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Current status and future role of brain PET/MRI in clinical and research settings

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Abstract

Hybrid PET/MRI systematically offers a complementary combination of two modalities that has often proven itself superior to the single modality approach in the diagnostic work-up of many neurological and psychiatric diseases. Emerging PET tracers, technical advances in multiparametric MRI and obvious workflow advantages may lead to a significant improvement in the diagnosis of dementia disorders, neurooncological diseases, epilepsy and neurovascular diseases using PET/MRI. Moreover, simultaneous PET/MRI is well suited to complex studies of brain function in which fast fluctuations of brain signals (e.g. related to task processing or in response to pharmacological interventions) need to be monitored on multiple levels. Initial simultaneous studies have already demonstrated that these complementary measures of brain function can provide new insights into the functional and structural organization of the brain.

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References

  1. Dukart J, Mueller K, Horstmann A, Barthel H, Möller HE, Villringer A, et al. Combined evaluation of FDG-PET and MRI improves detection and differentiation of dementia. PLoS One. 2011;6:e18111.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  2. Jack Jr CR, Lowe VJ, Senjem ML, Weigand SD, Kemp BJ, Shiung MM, et al. 11C PiB and structural MRI provide complementary information in imaging of Alzheimer’s disease and amnestic mild cognitive impairment. Brain J Neurol. 2008;131:665–80.

    Article  Google Scholar 

  3. Pauleit D, Floeth F, Hamacher K, Riemenschneider MJ, Reifenberger G, Müller H-W, et al. O-(2-[18F]fluoroethyl)-L-tyrosine PET combined with MRI improves the diagnostic assessment of cerebral gliomas. Brain J Neurol. 2005;128:678–87.

    Article  Google Scholar 

  4. Pirotte BJ, Levivier M, Goldman S, Massager N, Wikler D, Dewitte O, et al. Positron emission tomography-guided volumetric resection of supratentorial high-grade gliomas: a survival analysis in 66 consecutive patients. Neurosurgery. 2009;64:471–81; discussion 481.

    Article  PubMed  Google Scholar 

  5. Dunet V, Maeder P, Nicod-Lalonde M, Lhermitte B, Pollo C, Bloch J, et al. Combination of MRI and dynamic FET PET for initial glioma grading. Nuklearmedizin. 53:155–61.

  6. Catana C, Drzezga A, Heiss W-D, Rosen BR. PET/MRI for neurologic applications. J Nucl Med. 2012;53:1916–25.

    Article  PubMed  Google Scholar 

  7. Heiss W-D. Radionuclide imaging in ischemic stroke. J Nucl Med. 2014;55:1831–41.

    Article  CAS  PubMed  Google Scholar 

  8. Zhang K, Herzog H, Mauler J, Filss C, Okell TW, Kops ER, et al. Comparison of cerebral blood flow acquired by simultaneous [15O]water positron emission tomography and arterial spin labeling magnetic resonance imaging. J Cereb Blood Flow Metab. 2014;34:1373–80.

    Article  PubMed Central  PubMed  Google Scholar 

  9. Rischpler C, Nekolla SG, Dregely I, Schwaiger M. Hybrid PET/MR imaging of the heart: potential, initial experiences, and future prospects. J Nucl Med. 2013;54:402–15.

    Article  CAS  PubMed  Google Scholar 

  10. Bolus NE, George R, Washington J, Newcomer BR. PET/MRI: the blended-modality choice of the future? J Nucl Med Technol. 2009;37:63–71. quiz 72–73.

    Article  PubMed  Google Scholar 

  11. Beyer T, Antoch G, Müller S, Egelhof T, Freudenberg LS, Debatin J, et al. Acquisition protocol considerations for combined PET/CT imaging. J Nucl Med. 2004;45 Suppl 1:25S–35.

    PubMed  Google Scholar 

  12. Gilmore CD, Comeau CR, Alessi AM, Blaine M, El Fakhri GN, Hunt JK, et al. PET/MR imaging consensus paper: a joint paper by the Society of Nuclear Medicine and Molecular Imaging Technologist Section and the Section for Magnetic Resonance Technologists. J Nucl Med Technol. 2013;41:108–13.

