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Emerging PET/MRI applications in neuroradiology and neuroscience

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Abstract

PET and MRI are powerful imaging techniques that have been used extensively to study diseases of the brain, head, and neck. In many diseases, including dementia, epilepsy and head and neck cancers, PET and MRI play important and complementary roles in standard diagnostic evaluation. Recent advances in PET detector technology have allowed combination of PET and MRI into a single machine capable of simultaneous imaging which may offer several, distinct advantages over serial imaging and post-acquisition fusion such as decreased patient burden and improved PET imaging quantification. In addition, a PET/MR instrument potentially has the unique ability to combine time-dependent physiological and functional information from MRI with the specific metabolic and receptor specific information from PET imaging. Over the past several years, numerous anecdotal reports and several larger studies showed the feasibility of PET/MR in various brain and head and neck applications including, for example, concomitant fMRI and PET neuroreceptor imaging. Future well-designed studies with a focus on evaluating and optimizing the synergistic qualities of these combined technologies may fulfill the promise of PET-MRI to provide unparalleled opportunities to understand complex brain function and pathology.

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References

  1. Shao Y et al (1997) Simultaneous PET and MR imaging. Phys Med Biol 42(10):1965–1970

    Article  CAS  PubMed  Google Scholar 

  2. Woods RP, Mazziotta JC, Cherry SR (1993) MRI-PET registration with automated algorithm. J Comput Assist Tomogr 17(4):536–546

    Article  CAS  PubMed  Google Scholar 

  3. Schlemmer HP et al (2008) Simultaneous MR/PET imaging of the human brain: feasibility study. Radiology 248(3):1028–1035

    Article  PubMed  Google Scholar 

  4. Catana C et al (2006) Simultaneous acquisition of multislice PET and MR images: initial results with a MR-compatible PET scanner. J Nucl Med 47(12):1968–1976

    PubMed  Google Scholar 

  5. von Schulthess GK et al (2013) Clinical positron emission tomography/magnetic resonance imaging applications. Semin Nucl Med 43(1):3–10

    Article  PubMed  Google Scholar 

  6. Delso G, Ter Voert E, Veit-Haibach P (2015) How does PET/MR work? Basic physics for physicians. Abdom Imaging 40(6):1352–1357

    Article  PubMed  Google Scholar 

  7. Garibotto V et al (2013) Clinical applications of hybrid PET/MRI in neuroimaging. Clin Nucl Med 38(1):e13–e18

    Article  PubMed  Google Scholar 

  8. Zaidi H et al (2011) Design and performance evaluation of a whole-body Ingenuity TF PET-MRI system. Phys Med Biol 56(10):3091–3106

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Veit-Haibach P et al (2013) PET-MR imaging using a tri-modality PET/CT-MR system with a dedicated shuttle in clinical routine. MAGMA 26(1):25–35

    Article  PubMed  Google Scholar 

  10. Vargas MI et al (2013) Approaches for the optimization of MR protocols in clinical hybrid PET/MRI studies. MAGMA 26(1):57–69

    Article  PubMed  Google Scholar 

  11. Surti S et al (2011) Impact of time-of-flight PET on whole-body oncologic studies: a human observer lesion detection and localization study. J Nucl Med 52(5):712–719

    Article  PubMed  PubMed Central  Google Scholar 

  12. Yoon HS et al (2012) Initial results of simultaneous PET/MRI experiments with an MRI-compatible silicon photomultiplier PET scanner. J Nucl Med 53(4):608–614

    Article  CAS  PubMed  Google Scholar 

  13. Delso G et al (2011) Performance measurements of the Siemens mMR integrated whole-body PET/MR scanner. J Nucl Med 52(12):1914–1922

    Article  PubMed  Google Scholar 

  14. de Galiza Barbosa F, von Schulthess G, Veit-Haibach P (2015) Workflow in simultaneous PET/MRI. Semin Nucl Med 45(4):332–344

    Article  Google Scholar 

  15. Martinez-Moller A et al (2009) Tissue classification as a potential approach for attenuation correction in whole-body PET/MRI: evaluation with PET/CT data. J Nucl Med 50(4):520–526

    Article  PubMed  Google Scholar 

  16. Kim JH et al (2012) Comparison of segmentation-based attenuation correction methods for PET/MRI: evaluation of bone and liver standardized uptake value with oncologic PET/CT data. J Nucl Med 53(12):1878–1882

