke, J., Salomon, A., et al. (2012). MRI-based attenuation correction for hybrid PET/MRI systems: A 4-class tissue segmentation technique using a combined Ultrashort-Echo-Time/Dixon MRI sequence. Journal of Nuclear Medicine, 53, 796–804.CrossRefGoogle Scholar
  46. 46.
    Martinex-Moeller, A., Souvatzoglou, M., & Delso, G. (2009). Tissue classification as a potential approach for attenuation correction in whole-body PET/MRI: Evaluation with PET/CT data. Journal of Nuclear Medicine, 50, 520–526.CrossRefGoogle Scholar
  47. 47.
    Hofmann, M., Bezrukov, I., Mantlik, F., et al. (2011). MRI-based attenuation correction for the whole-body PET/MRI: Quantitative evaluation of segmentation- and atlas- based methods. Journal of Nuclear Medicine, 52, 1392–1399.Google Scholar
  48. 48.
    Steinberg, J., Jia, G., Sammet, S., et al. (2010). Three-region MRI-based whole-body attenuation correction for automated PET reconstruction. Nuclear Medicine and Biology, 37, 227–235.CrossRefGoogle Scholar
  49. 49.
    Schulz, V., Torres-Espallardo, I., Renisch, S., et al. (2011). Automatic, three-segment, MR-based attenuation correction for whole-body PET/MR data. European Journal of Nuclear Medicine and Molecular Imaging, 38, 138–152.CrossRefGoogle Scholar
  50. 50.
    Huang, S. C., Carson, R. E., Phelps, M. E., et al. (1981). A boundary method for attenuation correction in positron emission tomography. Journal of Nuclear Medicine, 22, 627–637.Google Scholar
  51. 51.
    Martinez-Moeller, A., & Nekolla, S. (2012). Attenuation correction for PET/MRI: Problems, novel approaches and practical solutions. Z Medical Physics, 22, 299–310.CrossRefGoogle Scholar
  52. 52.
    Bezrukov, I., Mantlik, F., Schmidt, H., et al. (2013). MR-based PET attenuation correction for PET/MRI imaging. Seminars in Nuclear Medicine, 43, 45–59.CrossRefGoogle Scholar
  53. 53.
    Robinson, P. J., & Kreel, L. (1979). Pulmonary tissue attenuation with computed tomography: Comparison of inspiration and expiration scans. Journal of Computer Assisted Tomography, 3, 740–748.Google Scholar
  54. 54.
    Zaidi, H., & Del Guerra, A. (2011). An outlook on future design of hybrid PET/MRI systems. Medical Physics, 38, 5667–5689.CrossRefGoogle Scholar
  55. 55.
    Zaidi, H., Ojha, N., Morich, M., et al. (2011). Design and performance evaluation of awhole-body ingenuity PET/MRI system. Physics in Medicine and Biology, 56, 3091–3106.CrossRefGoogle Scholar
  56. 56.
    Schreibmann, E., Nye, J. A., Schuster, D. M., et al. (2010). MR-based attenuation correction for hybrid PET-MR brain imaging systems using deformable image registration. Medical Physics, 37, 2101–2109.CrossRefGoogle Scholar
  57. 57.
    Beyer, T., Weigert, M., Quick, H. H., et al. (2008). MR-based attenuation correction fortorso-PET/MR imaging: Pitfalls in mapping MR to CT data. European Journal of Nuclear Medicine, 35, 1142–1146.CrossRefGoogle Scholar
  58. 58.
    Wagenknecht, G., Kaiser, H. J., Mottaghy, F. M., et al. (2012). MRI for attenuation correction in PET: Methods and challenges. MAGMA, 26, 99–113.Google Scholar
  59. 59.
    Kessler, R. M., Ellis, J. R., & Eden, M. (1984). Analysis of emission tomographic scan data: Limitations imposed by resolution and background. Journal of Computer Assisted Tomography, 8, 514–522.CrossRefGoogle Scholar
  60. 60.
    Matsuda, H., Ohnishi, T., Asada, T., et al. (2003). Correction for partial-volume effectson brain perfusion SPECT in healthy men. Journal of Nuclear Medicine, 44, 1243–1252.Google Scholar
  61. 61.
    Shidahara, M., Tsoumpas, C., Hammers, A., et al. (2009). Functional and structural synergy for resolution recovery and partial volume correction in brain PET. Neuroimage, 44, 340–348.CrossRefGoogle Scholar
  62. 62.
    Baete, K., Nuyts, J., & Laere, K. V. (2004). Evaluation of anatomy based reconstruction for partial volume correction in brain FDG-PET. Neuroimage, 23, 305–317.CrossRefGoogle Scholar
  63. 63.