    Article  PubMed  Google Scholar 

  13. Carney JP, Townsend DW, Rappoport V, Bendriem B. Method for transforming CT images for attenuation correction in PET/CT imaging. Med Phys. 2006;33:976–83.

    Article  PubMed  Google Scholar 

  14. Navalpakkam BK, Braun H, Kuwert T, Quick HH. Magnetic resonance-based attenuation correction for PET/MR hybrid imaging using continuous valued attenuation maps. Invest Radiol. 2013;48:323–32.

    Article  PubMed  Google Scholar 

  15. Berker Y, Franke J, Salomon A, Palmowski M, Donker HC, Temur Y, et al. MRI-based attenuation correction for hybrid PET/MRI systems: a 4-class tissue segmentation technique using a combined ultrashort-echo-time/Dixon MRI sequence. J Nucl Med. 2012;53:796–804.

    Article  PubMed  Google Scholar 

  16. Andersen FL, Ladefoged CN, Beyer T, Keller SH, Hansen AE, Højgaard L, et al. Combined PET/MR imaging in neurology: MR-based attenuation correction implies a strong spatial bias when ignoring bone. Neuroimage. 2014;84:206–16.

    Article  PubMed  Google Scholar 

  17. Keereman V, Fierens Y, Broux T, De Deene Y, Lonneux M, Vandenberghe S. MRI-based attenuation correction for PET/MRI using ultrashort echo time sequences. J Nucl Med. 2010;51:812–8.

    Article  PubMed  Google Scholar 

  18. Poynton CB, Chen KT, Chonde DB, Izquierdo-Garcia D, Gollub RL, Gerstner ER, et al. Probabilistic atlas-based segmentation of combined T1-weighted and DUTE MRI for calculation of head attenuation maps in integrated PET/MRI scanners. Am J Nucl Med Mol Imaging. 2014;4:160–71.

    PubMed Central  PubMed  Google Scholar 

  19. Rezaei A, Defrise M, Nuyts J. ML-reconstruction for TOF-PET with simultaneous estimation of the attenuation factors. IEEE Trans Med Imaging. 2014;33:1563–72.

    Article  PubMed  Google Scholar 

  20. Delso G, Fürst S, Jakoby B, Ladebeck R, Ganter C, Nekolla SG, et al. Performance measurements of the Siemens mMR integrated whole-body PET/MR scanner. J Nucl Med. 2011;52:1914–22.

    Article  PubMed  Google Scholar 

  21. Oakes TR, Johnstone T, Ores Walsh KS, Greischar LL, Alexander AL, Fox AS, et al. Comparison of fMRI motion correction software tools. Neuroimage. 2005;28:529–43.

    Article  CAS  PubMed  Google Scholar 

  22. Catana C, Benner T, van der Kouwe A, Byars L, Hamm M, Chonde DB, et al. MRI-assisted PET motion correction for neurologic studies in an integrated MR-PET scanner. J Nucl Med. 2011;52:154–61.

    Article  PubMed Central  PubMed  Google Scholar 

  23. Fung EK, Carson RE. Cerebral blood flow with [15O]water PET studies using an image-derived input function and MR-defined carotid centerlines. Phys Med Biol. 2013;58:1903–23.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  24. Su Y, Arbelaez AM, Benzinger TLS, Snyder AZ, Vlassenko AG, Mintun MA, et al. Noninvasive estimation of the arterial input function in positron emission tomography imaging of cerebral blood flow. J Cereb Blood Flow Metab. 2013;33:115–21.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  25. Olivot J-M, Mlynash M, Thijs VN, Kemp S, Lansberg MG, Wechsler L, et al. Optimal Tmax threshold for predicting penumbral tissue in acute stroke. Stroke J Cereb Circ. 2009;40:469–75.

    Article  Google Scholar 

  26. Sugawara Y, Zasadny KR, Neuhoff AW, Wahl RL. Reevaluation of the standardized uptake value for FDG: variations with body weight and methods for correction. Radiology. 1999;213:521–5.

    Article  CAS  PubMed  Google Scholar 

  27. Chan T. Computerized method for automatic evaluation of lean body mass from PET/CT: comparison with predictive equations. J Nucl Med. 2012;53:130–7.