    Article  PubMed  Google Scholar 

  17. Aznar MC et al (2014) Whole-body PET/MRI: the effect of bone attenuation during MR-based attenuation correction in oncology imaging. Eur J Radiol 83(7):1177–1183

    Article  CAS  PubMed  Google Scholar 

  18. Samarin A et al (2012) PET/MR imaging of bone lesions–implications for PET quantification from imperfect attenuation correction. Eur J Nucl Med Mol Imaging 39(7):1154–1160

    Article  PubMed  Google Scholar 

  19. Izquierdo-Garcia D, Catana C (2016) MR Imaging–Guided Attenuation Correction of PET Data in PET/MR Imaging. PET Clin 11(2):129–149

    Article  PubMed  Google Scholar 

  20. Hofmann M et al (2011) MRI-based attenuation correction for whole-body PET/MRI: quantitative evaluation of segmentation- and atlas-based methods. J Nucl Med 52(9):1392–1399

    Article  PubMed  Google Scholar 

  21. Delso G et al (2014) Anatomic evaluation of 3-dimensional ultrashort-echo-time bone maps for PET/MR attenuation correction. J Nucl Med 55(5):780–785

    Article  PubMed  Google Scholar 

  22. Boellaard R et al (2014) Accurate PET/MR quantification using time of flight MLAA image reconstruction. Mol Imaging Biol 16(4):469–477

    Article  CAS  PubMed  Google Scholar 

  23. Rezaei A, Defrise M, Nuyts J (2014) ML-reconstruction for TOF-PET with simultaneous estimation of the attenuation factors. IEEE Trans Med Imaging 33(7):1563–1572

    Article  PubMed  Google Scholar 

  24. Chen CA et al (2011) New MR imaging methods for metallic implants in the knee: artifact correction and clinical impact. J Magn Reson Imaging 33(5):1121–1127

    Article  PubMed  PubMed Central  Google Scholar 

  25. Koch KM et al (2009) A multispectral three-dimensional acquisition technique for imaging near metal implants. Magn Reson Med 61(2):381–390

    Article  PubMed  Google Scholar 

  26. Lu W et al (2009) SEMAC: slice encoding for metal artifact correction in MRI. Magn Reson Med 62(1):66–76

    Article  PubMed  PubMed Central  Google Scholar 

  27. Davison H et al (2015) Incorporation of time-of-flight information reduces metal artifacts in simultaneous positron emission tomography/magnetic resonance imaging: a simulation study. Invest Radiol 50(7):423–429

    Article  PubMed  Google Scholar 

  28. Gunzinger JM et al (2014) Metal artifact reduction in patients with dental implants using multispectral three-dimensional data acquisition for hybrid PET/MRI. EJNMMI Phys 1(1):102

    Article  PubMed  PubMed Central  Google Scholar 

  29. Lee W et al (2011) Effects of MR contrast agents on PET quantitation in PET-MRI study. J Nucl Med 52(suppl 1):53

  30. Lois C et al (2012) Effect of MR contrast agents on quantitative accuracy of PET in combined whole-body PET/MR imaging. Eur J Nucl Med Mol Imaging 39(11):1756–1766

    Article  CAS  PubMed  Google Scholar 

  31. Catana C et al (2012) PET/MRI for neurologic applications. J Nucl Med 53(12):1916–1925

    Article  PubMed  Google Scholar 

  32. Catana C et al (2011) MRI-assisted PET motion correction for neurologic studies in an integrated MR-PET scanner. J Nucl Med 52(1):154–161

    Article  PubMed  PubMed Central  Google Scholar 

  33. Raichle ME et al (1983) Brain Blood Flow Measured with Intravenous H2150. II. Implementation and validation. J Nucl Med 24(9):790–798

    CAS  PubMed  Google Scholar 

  34. Su Y et al (2013) Noninvasive estimation of the arterial input function in positron emission tomography imaging of cerebral blood flow. J Cereb Blood Flow Metab 33(1):115–121

    Article  CAS  PubMed  Google Scholar 

  35. Fung EK, Carson RE (2013) Cerebral blood flow with [15O] water PET studies using an image-derived input function and MR-defined carotid centerlines. Phys Med Biol 58(6):1903–1923

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  36. Kwan P, Brodie MJ (2003) Clinical trials of antiepileptic medications in newly diagnosed patients with epilepsy. Neurology 60(11 Suppl 4):S2–S12

    Article  CAS  PubMed  Google Scholar 

  37. Engel Jr J et al (2003) Practice parameter: temporal lobe and localized neocortical resections for epilepsy. Epilepsia 44(6):741–751