    Sokoloff, L., Reivich, M., Kennedy, C., et al. (1977). The [14c]deoxyglucose method for the measurement of local cerebral glucose utilization: Theory, procedure, and normal values in the conscious and anesthetized albino rat. Journal of Neurochemistry, 28, 897–916.CrossRefGoogle Scholar
  64. 64.
    Reivich, M., Kuhl, D., Wolf, A., et al. (1979). The [18F]fluorodeoxyglucose method for the measurement of local cerebral glucose utilization in man. Circulation Research, 44, 127–137.CrossRefGoogle Scholar
  65. 65.
    Patlak, C. S., Blasberg, R. G., & Fenstermacher, J. D. (1983). Graphical evaluation of blood- to-brain transfer constant from multiple-time uptake data. Journal of Cerebral Blood Flow and Metabolism, 3, 1–7.CrossRefGoogle Scholar
  66. 66.
    Patlak, C. S., & Blasberg, R. G. (1985). Graphical evaluation of blood-to-brain transfer constant from multiple-time uptake data. Generalizations. Journal of Cerebral Blood Flow and Metabolism, 5, 584–590.CrossRefGoogle Scholar
  67. 67.
    Zaidi, H., Mawlawi, O., & Orton, C. G. (2007). Simultaneous PET/MR will replace PET/CT as the molecular multimodality imaging platform of choice? Medical Physics, 34, 1525–1528.CrossRefGoogle Scholar
  68. 68.
    Blankespor, S. C., Xu, X., Kaiki, K., et al. (1996). Attenuation correction of SPECT using X-ray CT on an emission-transmission CT system; myocardial perfusion assessment. IEEE Transactions on Nuclear Science, 43, 2263–2274.CrossRefGoogle Scholar
  69. 69.
    Lewellen, T. K. (1998). Time-of-flight PET. Seminars in Nuclear Medicine, 28, 268–275.CrossRefGoogle Scholar
  70. 70.
    Moses, W. W. (2007). Recent advances and future advances in time-of-flight PET. Methods in Physics Research Section A, 580, 919–924.CrossRefGoogle Scholar
  71. 71.
    Delso, G., Furst, S., Jakoby, B., et al. (2011). Performance measurements of the siemens mMR integrated whole-body PET/MR scanner. Journal of Nuclear Medicine, 52, 1914–1922.CrossRefGoogle Scholar
  72. 72.
    Kalemis, A., Delattre, B., Heinzer, S. (2012) Sequential whole-body PET/MR scanner: concept, clinical use, and optimisation after two years in the clinic. The manufacturer’s perspective. Magnetic Resonance Materials in Physics, Biology and Medicine, 26, 5–23.Google Scholar
  73. 73.
    Gilman, S. (1998). Imaging the brain. First of two parts. New England Journal of Medicine, 338, 812–820.CrossRefGoogle Scholar
  74. 74.
    Bisdas, S., Nagele, T., Schlemmer, H. P., et al. (2010). Switching on the lights for real-time multimodality tumor neuroimaging: The integrated positron-emission tomography/MR imaging system. American Journal of Neuroradiology, 31, 610–614.CrossRefGoogle Scholar
  75. 75.
    Boss, A., Stegger, L., Bisdas, S., et al. (2011). Feasibility of simultaneous PET/MR imaging in the head and upper neck area. European Radiology, 21, 1439–1446.CrossRefGoogle Scholar
  76. 76.
    Weissleder, R., & Pittet, M. J. (2008). Imaging in the era of molecular oncology. Nature, 452, 580–589.CrossRefGoogle Scholar
  77. 77.
    Czermin, J., Allen-Auerbach, M., & Schelbert, H. R. (2007). Improvements in cancer staging with PET/CT: Literature-based evidence as of september 2006. Journal of Nuclear Medicine, 48, 78–88.Google Scholar
  78. 78.
    Carli, M. F. D., Dorbala, S., Meserve, J., et al. (2007). Clinical myocardial perfusion PET/CT. Journal of Nuclear Medicine, 48, 783–793.CrossRefGoogle Scholar
  79. 79.
    Kaufmann, P. A., & Carli, M. F. D. (2009). Hybrid SPECT/CT and PET/CT imaging: The next step in noninvasive cardiac imaging. Seminars in Nuclear Medicine, 39, 341–347.CrossRefGoogle Scholar
  80. 80.
    Costa, D. C., Pilowsky, L. S., Ell, P. J. (1999). Nuclear medicine in neurology and psychiatry. Lancet, 354, 1107–1111.Google Scholar
  81. 81.
