15O-PET による脳循環測定:他モダリティ評価のためのツールとして
酸素15 標識ガスおよび標識水を用いたPET 測定(15O-PET)により,脳血流量(CBF)を含む主要な脳循環パラメータが高精度に,しかも1 回の検査で取得可能である.脳血管障害の病態評価における臨床的有用性が広く知られているが,近年では他モダリティによる脳循環測定法開発の評価ツールとしての役割も大きくなってきた.CT またはMR 造影剤の急速静注によるbolus-tracking 法や,最近急速に普及した動脈血スピンラベリングMRI 法が臨床利用されているが,CBF 測定手法としての妥当性は明確でない.これらの手法評価には,15O-PETによる脳循環測定との直接比較が非常に有効である.15...
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Published in | 脳循環代謝(日本脳循環代謝学会機関誌) Vol. 30; no. 1; pp. 53 - 58 |
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Format | Journal Article |
Language | Japanese |
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日本脳循環代謝学会
2018
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ISSN | 0915-9401 2188-7519 |
DOI | 10.16977/cbfm.30.1_53 |
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Abstract | 酸素15 標識ガスおよび標識水を用いたPET 測定(15O-PET)により,脳血流量(CBF)を含む主要な脳循環パラメータが高精度に,しかも1 回の検査で取得可能である.脳血管障害の病態評価における臨床的有用性が広く知られているが,近年では他モダリティによる脳循環測定法開発の評価ツールとしての役割も大きくなってきた.CT またはMR 造影剤の急速静注によるbolus-tracking 法や,最近急速に普及した動脈血スピンラベリングMRI 法が臨床利用されているが,CBF 測定手法としての妥当性は明確でない.これらの手法評価には,15O-PETによる脳循環測定との直接比較が非常に有効である.15O-PET のさらなる応用促進のため,検査法の短時間化,簡略化を目指した研究が期待される. |
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AbstractList | 酸素15 標識ガスおよび標識水を用いたPET 測定(15O-PET)により,脳血流量(CBF)を含む主要な脳循環パラメータが高精度に,しかも1 回の検査で取得可能である.脳血管障害の病態評価における臨床的有用性が広く知られているが,近年では他モダリティによる脳循環測定法開発の評価ツールとしての役割も大きくなってきた.CT またはMR 造影剤の急速静注によるbolus-tracking 法や,最近急速に普及した動脈血スピンラベリングMRI 法が臨床利用されているが,CBF 測定手法としての妥当性は明確でない.これらの手法評価には,15O-PETによる脳循環測定との直接比較が非常に有効である.15O-PET のさらなる応用促進のため,検査法の短時間化,簡略化を目指した研究が期待される. |
Author | 茨木, 正信 |
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References | 6) Okazawa H, Kudo T: Clinical impact of hemodynamic parameter measurement for cerebrovascular disease using positron emission tomography and 15O-labeled tracers. Ann Nucl Med 23: 217–227, 2009 26) Su Y, Arbelaez AM, Benzinger TL, Snyder AZ, Vlassenko AG, Mintun MA, Raichle ME: Noninvasive estimation of the arterial input function in positron emission tomography imaging of cerebral blood flow. J Cereb Blood Flow Metab 33: 115–121, 2013 24) Iguchi S, Hori Y, Moriguchi T, Morita N, Yamamoto A, Koshino K, Kawashima H, Zeniya T, Enmi J, Iida H: Verification of a semi-automated MRI-guided technique for non-invasive determination of the arterial input function in 15O-labeled gaseous PET. Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment 702: 111–113, 2013 1) Frackowiak RS, Lenzi GL, Jones T, Heather JD: Quantitative measurement of regional cerebral blood flow and oxygen metabolism in man using 15O and positron emission tomography: theory, procedure, and normal values. J Comput Assist Tomogr 4: 727–736, 1980 23) Robertson AD, Matta G, Basile VS, Black SE, Macgowan CK, Detre JA, MacIntosh BJ: Temporal and spatial variances in arterial spin-labeling are inversely related to large-artery blood velocity. AJNR Am J Neuroradiol 38: 1555–1561, 2017 25) Kudomi N, Maeda Y, Yamamoto Y, Nishiyama Y: Reconstruction of an input function from a dynamic PET water image using multiple tissue curves. Phys Med Biol 61: 5755–5767, 2016 7) Ibaraki M, Ohmura T, Matsubara K, Kinoshita T: Reliability of CT perfusion-derived CBF in relation to hemodynamic compromise in patients with cerebrovascular steno-occlusive disease: a comparative study with 15O PET. J Cereb Blood Flow Metab 35: 1280–1288, 2015 20) Amukotuwa SA, Yu C, Zaharchuk G: 3D Pseudocontinuous arterial spin labeling in routine clinical practice: A review of clinically significant artifacts. J Magn Reson Imaging 43: 11–27, 2016 2) Raichle ME, Martin WR, Herscovitch P, Mintun MA, Markham J: Brain blood flow measured with intravenous H215O. II. Implementation and validation. J Nucl Med 24: 790–798, 1983 9) MacDonald ME, Smith MR, Frayne R: Deconvolution with simple extrapolation