    Article  PubMed  Google Scholar 

  28. Acosta-Cabronero J, Williams GB, Cardenas-Blanco A, Arnold RJ, Lupson V, Nestor PJ. In vivo quantitative susceptibility mapping (QSM) in Alzheimer’s disease. PLoS One. 2013;8:e81093.

    Article  PubMed Central  PubMed  Google Scholar 

  29. Rivlin M, Horev J, Tsarfaty I, Navon G. Molecular imaging of tumors and metastases using chemical exchange saturation transfer (CEST) MRI. Sci Rep. 2013;3:3045.

    Article  PubMed  Google Scholar 

  30. Sorbi S, Hort J, Erkinjuntti T, Fladby T, Gainotti G, Gurvit H, et al. EFNS-ENS Guidelines on the diagnosis and management of disorders associated with dementia. Eur J Neurol. 2012;19:1159–79.

    Article  CAS  PubMed  Google Scholar 

  31. Frisoni GB, Fox NC, Jack Jr CR, Scheltens P, Thompson PM. The clinical use of structural MRI in Alzheimer disease. Nat Rev Neurol. 2010;6:67–77.

    Article  PubMed Central  PubMed  Google Scholar 

  32. Frisoni GB, Bocchetta M, Chételat G, Rabinovici GD, de Leon MJ, Kaye J, et al. Imaging markers for Alzheimer disease: which vs how. Neurology. 2013;81:487–500.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  33. Jack CR, Knopman DS, Jagust WJ, Shaw LM, Aisen PS, Weiner MW, et al. Hypothetical model of dynamic biomarkers of the Alzheimer’s pathological cascade. Lancet Neurol. 2010;9:119–28.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  34. Mosconi L. Brain glucose metabolism in the early and specific diagnosis of Alzheimer’s disease. FDG-PET studies in MCI and AD. Eur J Nucl Med Mol Imaging. 2005;32:486–510.

    Article  CAS  PubMed  Google Scholar 

  35. Heiss WD, Kessler J, Szelies B, Grond M, Fink G, Herholz K. Positron emission tomography in the differential diagnosis of organic dementias. J Neural Transm Suppl. 1991;33:13–9.

    CAS  PubMed  Google Scholar 

  36. Mosconi L, Tsui WH, Herholz K, Pupi A, Drzezga A, Lucignani G, et al. Multicenter standardized 18F-FDG PET diagnosis of mild cognitive impairment, Alzheimer’s disease, and other dementias. J Nucl Med. 2008;49:390–8.

    Article  PubMed Central  PubMed  Google Scholar 

  37. Clark CM, Schneider JA, Bedell BJ, Beach TG, Bilker WB, Mintun MA, et al. Use of florbetapir-PET for imaging beta-amyloid pathology. JAMA. 2011;305:275–83.

    Article  CAS  PubMed  Google Scholar 

  38. Nordberg A, Carter SF, Rinne J, Drzezga A, Brooks DJ, Vandenberghe R, et al. A European multicentre PET study of fibrillar amyloid in Alzheimer’s disease. Eur J Nucl Med Mol Imaging. 2013;40:104–14.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  39. Barthel H, Gertz H-J, Dresel S, Peters O, Bartenstein P, Buerger K, et al. Cerebral amyloid-β PET with florbetaben (18F) in patients with Alzheimer’s disease and healthy controls: a multicentre phase 2 diagnostic study. Lancet Neurol. 2011;10:424–35.

    Article  CAS  PubMed  Google Scholar 

  40. Hsiao I-T, Huang C-C, Hsieh C-J, Hsu W-C, Wey S-P, Yen T-C, et al. Correlation of early-phase 18F-florbetapir (AV-45/Amyvid) PET images to FDG images: preliminary studies. Eur J Nucl Med Mol Imaging. 2012;39:613–20.

    Article  CAS  PubMed  Google Scholar 

  41. Jones DT, Machulda MM, Vemuri P, McDade EM, Zeng G, Senjem ML, et al. Age-related changes in the default mode network are more advanced in Alzheimer disease. Neurology. 2011;77:1524–31.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  42. Sheline YI, Raichle ME, Snyder AZ, Morris JC, Head D, Wang S, et al. Amyloid plaques disrupt resting state default mode network connectivity in cognitively normal elderly. Biol Psychiatry. 2010;67:584–7.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  43. Myers N, Pasquini L, Göttler J, Grimmer T, Koch K, Ortner M, et al. Within-patient correspondence of amyloid-β and intrinsic network connectivity in Alzheimer’s disease. Brain J Neurol. 2014;137:2052–64.