    Tatsch, K., & Ell, P. J. (2006). PET and SPECT in common neuropsychiatric disease. Clinical Medicine, 6, 259–262.CrossRefGoogle Scholar
  82. 82.
    Edge, S.B., Byrd, D.R., Compton, C.C. (2009). AJCC Cancer staging handbook: From the AJCC cancer staging manual (7th ed.) New York: Springer.Google Scholar
  83. 83.
    Antoch, G., & Bockisch, A. (2009). Combine PET/MRI: A new dimension in whole-body oncology imaging? European Journal of Nuclear Medicine and Molecular Imaging, 36, 113–1120.CrossRefGoogle Scholar
  84. 84.
    Stoeckli, S. J., Steinert, H., Pfaltz, M., et al. (2002). Is there a role for positron emission tomography with 18F-fluorodeoxyglucose in the initial staging of nodal negative oral and oropharyngeal squamous cell carcinoma? Head Neck, 24, 345–349.CrossRefGoogle Scholar
  85. 85.
    Punwani, S., Taylor, S. A., Saad, Z. Z., et al. (2013). Diffusion-weighted MRI of lymphoma: prognostic utility and implications for PET/MRI? European Journal of Nuclear Medicine and Molecular Imaging, 40, 373–385.Google Scholar
  86. 86.
    Poptani, H., Gupta, R. K., Roy, R., et al. (1995). Characterization of intracranial mass lesions with in vivo proton MR spectroscopy. American Journal of Neuroradiology, 16, 1593–1603.Google Scholar
  87. 87.
    Gore, J. C., Manning, H. C., Quarles, C. C., et al. (2011). Magnetic resonance in the era of molecular imaging of cancer. Magnetic Resonance Imaging, 29, 587–600.CrossRefGoogle Scholar
  88. 88.
    Buchbender, C., Heusner, T. A., Lauenstein, T. C., et al. (2012). Oncologic PET/MRI, part 1: Tumors of the brain, head and neck, chest, abdomen and pelvis. Journal of Nuclear Medicine, 53, 928–937.CrossRefGoogle Scholar
  89. 89.
    Buchbender, C., Heusner, T. A., Lauenstein, T. C., et al. (2012). Oncologic PET/MRI, part 2: Bone tumors, soft-tissue tumors, melanoma and lymphoma. Journal of Nuclear Medicine, 53, 1244–1252.CrossRefGoogle Scholar
  90. 90.
    Assiri, Y., Schmid, D., Pietsch, C., et al. (2012). Contrast enhanced PET/MRI in abdominal oncological lesions. initial results. Annual Congress of the European Association of Nuclear Medicine. (Milan, Italy).Google Scholar
  91. 91.
    Crook, D. W., Mader, C., Kuhn, F. P., et al. (2012). Diagnostic performance of PET/MRI versus PET/CT in the abdomen. Vienna: European Congress of Radiology.Google Scholar
  92. 92.
    Hustinx, R., & Lucignani, G. (2010). PET/CT in head and neck cancer: An update. European Journal of Nuclear Medicine and Molecular Imaging, 37, 645–651.CrossRefGoogle Scholar
  93. 93.
    Schwenzer, N. F., Schraml, C., Mueller, M., et al. (2012). Pulmonary lesion assessment: comparison of whole-body hybrid MR/PET and PET/CT imaging. Pilot study. Radiology, 264, 551–558.CrossRefGoogle Scholar
  94. 94.
    Nekolla, S., & Martinex-Möller, A. (2009). A, S.: PET and MRI in cardiac imaging: From validation studies to integrated applications. European Journal of Nuclear Medicine and Molecular Imaging, 36, 121–130.CrossRefGoogle Scholar
  95. 95.
    Buescher, K., Martin, S. J., Kuhlmann, M. T., et al. (2010). Isochronous assessment of cardiac metabolism and function in mice using hybrid PET/MRI. Journal of Nuclear Medicine, 51, 1277–1284.CrossRefGoogle Scholar
  96. 96.
    Vargas, M.I., Becker, M., Garibotto, V., et al. (2012). Approaches for the optimization of MR protocols in clinical hybrid PET/MRI studies. MAGMA, 26, 57–69.Google Scholar
  97. 97.
    Prvulovic, D., Bokde, A. L., Faltraco, F., et al. (2011). Functional magnetic resonance imaging as a dynamic candidate biomarker for Alzheimers disease. Progress in Neurobiology, 95, 557–569.Google Scholar
  98. 98.
    Barnes, J., Ourselin, S., & Fox, N. C. (2009). Clinical application of measurement of hippocampal atrophy in degenerative dementias. Hippocampus, 19, 510–516.CrossRefGoogle Scholar
  99. 99.