for improved cerebral blood flow measurement in dynamic susceptibility contrast magnetic resonance imaging during acute ischemic stroke. Magn Reson Imaging 29: 620–629, 2011 19) Alsop DC, Detre JA, Golay X, Günther M, Hendrikse J, Hernandez-Garcia L, Lu H, MacIntosh BJ, Parkes LM, Smits M, van Osch MJ, Wang DJ, Wong EC, Zaharchuk G: 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 73: 102–116, 2015 8) Ibaraki M, Nakamura K, Toyoshima H, Takahashi K, Matsubara K, Umetsu A, Pfeuffer J, Kuribayashi H, Kinoshita T: Spatial coefficient of variation in pseudo-continuous arterial spin labeling cerebral blood flow images as a hemodynamic measure for cerebrovascular steno-occlusive disease: a comparative 15O positron emission tomography study. J Cereb Blood Flow Metab 2018. doi: 10.1177/0271678X18781667 [Epub ahead of Print] 17) Mehndiratta A, MacIntosh BJ, Crane DE, Payne SJ, Chappell MA: A control point interpolation method for the non-parametric quantification of cerebral haemodynamics from dynamic susceptibility contrast MRI. Neuroimage 64: 560–570, 2013 13) Wu O, Østergaard L, Weisskoff RM, Benner T, Rosen BR, Sorensen AG: Tracer arrival timing-insensitive technique for estimating flow in MR perfusion-weighted imaging using singular value decomposition with a block-circulant deconvolution matrix. Magn Reson Med 50: 164–174, 2003 4) Ito H, Kanno I, Fukuda H: Human cerebral circulation: positron emission tomography studies. Ann Nucl Med 19: 65–74, 2005 3) Mintun MA, Raichle ME, Martin WR, Herscovitch P: Brain oxygen utilization measured with O-15 radiotracers and positron emission tomography. J Nucl Med 25: 177–187, 1984 5) Powers WJ, Grubb RL, Raichle ME: Physiological responses to focal cerebral ischemia in humans. Ann Neurol 16: 546–552, 1984 16) Boutelier T, Kudo K, Pautot F, Sasaki M: Bayesian hemodynamic parameter estimation by bolus tracking perfusion weighted imaging. IEEE Trans Med Imaging 31: 1381–1395, 2012 14) Smith MR, Lu H, Trochet S, Frayne R: Removing the effect of SVD algorithmic artifacts present in quantitative MR perfusion studies. Magn Reson Med 51: 631–634, 2004 15) Ibaraki M, Shimosegawa E, Toyoshima H, Takahashi K, Miura S, Kanno I: Tracer delay correction of cerebral blood flow with dynamic susceptibility contrast-enhanced MRI. J Cereb Blood Flow Metab 25: 378–390, 2005 18) Detre JA, Rao H, Wang DJ, Chen YF, Wang Z: Applications of arterial spin labeled MRI in the brain. J Magn Reson Imaging 35: 1026–1037, 2012 12) Østergaard L, Weisskoff RM, Chesler DA, Gyldensted C, Rosen BR: High resolution measurement of cerebral blood flow using intravascular tracer bolus passages. Part I: Mathematical approach and statistical analysis. Magn Reson Med 36: 715–725, 1996 22) Mutsaerts HJ, Petr J, Václavů L, van Dalen JW, Robertson AD, Caan MW, Masellis M, Nederveen AJ, Richard E, MacIntosh BJ: The spatial coefficient of variation in arterial spin labeling cerebral blood flow images. J Cereb Blood Flow Metab 37: 3184–3192, 2017 29) Koopman T, Yaqub M, Heijtel DF, Nederveen AJ, van Berckel BN, Lammertsma AA, Boellaard R: Semi-quantitative cerebral blood flow parameters derived from non-invasive [15O]H2O PET studies. J Cereb Blood Flow Metab, 2017 doi: 10.1177/0271678X17730654 [Epub ahead of Print] 27) Khalighi MM, Deller TW, Fan AP, Gulaka PK, Shen B, Singh P, Park JH, Chin FT, Zaharchuk G: Image-derived input function estimation on a TOF-enabled PET/MR for cerebral blood flow mapping. J Cereb Blood Flow Metab 38: 126–135, 2018 28) Islam MM, Tsujikawa T, Mori T, Kiyono Y, Okazawa H: Estimation of arterial input by a noninvasive image derived method in brain H215O PET study: confirmation of arterial location using MR angiography. Phys Med Biol 62: 4514–4524, 2017 10) Salluzzi M, Frayne R, Smith MR: An alternative viewpoint