    Article  Google Scholar 

  38. Jones AL, Cascino GD (2016) Evidence on Use of Neuroimaging for Surgical Treatment of Temporal Lobe Epilepsy: A Systematic Review. JAMA Neurol 73(4):464–470

    Article  PubMed  Google Scholar 

  39. Theodore WH et al (2001) Hippocampal volume and glucose metabolism in temporal lobe epileptic foci. Epilepsia 42(1):130–132

    Article  CAS  PubMed  Google Scholar 

  40. Theodore WH et al (1992) Temporal lobectomy for uncontrolled seizures: the role of positron emission tomography. Ann Neurol 32(6):789–794

    Article  CAS  PubMed  Google Scholar 

  41. Gok B et al (2013) The evaluation of FDG-PET imaging for epileptogenic focus localization in patients with MRI positive and MRI negative temporal lobe epilepsy. Neuroradiology 55(5):541–550

    Article  PubMed  Google Scholar 

  42. Chassoux F et al (2010) FDG-PET improves surgical outcome in negative MRI Taylor-type focal cortical dysplasias. Neurology 75(24):2168–2175

    Article  CAS  PubMed  Google Scholar 

  43. Lee KK, Salamon N (2009) [18F] fluorodeoxyglucose-positron-emission tomography and MR imaging coregistration for presurgical evaluation of medically refractory epilepsy. AJNR Am J Neuroradiol 30(10):1811–1816

    Article  CAS  PubMed  Google Scholar 

  44. Salamon N et al (2008) FDG-PET/MRI coregistration improves detection of cortical dysplasia in patients with epilepsy. Neurology 71(20):1594–1601

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Capraz IY et al (2015) Surgical outcome in patients with MRI-negative, PET-positive temporal lobe epilepsy. Seizure 29:63–68

    Article  PubMed  Google Scholar 

  46. Carne RP et al (2004) MRI-negative PET-positive temporal lobe epilepsy: a distinct surgically remediable syndrome. Brain 127(Pt 10):2276–2285

    Article  CAS  PubMed  Google Scholar 

  47. LoPinto-Khoury C et al (2012) Surgical outcome in PET-positive, MRI-negative patients with temporal lobe epilepsy. Epilepsia 53(2):342–348

    Article  PubMed  Google Scholar 

  48. Yang PF et al (2014) Long-term epilepsy surgery outcomes in patients with PET-positive, MRI-negative temporal lobe epilepsy. Epilepsy Behav 41:91–97

    Article  PubMed  Google Scholar 

  49. Grouiller F et al (2015) All-in-one interictal presurgical imaging in patients with epilepsy: single-session EEG/PET/(f) MRI. Eur J Nucl Med Mol Imaging 42(7):1133–1143

    Article  PubMed  Google Scholar 

  50. Ding YS et al (2014) A pilot study in epilepsy patients using simultaneous PET/MR. Am J Nucl Med Mol Imaging 4(5):459–470

    PubMed  PubMed Central  Google Scholar 

  51. Shin HW et al (2015) Initial experience in hybrid PET-MRI for evaluation of refractory focal onset epilepsy. Seizure 31:1–4

    Article  PubMed  Google Scholar 

  52. Gaugler J, James B, Johnson T, Scholz K, Weuve J. for the Alzheimer’s Association (2014) 2014 Alzheimer’s disease facts and figures. Alzheimers Dement 10(2):e47–e92

    Article  Google Scholar 

  53. Nasrallah IM, Wolk DA (2014) Multimodality imaging of Alzheimer disease and other neurodegenerative dementias. J Nucl Med 55(12):2003–2011

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. De Leon MJ et al (1993) Measurement of medial temporal lobe atrophy in diagnosis of Alzheimer’s disease. Lancet 341(8837):125–126

    Article  CAS  PubMed  Google Scholar 

  55. Whitwell JL et al (2008) MRI patterns of atrophy associated with progression to AD in amnestic mild cognitive impairment. Neurology 70(7):512–520

    Article  CAS  PubMed  Google Scholar 

  56. Davatzikos C et al (2009) Longitudinal progression of Alzheimer’s-like patterns of atrophy in normal older adults: the SPARE-AD index. Brain 132(Pt 8):2026–2035

    Article  PubMed  PubMed Central  Google Scholar 

  57. Fan Y et al (2008) Structural and functional biomarkers of prodromal Alzheimer’s disease: a high-dimensional pattern classification study. Neuroimage 41(2):277–285