    Wattjes, M. P. (2011). Structural MRI. International Psychogeriatrics, 23, S13–S24.CrossRefGoogle Scholar
  100. 100.
    Utriainen, M., Komu, M., Vuorinen, V., et al. (2003). Evaluation of brain tumor metabolism with [11C] choline PET and 1H-MRS. Journal of Neuro Oncology, 62, 329–338.CrossRefGoogle Scholar
  101. 101.
    Floeth, F. W., Pauleit, D., Wittsack, H. J., et al. (2005). Multimodal metabolic imaging of cerebral gliomas: positron emission tomography with [18F]fluoroethyl-L-tyrosine and magnetic resonance spectroscopy. Journal of Neurosurgery, 102, 318–327.CrossRefGoogle Scholar
  102. 102.
    Chua, T. C., Wen, W., Slaving, M. J., et al. (2008). Diffusion tensor imaging in mild cognitive impairment and Alzheimers disease: A review. Current Opinion in Neurology, 21, 83–92.CrossRefGoogle Scholar
  103. 103.
    Dickerson, B. C., & Sperling, R. A. (2004). Functional abnormalities of the medial temporal lobe memory system in mild cognitive impairment and Alzheimers disease: insights from functional MRI studies. Neuropsychologia, 55, 1624–1635.Google Scholar
  104. 104.
    Klunk, W. E., Engler, H., Nordberg, A., et al. (2004). Imaging brain amyloid in Alzheimersdisease with Pittsburgh compound-B. Annals of Neurology, 55, 306–319.CrossRefGoogle Scholar
  105. 105.
    Rowe, C. C., & Villemagne, V. L. (2011). Brain amyloid imaging. Journal of Nuclear Medicine, 52, 1733–1740.Google Scholar
  106. 106.
    Heiss, W. D. (2000). Ischemic penumbra: Evidence from functional imaging in men. Journal of Cerebral Blood Flow and Metabolism, 20, 1276–1293.CrossRefGoogle Scholar
  107. 107.
    Loevblad, K. O., Laubach, H. J., Baird, A. E., et al. (1998). Clinical experience with diffusion-weighted MR in patients with acute stroke. American Journal of Neuroradiology, 19, 1061–1066.Google Scholar
  108. 108.
    Sorensen, A. G., Copen, W. A., Ostergaard, L., et al. (1999). Hyperacute stroke: Simultaneous measurement of relative cerebral blood volume, relative cerebral blood flow, and mean tissue transit time. Radiology, 210, 519–527.CrossRefGoogle Scholar
  109. 109.
    LoPinto-Khoury, C., Sperling, M. R., Skidmore, C., et al. (2012). Surgical outcome in PET-positive, MRI-negative patients with temporal lobe epilepsy. Epilepsia, 53, 342–348.CrossRefGoogle Scholar
  110. 110.
    Mercuri, E., Pichiecchio, A., Allsop, J., Messina, S., Pane, M., & Muntoni, F. (2007). Muscle MRI in inherited neuromuscular disorders: Past, present and future. Journal of Magnetic Resonance Imaging, 25, 433–440.CrossRefGoogle Scholar
  111. 111.
    Segal, R. L. (2007). Use of imaging to assess normal and adaptive muscle function. Physical Therapy, 87, 704–718.CrossRefGoogle Scholar
  112. 112.
    Prompers, J. J., Jeneson, J. A. L., Drost, M. R., Oomens, C. C., Strijkers, G. J., & Nicolay, K. (2006). Dynamic MRS and MRI of skeletal muscle function and biomechanics. NMR in Biomedicine, 19, 927–953.CrossRefGoogle Scholar
  113. 113.
    Tai, S., Liu, R., Kuo, Y., Hsu, C., & Chen, C. (2010). Glucose uptake patterns in exercised skeletal muscles of elite male long-distance and short-distance runners. Chinese Journal of Physics, 53(2), 91–98.CrossRefGoogle Scholar
  114. 114.
    Heinonen, I., Nesterov, S. V., Kemppainen, J., Fujimoto, T., Knuuti, J., & Kalliokoski, K. K. (2012). Increasing exercise intensity reduces heterogeneity of glucose uptake in human skeletal muscles. PLoS ONE, 7(12), e52191.CrossRefGoogle Scholar

Copyright information

© Springer-Verlag London 2014

Authors and Affiliations

  • David García Juan
    • 1
  • Sara Trombella
    • 1
  • Osman Ratib
    • 1
    Email author
  1. 1.Hôpitaux Universitaires de Genève, Service de Médecine NucléaireGenèveSwitzerland

Personalised recommendations