    Article  Google Scholar 

  44. Griffa A, Baumann PS, Thiran J-P, Hagmann P. Structural connectomics in brain diseases. Neuroimage. 2013;80:515–26.

    Article  PubMed  Google Scholar 

  45. Alsop DC, Dai W, Grossman M, Detre JA. Arterial spin labeling blood flow MRI: its role in the early characterization of Alzheimer’s disease. J Alzheimers Dis. 2010;20:871–80.

    PubMed Central  PubMed  Google Scholar 

  46. Kendziorra K, Wolf H, Meyer PM, Barthel H, Hesse S, Becker GA, et al. Decreased cerebral α4β2* nicotinic acetylcholine receptor availability in patients with mild cognitive impairment and Alzheimer’s disease assessed with positron emission tomography. Eur J Nucl Med Mol Imaging. 2011;38:515–25.

    Article  CAS  PubMed  Google Scholar 

  47. Meyer PM, Strecker K, Kendziorra K, Becker G, Hesse S, Woelpl D, et al. Reduced alpha4beta2*-nicotinic acetylcholine receptor binding and its relationship to mild cognitive and depressive symptoms in Parkinson disease. Arch Gen Psychiatry. 2009;66:866–77.

    Article  CAS  PubMed  Google Scholar 

  48. Jagust W. Time for tau. Brain. 2014;137:1570–1.

    Article  PubMed  Google Scholar 

  49. Bailey DL, Barthel H, Beuthin-Baumann B, Beyer T, Bisdas S, Boellaard R, et al. Combined PET/MR: Where are we now? Summary report of the second international workshop on PET/MR imaging April 8-12, 2013, Tubingen, Germany. Mol Imaging Biol. 2014;16:295–310

    PubMed  Google Scholar 

  50. Garibotto V, Heinzer S, Vulliemoz S, Guignard R, Wissmeyer M, Seeck M, et al. Clinical applications of hybrid PET/MRI in neuroimaging. Clin Nucl Med. 2013;38:e13–8.

    Article  PubMed  Google Scholar 

  51. Drzezga A, Barthel H, Minoshima S, Sabri O. Potential clinical applications of PET/MR imaging in neurodegenerative diseases. J Nucl Med. 2014;55 Suppl 2;47S–57S.

    Article  PubMed  Google Scholar 

  52. Schmidt H, Schwenzer NF, Bezrukov I, Mantlik F, Kolb A, Kupferschläger J, et al. On the quantification accuracy, homogeneity, and stability of simultaneous positron emission tomography/magnetic resonance imaging systems. Invest Radiol. 2014;49:373–81.

    Article  PubMed  Google Scholar 

  53. Hitz S, Habekost C, Fürst S, Delso G, Förster S, Ziegler S, et al. Systematic comparison of the performance of integrated whole-body PET/MR imaging to conventional PET/CT for 18F-FDG brain imaging in patients examined for suspected dementia. J Nucl Med. 2014;55:923–31.

    Article  CAS  PubMed  Google Scholar 

  54. Barker 2nd FG, Chang SM, Huhn SL, Davis RL, Gutin PH, McDermott MW, et al. Age and the risk of anaplasia in magnetic resonance-nonenhancing supratentorial cerebral tumors. Cancer. 1997;80:936–41.

    Article  PubMed  Google Scholar 

  55. Scott JN, Brasher PMA, Sevick RJ, Rewcastle NB, Forsyth PA. How often are nonenhancing supratentorial gliomas malignant? A population study. Neurology. 2002;59:947–9.

    Article  CAS  PubMed  Google Scholar 

  56. Kruser TJ, Mehta MP, Robins HI. Pseudoprogression after glioma therapy: a comprehensive review. Expert Rev Neurother. 2013;13:389–403.

    Article  CAS  PubMed  Google Scholar 

  57. Duffau H. A new philosophy in surgery for diffuse low-grade glioma (DLGG): oncological and functional outcomes. Neurochirurgie. 2013;59:2–8.