of the similarities and differences of SVD and FT deconvolution algorithms used for quantitative MR perfusion studies. Magn Reson Imaging 23: 481–492, 2005 21) Zaharchuk G, Bammer R, Straka M, Shankaranarayan A, Alsop DC, Fischbein NJ, Atlas SW, Moseley ME: Arterial spin-label imaging in patients with normal bolus perfusion-weighted MR imaging findings: pilot identification of the borderzone sign. Radiology 252: 797–807, 2009 11) Calamante F, Gadian DG, Connelly A: Delay and dispersion effects in dynamic susceptibility contrast MRI: simulations using singular value decomposition. Magn Reson Med 44: 466–473, 2000 |
References_xml | – reference: 2) Raichle ME, Martin WR, Herscovitch P, Mintun MA, Markham J: Brain blood flow measured with intravenous H215O. II. Implementation and validation. J Nucl Med 24: 790–798, 1983 – reference: 24) Iguchi S, Hori Y, Moriguchi T, Morita N, Yamamoto A, Koshino K, Kawashima H, Zeniya T, Enmi J, Iida H: Verification of a semi-automated MRI-guided technique for non-invasive determination of the arterial input function in 15O-labeled gaseous PET. Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment 702: 111–113, 2013 – reference: 3) Mintun MA, Raichle ME, Martin WR, Herscovitch P: Brain oxygen utilization measured with O-15 radiotracers and positron emission tomography. J Nucl Med 25: 177–187, 1984 – reference: 22) Mutsaerts HJ, Petr J, Václavů L, van Dalen JW, Robertson AD, Caan MW, Masellis M, Nederveen AJ, Richard E, MacIntosh BJ: The spatial coefficient of variation in arterial spin labeling cerebral blood flow images. J Cereb Blood Flow Metab 37: 3184–3192, 2017 – reference: 6) Okazawa H, Kudo T: Clinical impact of hemodynamic parameter measurement for cerebrovascular disease using positron emission tomography and 15O-labeled tracers. Ann Nucl Med 23: 217–227, 2009 – reference: 10) Salluzzi M, Frayne R, Smith MR: An alternative viewpoint of the similarities and differences of SVD and FT deconvolution algorithms used for quantitative MR perfusion studies. Magn Reson Imaging 23: 481–492, 2005 – reference: 29) Koopman T, Yaqub M, Heijtel DF, Nederveen AJ, van Berckel BN, Lammertsma AA, Boellaard R: Semi-quantitative cerebral blood flow parameters derived from non-invasive [15O]H2O PET studies. J Cereb Blood Flow Metab, 2017 doi: 10.1177/0271678X17730654 [Epub ahead of Print] – reference: 17) Mehndiratta A, MacIntosh BJ, Crane DE, Payne SJ, Chappell MA: A control point interpolation method for the non-parametric quantification of cerebral haemodynamics from dynamic susceptibility contrast MRI. Neuroimage 64: 560–570, 2013 – reference: 11) Calamante F, Gadian DG, Connelly A: Delay and dispersion effects in dynamic susceptibility contrast MRI: simulations using singular value decomposition. Magn Reson Med 44: 466–473, 2000 – reference: 27) Khalighi MM, Deller TW, Fan AP, Gulaka PK, Shen B, Singh P, Park JH, Chin FT, Zaharchuk G: Image-derived input function estimation on a TOF-enabled PET/MR for cerebral blood flow mapping. J Cereb Blood Flow Metab 38: 126–135, 2018 – reference: 7) Ibaraki M, Ohmura T, Matsubara K, Kinoshita T: Reliability of CT perfusion-derived CBF in relation to hemodynamic compromise in patients with cerebrovascular steno-occlusive disease: a comparative study with 15O PET. J Cereb Blood Flow Metab 35: 1280–1288, 2015 – reference: 14) Smith MR, Lu H, Trochet S, Frayne R: Removing the effect of SVD algorithmic artifacts present in quantitative MR perfusion studies. Magn Reson Med 51: 631–634, 2004 – reference: 20) Amukotuwa SA, Yu C, Zaharchuk G: 3D Pseudocontinuous arterial spin labeling in routine clinical practice: A review of clinically significant artifacts. J Magn Reson Imaging 43: 11–27, 2016 – reference: 8) Ibaraki M, Nakamura K, Toyoshima H, Takahashi K, Matsubara K, