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Hybrid PET/MR Neuroimaging pp 827–838Cite as

Perfusion PET and Cerebrovascular Reactivity with Acetazolamide Versus CO2 Challenge

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Abstract

Hybrid PET/MRI is being increasingly employed for quantitative cerebral perfusion imaging and assessment of cerebrovascular reactivity. Perfusion PET with diffusible tracers such as 15O-H2O is capable of precise cerebral blood flow (CBF) quantification and is the gold standard for the validation of protocols for other imaging-based techniques such as arterial spin labeling MRI. In hybrid acquisition, MRI aids in simplifying the PET protocol and improves the accuracy of autoradiographic or kinetic analysis by deriving parameters related to arterial input and tissue composition. Intravenous administration of acetazolamide and inducing hypercapnia using a breathing apparatus are the most common methods employed for modulating brain perfusion to measure cerebrovascular reactivity as a proxy of cerebrovascular reserve capacity, an important clinical marker in cerebrovascular diseases. Impaired vasodilatory response to these stimuli indicates areas that are at risk for ischemia. Simultaneous PET/MRI is essential for refining cerebrovascular reactivity MRI protocols and for assessing their applicability and limitations in various diseases and pathophysiologic scenarios prior to clinical deployment.

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References

  1. Xing CY, Tarumi T, Liu J, et al. Distribution of cardiac output to the brain across the adult lifespan. J Cereb Blood Flow Metab. 2017;37(8):2848–56.

    Article  PubMed  Google Scholar 

  2. Aanerud J, Borghammer P, Rodell A, et al. Sex differences of human cortical blood flow and energy metabolism. J Cereb Blood Flow Metab. 2017;37(7):2433–40.

    Article  PubMed  Google Scholar 

  3. Raichle ME, Grubb RL Jr, Gado MH, et al. Correlation between regional cerebral blood flow and oxidative metabolism. In vivo studies in man. Arch Neurol. 1976;33(8):523–6.

    Article  CAS  PubMed  Google Scholar 

  4. Ishii K, Sasaki M, Kitagaki H, et al. Regional difference in cerebral blood flow and oxidative metabolism in human cortex. J Nucl Med. 1996;37(7):1086–8.

    CAS  PubMed  Google Scholar 

  5. Morris ED, Endres CJ, Schmidt KC, et al. Kinetic modeling in positron emission tomography. San Diego: Emission Tomography: The Fundamentals of PET and SPECT Academic; 2004.

    Book  Google Scholar 

  6. Raichle ME, Martin WR, Herscovitch P, et al. Brain blood flow measured with intravenous H2(15)O. II. Implementation and validation. J Nucl Med. 1983;24(9):790–8.

    CAS  PubMed  Google Scholar 

  7. Fan AP, Jahanian H, Holdsworth SJ, et al. Comparison of cerebral blood flow measurement with [15O]-water positron emission tomography and arterial spin labeling magnetic resonance imaging: a systematic review. J Cereb Blood Flow Metab. 2016;36(5):842–61.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. McDevitt DG, Nies AS. Simultaneous measurement of cardiac output and its distribution with microspheres in the rat. Cardiovasc Res. 1976;10(4):494–8.

    Article  CAS  PubMed  Google Scholar 

  9. Brooks DJ, Frackowiak RS, Lammertsma AA, et al. A comparison between regional cerebral blood flow measurements obtained in human subjects using 11C-methylalbumin microspheres, the C15O2 steady-state method, and positron emission tomography. Acta Neurol Scand. 1986;73(4):415–22.

    Article  CAS  PubMed  Google Scholar 

  10. Andersen AR. 99mTc-D,L-hexamethylene-propyleneamine oxime (99mTc-HMPAO): basic kinetic studies of a tracer of cerebral blood flow. Cerebrovasc Brain Metab Rev. 1989;1(4):288–318.

    CAS  PubMed  Google Scholar 

  11. Ito H, Inoue K, Goto R, et al. Database of normal human cerebral blood flow measured by SPECT: I. Comparison between I-123-IMP, Tc-99m-HMPAO, and Tc-99m-ECD as referred with O-15 labeled water PET and voxel-based morphometry. Ann Nucl Med. 2006;20(2):131–8.

    Article  CAS  PubMed  Google Scholar 

  12. Kety SS, Schmidt CF. The nitrous oxide method for the quantitative determination of cerebral blood flow in man: theory, procedure and normal values. J Clin Invest. 1948;27(4):476–83.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Landau WM, Freygang WH Jr, Roland LP, et al. The local circulation of the living brain; values in the unanesthetized and anesthetized cat. Trans Am Neurol Assoc. 1955;80th Meeting:125–9.

    Google Scholar 

  14. Meier P, Zierler KL. On the theory of the indicator-dilution method for measurement of blood flow and volume. J Appl Physiol. 1954;6(12):731–44.

    Article  CAS  PubMed  Google Scholar 

  15. Goetti R, Warnock G, Kuhn FP, et al. Quantitative cerebral perfusion imaging in children and young adults with Moyamoya disease: comparison of arterial spin-labeling-MRI and H(2)[(15)O]-PET. AJNR Am J Neuroradiol. 2014;35(5):1022–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Huang SC, Mahoney DK, Phelps ME. Quantitation in positron emission tomography: 8. Effects of nonlinear parameter estimation on functional images. J Comput Assist Tomogr. 1987;11(2):314–25.

    Article  CAS  PubMed  Google Scholar 

  17. Herscovitch P, Markham J, Raichle ME. Brain blood flow measured with intravenous H2(15)O. I. Theory and error analysis. J Nucl Med. 1983;24(9):782–9.

    CAS  PubMed  Google Scholar 

  18. Boellaard R, Knaapen P, Rijbroek A, et al. Evaluation of basis function and linear least squares methods for generating parametric blood flow images using 15O-water and positron emission tomography. Mol Imaging Biol. 2005;7(4):273–85.

    Article  PubMed  Google Scholar 

  19. Lammertsma AA, Jones T, Frackowiak RS, et al. A theoretical study of the steady-state model for measuring regional cerebral blood flow and oxygen utilisation using oxygen-15. J Comput Assist Tomogr. 1981;5(4):544–50.

    Article  CAS  PubMed  Google Scholar 

  20. Iida H, Kanno I, Miura S, et al. Error analysis of a quantitative cerebral blood flow measurement using H2(15)O autoradiography and positron emission tomography, with respect to the dispersion of the input function. J Cereb Blood Flow Metab. 1986;6(5):536–45.

    Article  CAS  PubMed  Google Scholar 

  21. Kamano H, Yoshiura T, Hiwatashi A, et al. Arterial spin labeling in patients with chronic cerebral artery steno-occlusive disease: correlation with (15)O-PET. Acta Radiol. 2013;54(1):99–106.

    Article  PubMed  Google Scholar 

  22. Islam MM, Tsujikawa T, Mori T, et al. Pixel-by-pixel precise delay correction for measurement of cerebral hemodynamic parameters in H(2)(15)O PET study. Ann Nucl Med. 2017;31(4):283–94.

    Article  PubMed  PubMed Central  Google Scholar 

  23. Singh A, Rathore RK, Haris M, et al. Improved bolus arrival time and arterial input function estimation for tracer kinetic analysis in DCE-MRI. J Magn Reson Imaging. 2009;29(1):166–76.

    Article  PubMed  Google Scholar 

  24. Evans E, Sawiak SJ, Ward AO, et al. Comparison of first pass bolus AIFs extracted from sequential (18)F-FDG PET and DSC-MRI of mice. Nucl Instrum Methods Phys Res A. 2014;734(B):137–40.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Jochimsen TH, Zeisig V, Schulz J, et al. Fully automated calculation of image-derived input function in simultaneous PET/MRI in a sheep model. EJNMMI Phys. 2016;3(1):2.

    Article  PubMed  PubMed Central  Google Scholar 

  26. Livne M, Madai VI, Brunecker P, et al. A PET-guided framework supports a multiple arterial input functions approach in DSC-MRI in acute stroke. J Neuroimaging. 2017;27(5):486–92.

    Article  PubMed  Google Scholar 

  27. Khalighi MM, Deller TW, Fan AP, et al. Image-derived input function estimation on a TOF-enabled PET/MR for cerebral blood flow mapping. J Cereb Blood Flow Metab. 2018;38(1):126–35.

    Article  CAS  PubMed  Google Scholar 

  28. Richard MA, Fouquet JP, Lebel R, et al. MRI-guided derivation of the input function for PET kinetic modeling. PET Clin. 2016;11(2):193–202.

    Article  PubMed  Google Scholar 

  29. Zhang X, Xie Z, Berg E, et al. Total-body dynamic reconstruction and parametric imaging on the uEXPLORER. J Nucl Med. 2020;61(2):285–91.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Iida H, Kanno I, Miura S, et al. A determination of the regional brain/blood partition coefficient of water using dynamic positron emission tomography. J Cereb Blood Flow Metab. 1989;9(6):874–85.

    Article  CAS  PubMed  Google Scholar 

  31. Herscovitch P, Raichle ME. What is the correct value for the brain--blood partition coefficient for water? J Cereb Blood Flow Metab. 1985;5(1):65–9.

    Article  CAS  PubMed  Google Scholar 

  32. Alsop DC, Detre JA, Golay X, et al. Recommended implementation of arterial spin-labeled perfusion MRI for clinical applications: a consensus of the ISMRM perfusion study group and the European consortium for ASL in dementia. Magn Reson Med. 2015;73(1):102–16.

    Article  PubMed  Google Scholar 

  33. Roberts DA, Rizi R, Lenkinski RE, et al. Magnetic resonance imaging of the brain: blood partition coefficient for water: application to spin-tagging measurement of perfusion. J Magn Reson Imaging. 1996;6(2):363–6.

    Article  CAS  PubMed  Google Scholar 

  34. Thalman SW, Powell DK, Lin AL. Novel calibrated short TR recovery (CaSTRR) method for brain-blood partition coefficient correction enhances Gray-white matter contrast in blood flow measurements in mice. Front Neurosci. 2019;13:308.

    Article  PubMed  PubMed Central  Google Scholar 

  35. Gutierrez D, Montandon ML, Assal F, et al. Anatomically guided voxel-based partial volume effect correction in brain PET: impact of MRI segmentation. Comput Med Imaging Graph. 2012;36(8):610–9.

    Article  PubMed  Google Scholar 

  36. Tahaei MS, Reader AJ, Collins DL. Two novel PET image restoration methods guided by PET-MR kernels: application to brain imaging. Med Phys. 2019;46(5):2085–102.

    Article  PubMed  Google Scholar 

  37. Herzog H, Seitz RJ, Tellmann L, et al. Quantitation of regional cerebral blood flow with 15O-butanol and positron emission tomography in humans. J Cereb Blood Flow Metab. 1996;16(4):645–9.

    Article  CAS  PubMed  Google Scholar 

  38. Lorthois S, Duru P, Billanou I, et al. Kinetic modeling in the context of cerebral blood flow quantification by H2(15)O positron emission tomography: the meaning of the permeability coefficient in Renkin-Crone′s model revisited at capillary scale. J Theor Biol. 2014;353:157–69.

    Article  PubMed  Google Scholar 

  39. Berridge MS, Adler LP, Nelson AD, et al. Measurement of human cerebral blood flow with [15O]butanol and positron emission tomography. J Cereb Blood Flow Metab. 1991;11(5):707–15.

    Article  CAS  PubMed  Google Scholar 

  40. Martin CC, Jerabek PA, Nickerson LD, et al. Effect of partition coefficient, permeability surface product, and radioisotope on the signal-to-noise ratio in PET functional brain mapping: a computer simulation. Hum Brain Mapp. 1999;7(3):151–60.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Herscovitch P, Raichle ME, Kilbourn MR, et al. Positron emission tomographic measurement of cerebral blood flow and permeability-surface area product of water using [15O]water and [11C]butanol. J Cereb Blood Flow Metab. 1987;7(5):527–42.

    Article  CAS  PubMed  Google Scholar 

  42. Herscovitch P, Raichle M, Kilbourn M, et al. Use of O-15 water and C-11 butanol to measure cerebral blood flow (CBF) and water permeability with positron emission tomography (PET). J Nucl Med. 1985;26(5):6.

    Google Scholar 

  43. Rasmussen PM, Jespersen SN, Østergaard L. The effects of transit time heterogeneity on brain oxygenation during rest and functional activation. J Cereb Blood Flow Metab. 2015;35(3):432–42.