    Article  CAS  PubMed  Google Scholar 

  58. Galldiks N, Kracht LW, Dunkl V, Ullrich RT, Vollmar S, Jacobs AH, et al. Imaging of non- or very subtle contrast-enhancing malignant gliomas with [11C]-methionine positron emission tomography. Mol Imaging. 2011;10:453–9.

    CAS  PubMed  Google Scholar 

  59. Galldiks N, Ullrich R, Schroeter M, Fink GR, Jacobs AH, Kracht LW. Volumetry of [(11)C]-methionine PET uptake and MRI contrast enhancement in patients with recurrent glioblastoma multiforme. Eur J Nucl Med Mol Imaging. 2010;37:84–92.

    Article  PubMed Central  PubMed  Google Scholar 

  60. Bangiyev L, Rossi Espagnet MC, Young R, Shepherd T, Knopp E, Friedman K, et al. Adult brain tumor imaging: state of the art. Semin Roentgenol. 2014;49:39–52.

    Article  PubMed  Google Scholar 

  61. Law M, Yang S, Wang H, Babb JS, Johnson G, Cha S, et al. Glioma grading: sensitivity, specificity, and predictive values of perfusion MR imaging and proton MR spectroscopic imaging compared with conventional MR imaging. AJNR Am J Neuroradiol. 2003;24:1989–98.

    PubMed  Google Scholar 

  62. Law M, Yang S, Babb JS, Knopp EA, Golfinos JG, Zagzag D, et al. Comparison of cerebral blood volume and vascular permeability from dynamic susceptibility contrast-enhanced perfusion MR imaging with glioma grade. AJNR Am J Neuroradiol. 2004;25:746–55.

    PubMed  Google Scholar 

  63. La Fougère C, Suchorska B, Bartenstein P, Kreth F-W, Tonn J-C. Molecular imaging of gliomas with PET: opportunities and limitations. Neuro Oncol. 2011;13:806–19.

    Article  PubMed Central  PubMed  Google Scholar 

  64. Ceyssens S, Van Laere K, de Groot T, Goffin J, Bormans G, Mortelmans L. [11C]methionine PET, histopathology, and survival in primary brain tumors and recurrence. AJNR Am J Neuroradiol. 2006;27:1432–7.

    CAS  PubMed  Google Scholar 

  65. Ullrich RT, Kracht L, Brunn A, Herholz K, Frommolt P, Miletic H, et al. Methyl-L-11C-methionine PET as a diagnostic marker for malignant progression in patients with glioma. J Nucl Med. 2009;50:1962–8.

    Article  PubMed  Google Scholar 

  66. Singhal T, Narayanan TK, Jacobs MP, Bal C, Mantil JC. 11C-methionine PET for grading and prognostication in gliomas: a comparison study with 18F-FDG PET and contrast enhancement on MRI. J Nucl Med. 2012;53:1709–15.

    Article  PubMed  Google Scholar 

  67. Pöpperl G, Kreth FW, Mehrkens JH, Herms J, Seelos K, Koch W, et al. FET PET for the evaluation of untreated gliomas: correlation of FET uptake and uptake kinetics with tumour grading. Eur J Nucl Med Mol Imaging. 2007;34:1933–42.

    Article  PubMed  Google Scholar 

  68. Kunz M, Thon N, Eigenbrod S, Hartmann C, Egensperger R, Herms J, et al. Hot spots in dynamic (18)FET-PET delineate malignant tumor parts within suspected WHO grade II gliomas. Neuro Oncol. 2011;13:307–16.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  69. Pirotte B, Goldman S, Massager N, David P, Wikler D, Vandesteene A, et al. Comparison of 18F-FDG and 11C-methionine for PET-guided stereotactic brain biopsy of gliomas. J Nucl Med. 2004;45:1293–8.

  70. Purz S, Mauz-Körholz C, Körholz D, Hasenclever D, Krausse A, Sorge I, et al. [18F]Fluorodeoxyglucose positron emission tomography for detection of bone marrow involvement in children and adolescents with Hodgkin’s lymphoma. J Clin Oncol. 2011;29:3523–8.