    Article  PubMed  PubMed Central  Google Scholar 

  58. Shu N et al (2012) Disrupted topological organization in white matter structural networks in amnestic mild cognitive impairment: relationship to subtype. Radiology 265(2):518–527

    Article  PubMed  Google Scholar 

  59. Choo IH et al (2013) Combination of 18F-FDG PET and cerebrospinal fluid biomarkers as a better predictor of the progression to Alzheimer’s disease in mild cognitive impairment patients. J Alzheimers Dis 33(4):929–939

    CAS  PubMed  Google Scholar 

  60. Barthel H et al (2011) Cerebral amyloid-beta PET with florbetaben (18F) in patients with Alzheimer’s disease and healthy controls: a multicentre phase 2 diagnostic study. Lancet Neurol 10(5):424–435

    Article  CAS  PubMed  Google Scholar 

  61. Shaffer JL et al (2013) Predicting cognitive decline in subjects at risk for Alzheimer disease by using combined cerebrospinal fluid, MR imaging, and PET biomarkers. Radiology 266(2):583–591

    Article  PubMed  PubMed Central  Google Scholar 

  62. Hsiao IT et al (2012) Correlation of early-phase 18F-florbetapir (AV-45/Amyvid) PET images to FDG images: preliminary studies. Eur J Nucl Med Mol Imaging 39(4):613–620

    Article  CAS  PubMed  Google Scholar 

  63. Tahmasian M et al (2016) Based on the network degeneration hypothesis: separating individual patients with different neurodegenerative syndromes in a preliminary hybrid PET/MR study. J Nucl Med 57(3):410–415

    Article  PubMed  Google Scholar 

  64. Moodley KK et al (2015) Simultaneous PET-MRI Studies of the Concordance of Atrophy and Hypometabolism in Syndromic Variants of Alzheimer’s Disease and Frontotemporal Dementia: An Extended Case Series. J Alzheimers Dis 46(3):639–653

    Article  CAS  PubMed  Google Scholar 

  65. Bruck A et al (2006) Striatal subregional 6-[18F] fluoro-L-dopa uptake in early Parkinson’s disease: A two-year follow-up study. Mov Disord 21(7):958–963

    Article  PubMed  Google Scholar 

  66. Pikstra AR et al (2016) Relation of 18-F-Dopa PET with hypokinesia-rigidity, tremor and freezing in Parkinson’s disease. Neuroimage Clin 11:68–72

    Article  PubMed  PubMed Central  Google Scholar 

  67. Hsiao IT et al (2014) Correlation of Parkinson disease severity and 18F-DTBZ positron emission tomography. JAMA Neurol 71(6):758–766

    Article  PubMed  Google Scholar 

  68. Okamura N et al (2010) In vivo measurement of vesicular monoamine transporter type 2 density in Parkinson disease with 18F-AV-133. J Nucl Med 51(2):223–228

    Article  PubMed  Google Scholar 

  69. Pavese N et al (2012) [18F] FDOPA uptake in the raphe nuclei complex reflects serotonin transporter availability. A combined [18F] FDOPA and [11 C] DASB PET study in Parkinson’s disease. Neuroimage 59(2):1080–1084

    Article  CAS  PubMed  Google Scholar 

  70. Sander CY et al (2013) Neurovascular coupling to D2/D3 dopamine receptor occupancy using simultaneous PET/functional MRI. Proc Natl Acad Sci U S A 110(27):11169–11174

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  71. Law M et al (2003) 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 24(10):1989–1998

    PubMed  Google Scholar 

  72. Provenzale JM, Mukundan S, Barboriak DP (2006) Diffusion-weighted and perfusion MR imaging for brain tumor characterization and assessment of treatment response. Radiology 239(3):632–649

    Article  PubMed  Google Scholar 

  73. Wang S et al (2016) Differentiating tumor progression from pseudoprogression in patients with glioblastomas using diffusion tensor imaging and dynamic susceptibility contrast MRI. AJNR Am J Neuroradiol 37(1):28–36

    Article  CAS  PubMed  Google Scholar 

  74. Suh CH et al (2013) Prediction of pseudoprogression in patients with glioblastomas using the initial and final area under the curves ratio derived from dynamic contrast-enhanced T1-weighted perfusion MR imaging. AJNR Am J Neuroradiol 34(12):2278–2286

    Article  CAS  PubMed  Google Scholar 

  75. Hustinx R et al (2005) PET imaging for differentiating recurrent brain tumor from radiation necrosis. Radiol Clin N Am 43(1):35–47