    Article  PubMed  Google Scholar 

  44. Buxton RB. Dynamic models of BOLD contrast. NeuroImage. 2012;62(2):953–61.

    Article  PubMed  Google Scholar 

  45. Ibaraki M, Shimosegawa E, Miura S, et al. PET measurements of CBF, OEF, and CMRO2 without arterial sampling in hyperacute ischemic stroke: method and error analysis. Ann Nucl Med. 2004;18(1):35–44.

    Article  PubMed  Google Scholar 

  46. Jahanian H, Peltier S, Noll DC, et al. Arterial cerebral blood volume-weighted functional MRI using pseudocontinuous arterial spin tagging (AVAST). Magn Reson Med. 2015;73(3):1053–64.

    Article  PubMed  Google Scholar 

  47. van der Kleij LA, De Vis JB, de Bresser J, et al. Arterial CO(2) pressure changes during hypercapnia are associated with changes in brain parenchymal volume. Eur Radiol Exp. 2020;4(1):17.

    Article  PubMed  PubMed Central  Google Scholar 

  48. Mokri B. The Monro-Kellie hypothesis: applications in CSF volume depletion. Neurology. 2001;56(12):1746–8.

    Article  CAS  PubMed  Google Scholar 

  49. Evans PG, Sokolska M, Alves A, et al. Non-invasive MRI of blood-cerebrospinal fluid barrier function. Nat Commun. 2020;11(1):2081.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Attwell D, Buchan AM, Charpak S, et al. Glial and neuronal control of brain blood flow. Nature. 2010;468(7321):232–43.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Leenders KL, Perani D, Lammertsma AA, et al. Cerebral blood flow, blood volume and oxygen utilization. Normal values and effect of age. Brain. 1990;113(Pt 1):27–47.

    Article  PubMed  Google Scholar 

  52. Grubb RL Jr, Raichle ME, Eichling JO, et al. The effects of changes in PaCO2 on cerebral blood volume, blood flow, and vascular mean transit time. Stroke. 1974;5(5):630–9.

    Article  PubMed  Google Scholar 

  53. Zong X, Kim T, Kim SG. Contributions of dynamic venous blood volume versus oxygenation level changes to BOLD fMRI. NeuroImage. 2012;60(4):2238–46.

    Article  PubMed  Google Scholar 

  54. Vagal A, Wintermark M, Nael K, et al. Automated CT perfusion imaging for acute ischemic stroke: pearls and pitfalls for real-world use. Neurology. 2019;93(20):888–98.

    Article  PubMed  Google Scholar 

  55. Kaneko K, Kuwabara Y, Mihara F, et al. Validation of the CBF, CBV, and MTT values by perfusion MRI in chronic occlusive cerebrovascular disease: a comparison with 15O-PET. Acad Radiol. 2004;11(5):489–97.

    Article  PubMed  Google Scholar 

  56. Albers GW, Marks MP, Kemp S, et al. Thrombectomy for stroke at 6 to 16 hours with selection by perfusion imaging. N Engl J Med. 2018;378(8):708–18.

    Article  PubMed  PubMed Central  Google Scholar 

  57. Thulborn KR, Atkinson IC, Alexander A, et al. Comparison of blood oxygenation level-dependent fMRI and provocative DSC perfusion MR imaging for monitoring cerebrovascular reserve in intracranial chronic cerebrovascular disease. AJNR Am J Neuroradiol. 2018;39(3):448–53.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Brubaker LM, Smith JK, Lee YZ, et al. Hemodynamic and permeability changes in posterior reversible encephalopathy syndrome measured by dynamic susceptibility perfusion-weighted MR imaging. AJNR Am J Neuroradiol. 2005;26(4):825–30.

    PubMed  PubMed Central  Google Scholar 

  59. Kumar Y, Gupta N, Mangla M, et al. Comparison between MR perfusion and 18F-FDG PET in differentiating tumor recurrence from nonneoplastic contrast-enhancing tissue. Asian Pac J Cancer Prev. 2017;18(3):759–63.

    PubMed  PubMed Central  Google Scholar 

  60. Hatzoglou V, Ulaner GA, Zhang Z, et al. Comparison of the effectiveness of MRI perfusion and fluorine-18 FDG PET-CT for differentiating radiation injury from viable brain tumor: a preliminary retrospective analysis with pathologic correlation in all patients. Clin Imaging. 2013;37(3):451–7.