    Article  PubMed  Google Scholar 

  71. Grosu AL, Weber WA, Franz M, Stärk S, Piert M, Thamm R, et al. Reirradiation of recurrent high-grade gliomas using amino acid PET (SPECT)/CT/MRI image fusion to determine gross tumor volume for stereotactic fractionated radiotherapy. Int J Radiat Oncol Biol Phys. 2005;63:511–9.

    Article  CAS  PubMed  Google Scholar 

  72. Pirotte B, Goldman S, Dewitte O, Massager N, Wikler D, Lefranc F, et al. Integrated positron emission tomography and magnetic resonance imaging-guided resection of brain tumors: a report of 103 consecutive procedures. J Neurosurg. 2006;104:238–53.

    Article  PubMed  Google Scholar 

  73. Boss A, Bisdas S, Kolb A, Hofmann M, Ernemann U, Claussen CD, et al. Hybrid PET/MRI of intracranial masses: initial experiences and comparison to PET/CT. J Nucl Med. 2010;51:1198–205.

    Article  PubMed  Google Scholar 

  74. Bisdas S, Ritz R, Bender B, Braun C, Pfannenberg C, Reimold M, et al. Metabolic mapping of gliomas using hybrid MR-PET imaging: feasibility of the method and spatial distribution of metabolic changes. Invest Radiol. 2013;48:295–301.

    Article  CAS  PubMed  Google Scholar 

  75. Preuss M, Werner P, Barthel H, Nestler U, Christiansen H, Hirsch FW, et al. Integrated PET/MRI for planning navigated biopsies in pediatric brain tumors. Childs Nerv Syst. 30:1399–403.

  76. Werner P, Fritzsch D, Holland H, Bauer M, Krupp W, Hoffmann K-T, et al. Definition of primary and secondary glioblastoma – letter. Clin Cancer Res. 2014;20:2011–2.

    Article  PubMed  Google Scholar 

  77. Sharma H. Multiparametric imaging and MR image texture analysis in brain tumors (PhD thesis). The University of Western Ontario; 2014.

  78. Artan Y, Yetik IS, Haider MA. Automated prostate cancer localization with multiparametric magnetic resonance imaging. In: El-Baz AS, Saba L, Suri JS, editors. Abdomen and thoracic imaging: an engineering and clinical perspective. New York: Springer; 2014. p. 559–86.

    Chapter  Google Scholar 

  79. Prior FW, Fouke SJ, Benzinger T, Boyd A, Chicoine M, Cholleti S, et al. Predicting a multi-parametric probability map of active tumor extent using random forests. Conf Proc IEEE Eng Med Biol Soc. 2013;2013:6478–81.

    PubMed Central  PubMed  Google Scholar 

  80. Hacke W, Kaste M, Bluhmki E, Brozman M, Dávalos A, Guidetti D, et al. Thrombolysis with alteplase 3 to 4.5 hours after acute ischemic stroke. N Engl J Med. 2008;359:1317–29.

    Article  CAS  PubMed  Google Scholar 

  81. Heiss WD, Grond M, Thiel A, von Stockhausen HM, Rudolf J, Ghaemi M, et al. Tissue at risk of infarction rescued by early reperfusion: a positron emission tomography study in systemic recombinant tissue plasminogen activator thrombolysis of acute stroke. J Cereb Blood Flow Metab. 1998;18:1298–307.

    Article  CAS  PubMed  Google Scholar 

  82. Thijs VN, Adami A, Neumann-Haefelin T, Moseley ME, Marks MP, Albers GW. Relationship between severity of MR perfusion deficit and DWI lesion evolution. Neurology. 2001;57:1205–11.

    Article  CAS  PubMed  Google Scholar 

  83. Merino JG, Warach S. Imaging of acute stroke. Nat Rev Neurol. 2010;6:560–71.

    Article  PubMed  Google Scholar 

  84. Albers GW, Thijs VN, Wechsler L, Kemp S, Schlaug G, Skalabrin E, et al. Magnetic resonance imaging profiles predict clinical response to early reperfusion: the diffusion and perfusion imaging evaluation for understanding stroke evolution (DEFUSE) study. Ann Neurol. 2006;60:508–17.