    Article  PubMed  Google Scholar 

  76. Werner P et al (2015) Current status and future role of brain PET/MRI in clinical and research settings. Eur J Nucl Med Mol Imaging 42(3):512–526

    Article  CAS  PubMed  Google Scholar 

  77. O’Connor JP et al (2008) Quantitative imaging biomarkers in the clinical development of targeted therapeutics: current and future perspectives. Lancet Oncol 9(8):766–776

    Article  PubMed  CAS  Google Scholar 

  78. Asselin MC et al (2012) Quantifying heterogeneity in human tumours using MRI and PET. Eur J Cancer 48(4):447–455

    Article  PubMed  Google Scholar 

  79. Bisdas S et al (2013) Metabolic mapping of gliomas using hybrid MR-PET imaging: feasibility of the method and spatial distribution of metabolic changes. Invest Radiol 48(5):295–301

    Article  CAS  PubMed  Google Scholar 

  80. Pauleit D et al (2005) O-(2-[18F]fluoroethyl)-L-tyrosine PET combined with MRI improves the diagnostic assessment of cerebral gliomas. Brain 128(Pt 3):678–687

    Article  PubMed  Google Scholar 

  81. Huang RY et al (2015) Pitfalls in the neuroimaging of glioblastoma in the era of antiangiogenic and immuno/targeted therapy–detecting illusive disease, defining response. Front Neurol 6:33

    Article  PubMed  PubMed Central  Google Scholar 

  82. Preuss M et al (2014) Integrated PET/MRI for planning navigated biopsies in pediatric brain tumors. Childs Nerv Syst 30(8):1399–1403

    Article  PubMed  Google Scholar 

  83. Fraioli F et al (2015) 18F-fluoroethylcholine (18F-Cho) PET/MRI functional parameters in pediatric astrocytic brain tumors. Clin Nucl Med 40(1):e40–e45

    Article  PubMed  Google Scholar 

  84. Henriksen OM et al (2016) Simultaneous evaluation of brain tumour metabolism, structure and blood volume using [18F]-fluoroethyltyrosine (FET) PET/MRI: feasibility, agreement and initial experience. Eur J Nucl Med Mol Imaging 43(1):103–112

    Article  CAS  PubMed  Google Scholar 

  85. Shields AF et al (1998) Imaging proliferation in vivo with [F-18] FLT and positron emission tomography. Nat Med 4(11):1334–1336

    Article  CAS  PubMed  Google Scholar 

  86. Muzi M et al (2006) Kinetic analysis of 3’-deoxy-3’-18F-fluorothymidine in patients with gliomas. J Nucl Med 47(10):1612–1621

    CAS  PubMed  Google Scholar 

  87. Ullrich R et al (2008) Glioma proliferation as assessed by 3’-fluoro-3’-deoxy-L-thymidine positron emission tomography in patients with newly diagnosed high-grade glioma. Clin Cancer Res 14(7):2049–2055

    Article  CAS  PubMed  Google Scholar 

  88. Abgral R et al (2009) Does 18F-FDG PET/CT improve the detection of posttreatment recurrence of head and neck squamous cell carcinoma in patients negative for disease on clinical follow-up? J Nucl Med 50(1):24–29

    Article  PubMed  Google Scholar 

  89. Queiroz MA, Huellner MW (2015) PET/MR in cancers of the head and neck. Semin Nucl Med 45(3):248–265

    Article  PubMed  Google Scholar 

  90. Boss A et al (2011) Feasibility of simultaneous PET/MR imaging in the head and upper neck area. Eur Radiol 21(7):1439–1446

    Article  PubMed  Google Scholar 

  91. Kuhn FP et al (2014) Contrast-enhanced PET/MR imaging versus contrast-enhanced PET/CT in head and neck cancer: how much MR information is needed? J Nucl Med 55(4):551–558

    Article  CAS  PubMed  Google Scholar 

  92. Varoquaux A et al (2014) Detection and quantification of focal uptake in head and neck tumours: 18F-FDG PET/MR versus PET/CT. Eur J Nucl Med Mol Imaging 41(3):462–475

    Article  CAS  PubMed  Google Scholar 

  93. de Bree R et al (2000) Screening for distant metastases in patients with head and neck cancer. Laryngoscope 110(3 Pt 1):397–401