    Article  PubMed  Google Scholar 

  61. Xu Q, Liu Q, Ge H, et al. Tumor recurrence versus treatment effects in glioma: a comparative study of three dimensional pseudo-continuous arterial spin labeling and dynamic susceptibility contrast imaging. Medicine (Baltimore). 2017;96(50):e9332.

    Article  Google Scholar 

  62. Dirnagl U, Pulsinelli W. Autoregulation of cerebral blood flow in experimental focal brain ischemia. J Cereb Blood Flow Metab. 1990;10(3):327–36.

    Article  CAS  PubMed  Google Scholar 

  63. Keil VC, Eichhorn L, Mutsaerts H, et al. Cerebrovascular reactivity during prolonged breath-hold in experienced Freedivers. AJNR Am J Neuroradiol. 2018;39(10):1839–47.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  64. Willie CK, Smith KJ, Day TA, et al. Regional cerebral blood flow in humans at high altitude: gradual ascent and 2 wk at 5,050 m. J Appl Physiol (1985). 2014;116(7):905–10.

    Article  CAS  Google Scholar 

  65. Donahue MJ, Strother MK, Hendrikse J. Novel MRI approaches for assessing cerebral hemodynamics in ischemic cerebrovascular disease. Stroke. 2012;43(3):903–15.

    Article  PubMed  Google Scholar 

  66. Turan TN, Nizam A, Lynn MJ, et al. Relationship between risk factor control and vascular events in the SAMMPRIS trial. Neurology. 2017;88(4):379–85.

    Article  PubMed  PubMed Central  Google Scholar 

  67. Imaizumi M, Kitagawa K, Oku N, et al. Clinical significance of cerebrovascular reserve in acetazolamide challenge -comparison with acetazolamide challenge H2O-PET and gas-PET. Ann Nucl Med. 2004;18(5):369–74.

    Article  PubMed  Google Scholar 

  68. Han JS, Abou-Hamden A, Mandell DM, et al. Impact of extracranial-intracranial bypass on cerebrovascular reactivity and clinical outcome in patients with symptomatic moyamoya vasculopathy. Stroke. 2011;42(11):3047–54.

    Article  PubMed  Google Scholar 

  69. Ladner TR, Donahue MJ, Arteaga DF, et al. Prior Infarcts, Reactivity, and Angiography in Moyamoya Disease (PIRAMD): a scoring system for moyamoya severity based on multimodal hemodynamic imaging. J Neurosurg. 2017;126(2):495–503.

    Article  PubMed  Google Scholar 

  70. Czosnyka M, Miller C. Monitoring of cerebral autoregulation. Neurocrit Care. 2014;21(Suppl 2):S95–102.

    Article  PubMed  Google Scholar 

  71. Misaki K, Uchiyama N, Inaki A, et al. Objective evaluation of cerebrovascular reactivity for acetazolamide predicts cerebral hyperperfusion after carotid artery stenting: comparison with region of interest methods. J Neuroradiol. 2018;45(6):362–7.

    Article  PubMed  Google Scholar 

  72. Peng SL, Chen X, Li Y, et al. Age-related changes in cerebrovascular reactivity and their relationship to cognition: a four-year longitudinal study. NeuroImage. 2018;174:257–62.

    Article  PubMed  Google Scholar 

  73. Switzer AR, Cheema I, McCreary CR, et al. Cerebrovascular reactivity in cerebral amyloid angiopathy, Alzheimer disease, and mild cognitive impairment. Neurology. 2020;95(10):e1333-e1340; https://doi.org/10.1212/WNL.0000000000010201.

  74. Liu J, Tseng BY, Khan MA, et al. Individual variability of cerebral autoregulation, posterior cerebral circulation and white matter hyperintensity. J Physiol. 2016;594(11):3141–55.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  75. Tryambake D, He J, Firbank MJ, et al. Intensive blood pressure lowering increases cerebral blood flow in older subjects with hypertension. Hypertension. 2013;61(6):1309–15.

    Article  CAS  PubMed  Google Scholar 

  76. Toth P, Tarantini S, Csiszar A, et al. Functional vascular contributions to cognitive impairment and dementia: mechanisms and consequences of cerebral autoregulatory dysfunction, endothelial impairment, and neurovascular uncoupling in aging. Am J Physiol Heart Circ Physiol. 2017;312(1):H1–h20.