    Article  PubMed  Google Scholar 

  85. Hacke W, Furlan AJ, Al-Rawi Y, Davalos A, Fiebach JB, Gruber F, et al. Intravenous desmoteplase in patients with acute ischaemic stroke selected by MRI perfusion-diffusion weighted imaging or perfusion CT (DIAS-2): a prospective, randomised, double-blind, placebo-controlled study. Lancet Neurol. 2009;8:141–50.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  86. Davis SM, Donnan GA, Parsons MW, Levi C, Butcher KS, Peeters A, et al. Effects of alteplase beyond 3 h after stroke in the Echoplanar Imaging Thrombolytic Evaluation Trial (EPITHET): a placebo-controlled randomised trial. Lancet Neurol. 2008;7:299–309.

    Article  PubMed  Google Scholar 

  87. Bokkers RP, Bremmer JP, van Berckel BNM, Lammertsma AA, Hendrikse J, Pluim JPW, et al. Arterial spin labeling perfusion MRI at multiple delay times: a correlative study with H(2)(15)O positron emission tomography in patients with symptomatic carotid artery occlusion. J Cereb Blood Flow Metab. 2010;30:222–9.

    Article  PubMed Central  PubMed  Google Scholar 

  88. Nael K, Meshksar A, Liebeskind DS, Coull BM, Krupinski EA, Villablanca JP. Quantitative analysis of hypoperfusion in acute stroke: arterial spin labeling versus dynamic susceptibility contrast. Stroke J Cereb Circ. 2013;44:3090–6.

    Article  Google Scholar 

  89. Zaro-Weber O, Moeller-Hartmann W, Heiss W-D, Sobesky J. Maps of time to maximum and time to peak for mismatch definition in clinical stroke studies validated with positron emission tomography. Stroke J Cereb Circ. 2010;41:2817–21.

    Article  Google Scholar 

  90. O’Brien TJ, Hicks RJ, Ware R, Binns DS, Murphy M, Cook MJ. The utility of a 3-dimensional, large-field-of-view, sodium iodide crystal–based PET scanner in the presurgical evaluation of partial epilepsy. J Nucl Med. 2001;42:1158–65.

    PubMed  Google Scholar 

  91. Lee KK, Salamon N. [18F]fluorodeoxyglucose-positron-emission tomography and MR imaging coregistration for presurgical evaluation of medically refractory epilepsy. AJNR Am J Neuroradiol. 2009;30:1811–6.

    Article  CAS  PubMed  Google Scholar 

  92. LoPinto‐Khoury C, Sperling MR, Skidmore C, Nei M, Evans J, Sharan A, et al. Surgical outcome in PET‐positive, MRI‐negative patients with temporal lobe epilepsy. Epilepsia. 2012;53:342–8.

    Article  PubMed  Google Scholar 

  93. Chassoux F, Rodrigo S, Semah F, Beuvon F, Landre E, Devaux B, et al. FDG-PET improves surgical outcome in negative MRI Taylor-type focal cortical dysplasias. Neurology. 2010;75:2168–75.

    Article  CAS  PubMed  Google Scholar 

  94. Gok B, Jallo G, Hayeri R, Wahl R, Aygun N. The evaluation of FDG-PET imaging for epileptogenic focus localization in patients with MRI positive and MRI negative temporal lobe epilepsy. Neuroradiology. 2013;55:541–50.

    Article  PubMed  Google Scholar 

  95. Purz S, Sabri O, Viehweger A, Barthel H, Kluge R, Sorge I, et al. Potential pediatric applications of PET/MR. J Nucl Med. 2014;55 Suppl 2:32S–39S.

    Article  CAS  PubMed  Google Scholar 

  96. Sander CY, Hooker JM, Catana C, Normandin MD, Alpert NM, Knudsen GM, et al. Neurovascular coupling to D2/D3 dopamine receptor occupancy using simultaneous PET/functional MRI. Proc Natl Acad Sci U S A. 2013;110:11169–74.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  97. Wehrl HF, Martirosian P, Schick F, Reischl G, Pichler BJ. Assessment of rodent brain activity using combined [(15)O]H2O-PET and BOLD-fMRI. Neuroimage. 2014;89:271–9.