    Article  CAS  PubMed  Google Scholar 

  94. Strobel K et al (2009) Head and neck squamous cell carcinoma (HNSCC)–detection of synchronous primaries with 18F-FDG-PET/CT. Eur J Nucl Med Mol Imaging 36(6):919–927

    Article  PubMed  Google Scholar 

  95. Ladefoged CN et al (2015) Dental artifacts in the head and neck region: implications for Dixon-based attenuation correction in PET/MR. EJNMMI Phys 2(1):8

    Article  PubMed  PubMed Central  Google Scholar 

  96. Becker M et al (2008) Neoplastic invasion of Laryngeal Cartilage: Reassessment of Criteria for Diagnosis at MR Imaging. Radiology 249(2):551–559

    Article  PubMed  Google Scholar 

  97. Hacke W et al (2008) Thrombolysis with alteplase 3 to 4.5 hours after acute ischemic stroke. N Engl J Med 359(13):1317–1329

    Article  CAS  PubMed  Google Scholar 

  98. Thijs VN et al (2001) Relationship between severity of MR perfusion deficit and DWI lesion evolution. Neurology 57(7):1205–1211

    Article  CAS  PubMed  Google Scholar 

  99. Heiss WD et al (1998) 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 18(12):1298–1307

    Article  CAS  PubMed  Google Scholar 

  100. van Golen LW et al (2014) Quantification of cerebral blood flow in healthy volunteers and type 1 diabetic patients: Comparison of MRI arterial spin labeling and [15O] H2O positron emission tomography (PET). J Magn Reson Imaging 40(6):1300–1309

    Article  PubMed  Google Scholar 

  101. Zhang K et al (2014) 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 34(8):1373–1380

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  102. Andersen JB et al (2015) Positron emission tomography/magnetic resonance hybrid scanner imaging of cerebral blood flow using 15O-water positron emission tomography and arterial spin labeling magnetic resonance imaging in newborn piglets. J Cereb Blood Flow Metab 35(11):1703–1710

    Article  PubMed  PubMed Central  Google Scholar 

  103. Sarrafzadeh AS et al (2010) Imaging of hypoxic–ischemic penumbra with 18F-fluoromisonidazole PET/CT and measurement of related cerebral metabolism in aneurysmal subarachnoid hemorrhage. J Cereb Blood Flow Metab 30(1):36–45

    Article  CAS  PubMed  Google Scholar 

  104. Poloni G et al (2011) Recent developments in imaging of multiple sclerosis. Neurologist 17(4):185–204

    Article  PubMed  Google Scholar 

  105. Hagens M, van Berckel B, Barkhof F (2016) Novel MRI and PET markers of neuroinflammation in multiple sclerosis. Curr Opin Neurol 29(3):229–236

    Article  CAS  PubMed  Google Scholar 

  106. Bolcaen J et al (2013) Structural and metabolic features of two different variants of multiple sclerosis: a PET/MRI study. J Neuroimaging 23(3):431–436

    Article  PubMed  Google Scholar 

  107. Wey HY et al (2014) Simultaneous fMRI-PET of the opioidergic pain system in human brain. Neuroimage 102(Pt 2):275–282

    Article  PubMed  PubMed Central  Google Scholar 

  108. Gutte H et al (2015) Simultaneous hyperpolarized 13C-pyruvate MRI and 18F-FDG PET (HyperPET) in 10 dogs with cancer. J Nucl Med 56(11):1786–1792

    Article  CAS  PubMed  Google Scholar 

  109. Keshari KR et al (2015) Metabolic response of prostate cancer to nicotinamide phophoribosyltransferase inhibition in a hyperpolarized MR/PET compatible bioreactor. Prostate 75(14):1601–1609

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  110. Incerti E et al (2015) Radiation treatment of lymph node recurrence from prostate cancer: is 11C-choline PET/CT predictive of survival outcomes? J Nucl Med 56(12):1836–1842

    Article  CAS  PubMed  Google Scholar 

  111. Bolus NE et al (2009) PET/MRI: the blended-modality choice of the future? J Nucl Med Technol 37(2):63–71

    Article  PubMed  Google Scholar 

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Correspondence to Jacob Dubroff.

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The authors, Seyed Ali Nabavizadeh, Ilya Nasrallah, and Jacob Dubroff, all declare no conflict.

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Nabavizadeh, S.A., Nasrallah, I. & Dubroff, J. Emerging PET/MRI applications in neuroradiology and neuroscience. Clin Transl Imaging 5, 121–133 (2017). https://doi.org/10.1007/s40336-016-0209-4

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