    Article  PubMed  Google Scholar 

  77. Catchlove SJ, Pipingas A, Hughes ME, et al. Magnetic resonance imaging for assessment of cerebrovascular reactivity and its relationship to cognition: a systematic review. BMC Neurosci. 2018;19(1):21.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  78. Juttukonda MR, Donahue MJ. Neuroimaging of vascular reserve in patients with cerebrovascular diseases. NeuroImage. 2019;187:192–208.

    Article  PubMed  Google Scholar 

  79. Fathi AR, Yang C, Bakhtian KD, et al. Carbon dioxide influence on nitric oxide production in endothelial cells and astrocytes: cellular mechanisms. Brain Res. 2011;1386:50–7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  80. Yoon S, Zuccarello M, Rapoport RM. pCO(2) and pH regulation of cerebral blood flow. Front Physiol. 2012;3:365.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  81. Zappe AC, Uludağ K, Oeltermann A, et al. The influence of moderate hypercapnia on neural activity in the anesthetized nonhuman primate. Cereb Cortex. 2008;18(11):2666–73.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  82. Whittaker JR, Driver ID, Bright MG, et al. The absolute CBF response to activation is preserved during elevated perfusion: implications for neurovascular coupling measures. NeuroImage. 2016;125:198–207.

    Article  PubMed  Google Scholar 

  83. Démolis P, Florence G, Thomas L, et al. Is the acetazolamide test valid for quantitative assessment of maximal cerebral autoregulatory vasodilation? An experimental study. Stroke. 2000;31(2):508–15.

    Article  PubMed  Google Scholar 

  84. Maren TH. Use of inhibitors in physiological studies of carbonic anhydrase. Am J Phys. 1977;232(4):F291–7.

    CAS  Google Scholar 

  85. Kuwabara Y, Ichiya Y, Sasaki M, et al. Time dependency of the acetazolamide effect on cerebral hemodynamics in patients with chronic occlusive cerebral arteries. Early steal phenomenon demonstrated by [15O]H2O positron emission tomography. Stroke. 1995;26(10):1825–9.

    Article  CAS  PubMed  Google Scholar 

  86. Wong TH, Shagera QA, Ryoo HG, et al. Basal and acetazolamide brain perfusion SPECT in internal carotid artery stenosis. Nucl Med Mol Imaging. 2020;54(1):9–27.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  87. Boles Ponto LL, Schultz SK, Leonard Watkins G, et al. Technical issues in the determination of cerebrovascular reserve in elderly subjects using 15O-water PET imaging. NeuroImage. 2004;21(1):201–10.

    Article  PubMed  Google Scholar 

  88. Fierstra J, Sobczyk O, Battisti-Charbonney A, et al. Measuring cerebrovascular reactivity: what stimulus to use? J Physiol. 2013;591(23):5809–21.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  89. Bueno-Junior LS, Ruggiero RN, Rossignoli MT, et al. Acetazolamide potentiates the afferent drive to prefrontal cortex in vivo. Physiol Rep. 2017;5(1):e13066. https://doi.org/10.14814/phy2.13066. Epub 2017 Jan 13. PMID: 28087816; PMCID: PMC5256155.

  90. Ozgur HT, Kent Walsh T, Masaryk A, et al. Correlation of cerebrovascular reserve as measured by acetazolamide-challenged SPECT with angiographic flow patterns and intra- or extracranial arterial stenosis. AJNR Am J Neuroradiol. 2001;22(5):928–36.

    CAS  PubMed  PubMed Central  Google Scholar 

  91. Ni WW, Christen T, Rosenberg J, et al. Imaging of cerebrovascular reserve and oxygenation in Moyamoya disease. J Cereb Blood Flow Metab. 2017;37(4):1213–22.

    Article  CAS  PubMed  Google Scholar 

  92. Garrett MC, Komotar RJ, Starke RM, et al. Radiographic and clinical predictors of hemodynamic insufficiency in patients with athero-occlusive disease. J Stroke Cerebrovasc Dis. 2008;17(6):340–3.