    Article  PubMed  Google Scholar 

  98. Wehrl HF, Hossain M, Lankes K, Liu C-C, Bezrukov I, Martirosian P, et al. Simultaneous PET-MRI reveals brain function in activated and resting state on metabolic, hemodynamic and multiple temporal scales. Nat Med. 2013;19:1184–9.

    Article  CAS  PubMed  Google Scholar 

  99. Riedl V, Bienkowska K, Strobel C, Tahmasian M, Grimmer T, Förster S, et al. Local activity determines functional connectivity in the resting human brain: a simultaneous FDG-PET/fMRI study. J Neurosci. 2014;34:6260–6.

    Article  CAS  PubMed  Google Scholar 

  100. Schultz CC, Fusar-Poli P, Wagner G, Koch K, Schachtzabel C, Gruber O, et al. Multimodal functional and structural imaging investigations in psychosis research. Eur Arch Psychiatry Clin Neurosci. 2012;262 Suppl 2:S97–106.

    Article  PubMed  Google Scholar 

  101. Uppal R, Catana C, Ay I, Benner T, Sorensen AG, Caravan P. Bimodal thrombus imaging: simultaneous PET/MR imaging with a fibrin-targeted dual PET/MR probe – feasibility study in rat model. Radiology. 2011;258:812–20.

    Article  PubMed Central  PubMed  Google Scholar 

  102. Morbelli S, Perneczky R, Drzezga A, Frisoni GB, Caroli A, van Berckel BN, et al. Metabolic networks underlying cognitive reserve in prodromal Alzheimer disease: a European Alzheimer disease consortium project. J Nucl Med. 2013;54:894–902.

    Article  CAS  PubMed  Google Scholar 

  103. Yakushev I, Chételat G, Fischer FU, Landeau B, Bastin C, Scheurich A, et al. Metabolic and structural connectivity within the default mode network relates to working memory performance in young healthy adults. Neuroimage. 2013;79:184–90.

    Article  PubMed  Google Scholar 

  104. Villien M, Wey H-Y, Mandeville JB, Catana C, Polimeni JR, Sander CY, et al. Dynamic functional imaging of brain glucose utilization using fPET-FDG. Neuroimage. 2014;100:192–9.

    Article  PubMed  Google Scholar 

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Acknowledgments

We acknowledge the great support of the PET/MR, cyclotron and PET radiopharmacy teams at Leipzig University, Department of Nuclear Medicine. We are also grateful to Dominik Fritzsch, Donald Lobsien, and Karl-Titus Hoffmann of Leipzig University Department of Neuroradiology and to Andreas Schäfer, Joran Lobsien, Robert Turner, Harald Möller and Arno Villringer of Leipzig Max Planck Institute for Human Cognitive and Brain Sciences.

Disclosures

Henryk Barthel and Osama Sabri have been invited by Siemens Healthcare to present lectures on PET/MR imaging. Henryk Barthel and Osama Sabri received speaker and consultant honoraria related to amyloid imaging from Bayer Healthcare and Piramal Imaging. Alexander Drzezga received speaker and/or consultant honoraria from Bayer Healthcare/Piramal Imaging, GE Healthcare, Siemens Healthcare and AVID/Lilly Pharmaceuticals. The Leipzig University combined PET/MR system was sponsored by the German Research Foundation through grant no. SA 669/9-1.

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Authors and Affiliations

  1. Department of Nuclear Medicine, University Hospital Leipzig, Liebigstr. 18, 04103, Leipzig, Germany

    P. Werner, H. Barthel & O. Sabri

  2. Department of Nuclear Medicine, University Hospital Cologne, 50937, Köln, Germany

    A. Drzezga

Authors
  1. P. Werner
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  2. H. Barthel
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  3. A. Drzezga
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  4. O. Sabri
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Corresponding author

Correspondence to O. Sabri.

Additional information

P. Werner, H. Barthel, A. Drzezga and O. Sabri contributed equally to this work.

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Werner, P., Barthel, H., Drzezga, A. et al. Current status and future role of brain PET/MRI in clinical and research settings. Eur J Nucl Med Mol Imaging 42, 512–526 (2015). https://doi.org/10.1007/s00259-014-2970-9

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  • DOI: https://doi.org/10.1007/s00259-014-2970-9

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