    Article  PubMed  Google Scholar 

  93. Jo KI, Yeon JY, Hong SC, et al. Clinical course of asymptomatic adult moyamoya disease. Cerebrovasc Dis. 2014;37(2):94–101.

    Article  PubMed  Google Scholar 

  94. Acker G, Lange C, Schatka I, et al. Brain perfusion imaging under acetazolamide challenge for detection of impaired cerebrovascular reserve capacity: positive findings with (15)O-water PET in patients with negative (99m)Tc-HMPAO SPECT findings. J Nucl Med. 2018;59(2):294–8.

    Article  CAS  PubMed  Google Scholar 

  95. Soricelli A, Postiglione A, Cuocolo A, et al. Effect of adenosine on cerebral blood flow as evaluated by single-photon emission computed tomography in normal subjects and in patients with occlusive carotid disease. A comparison with acetazolamide. Stroke. 1995;26(9):1572–6.

    Article  CAS  PubMed  Google Scholar 

  96. Ito H, Kinoshita T, Tamura Y, et al. Effect of intravenous dipyridamole on cerebral blood flow in humans. A PET study. Stroke. 1999;30(8):1616–20.

    Article  CAS  PubMed  Google Scholar 

  97. Addicott MA, Yang LL, Peiffer AM, et al. The effect of daily caffeine use on cerebral blood flow: how much caffeine can we tolerate? Hum Brain Mapp. 2009;30(10):3102–14.

    Article  PubMed  PubMed Central  Google Scholar 

  98. Kapucu OL, Nobili F, Varrone A, et al. EANM procedure guideline for brain perfusion SPECT using 99mTc-labelled radiopharmaceuticals, version 2. Eur J Nucl Med Mol Imaging. 2009;36(12):2093–102.

    Article  CAS  PubMed  Google Scholar 

  99. Olesen ND, Fischer M, Secher NH. Sodium nitroprusside dilates cerebral vessels and enhances internal carotid artery flow in young men. J Physiol. 2018;596(17):3967–76.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  100. Cohen ER, Ugurbil K, Kim SG. Effect of basal conditions on the magnitude and dynamics of the blood oxygenation level-dependent fMRI response. J Cereb Blood Flow Metab. 2002;22(9):1042–53.

    Article  CAS  PubMed  Google Scholar 

  101. Cantin S, Villien M, Moreaud O, et al. Impaired cerebral vasoreactivity to CO2 in Alzheimer's disease using BOLD fMRI. NeuroImage. 2011;58(2):579–87.

    Article  CAS  PubMed  Google Scholar 

  102. Metzger A, Le Bars E, Deverdun J, et al. Is impaired cerebral vasoreactivity an early marker of cognitive decline in multiple sclerosis patients? Eur Radiol. 2018;28(3):1204–14.

    Article  PubMed  Google Scholar 

  103. Chung CC, Pimentel D, Jor'dan AJ, et al. Inflammation-associated declines in cerebral vasoreactivity and cognition in type 2 diabetes. Neurology. 2015;85(5):450–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  104. Tchistiakova E, Anderson ND, Greenwood CE, et al. Combined effects of type 2 diabetes and hypertension associated with cortical thinning and impaired cerebrovascular reactivity relative to hypertension alone in older adults. Neuroimage Clin. 2014;5:36–41.

    Article  PubMed  PubMed Central  Google Scholar 

  105. Tancredi FB, Hoge RD. Comparison of cerebral vascular reactivity measures obtained using breath-holding and CO2 inhalation. J Cereb Blood Flow Metab. 2013;33(7):1066–74.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  106. Poeppel T, Terborg C, Hautzel H, et al. Cerebral haemodynamics during hypo-and hypercapnia. Nuklearmedizin. 2007;46(03):93–100.

    Article  CAS  PubMed  Google Scholar 

  107. Peng SL, Ravi H, Sheng M, et al. Searching for a truly "iso-metabolic" gas challenge in physiological MRI. J Cereb Blood Flow Metab. 2017;37(2):715–25.

    Article  CAS  PubMed  Google Scholar 

  108. Hauser TK, Seeger A, Bender B, et al. Hypercapnic BOLD MRI compared to H(2)(15)O PET/CT for the hemodynamic evaluation of patients with moyamoya disease. Neuroimage Clin. 2019;22:101713.

    Article  PubMed  PubMed Central  Google Scholar 

  109. Hope TA, Fayad ZA, Fowler KJ, et al. Summary of the first ISMRM-SNMMI workshop on PET/MRI: applications and limitations. J Nucl Med. 2019;60(10):1340–6.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  110. Zhu Y, Zhu X. MRI-driven PET image optimization for neurological applications. Front Neurosci. 2019;13:782.

    Article  PubMed  PubMed Central  Google Scholar 

  111. Yan J, Lim JC, Townsend DW. MRI-guided brain PET image filtering and partial volume correction. Phys Med Biol. 2015;60(3):961–76.

    Article  PubMed  Google Scholar 

  112. Cal-González J, Pérez-Liva M, Herraiz JL, et al. Tissue-dependent and spatially-variant positron range correction in 3D PET. IEEE Trans Med Imaging. 2015;34(11):2394–403.

    Article  PubMed  Google Scholar 

  113. Deidda D, Karakatsanis NA, Robson PM, et al. Hybrid PET-MR list-mode kernelized expectation maximization reconstruction. Inverse Probl. 2019;35(4):044001.

    Article  Google Scholar 

  114. Meechai T, Tepmongkol S, Pluempitiwiriyawej C. Partial-volume effect correction in positron emission tomography brain scan image using super-resolution image reconstruction. Br J Radiol. 2015;88(1046):20140119.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  115. Song TA, Yang F, Chowdhury SR, et al. PET image deblurring and super-resolution with an MR-based joint entropy prior. IEEE Trans Comput Imaging. 2019;5(4):530–9.

    Article  PubMed  PubMed Central  Google Scholar 

  116. Su Y, Arbelaez AM, Benzinger TL, 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(1):115–21.

    Article  CAS  PubMed  Google Scholar 

  117. Ishii Y, Thamm T, Guo J, et al. Simultaneous phase-contrast MRI and PET for noninvasive quantification of cerebral blood flow and reactivity in healthy subjects and patients with cerebrovascular disease. J Magn Reson Imaging. 2020;51(1):183–94.

    Article  PubMed  Google Scholar 

  118. Fan AP, Khalighi MM, Guo J, et al. Identifying hypoperfusion in moyamoya disease with arterial spin labeling and an [(15)O]-water positron emission tomography/magnetic resonance imaging normative database. Stroke. 2019;50(2):373–80.

    Article  PubMed  PubMed Central  Google Scholar 

  119. Spann SM, Shao X, Wang DJ, et al. Robust single-shot acquisition of high resolution whole brain ASL images by combining time-dependent 2D CAPIRINHA sampling with spatio-temporal TGV reconstruction. NeuroImage. 2020;206:116337.

    Article  PubMed  Google Scholar 

  120. Hernandez-Garcia L, Nielsen JF, Noll DC. Improved sensitivity and temporal resolution in perfusion FMRI using velocity selective inversion ASL. Magn Reson Med. 2019;81(2):1004–15.

    Article  PubMed  Google Scholar 

  121. Simon AB, Buxton RB. Understanding the dynamic relationship between cerebral blood flow and the BOLD signal: implications for quantitative functional MRI. NeuroImage. 2015;116:158–67.

    Article  PubMed  Google Scholar 

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Authors and Affiliations

  1. Division of Nuclear Medicine, Department of Radiology, Stanford University, Stanford, CA, USA

    Farshad Moradi

  2. Department of Neurology, University of California, Davis, CA, USA

    Audrey P. Fan

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  1. Farshad Moradi
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  2. Audrey P. Fan
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Correspondence to Farshad Moradi .

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Editors and Affiliations

  1. Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, The Feinstein Institutes for Medical Research, Manhasset, NY, USA

    Ana M. Franceschi

  2. Stony Brook University Hospital, Stony Brook, NY, USA

    Dinko Franceschi

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Moradi, F., Fan, A.P. (2022). Perfusion PET and Cerebrovascular Reactivity with Acetazolamide Versus CO2 Challenge. In: Franceschi, A.M., Franceschi, D. (eds) Hybrid PET/MR Neuroimaging. Springer, Cham. https://doi.org/10.1007/978-3-030-82367-2_69

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  • DOI: https://doi.org/10.1007/978-3-030-82367-2_69

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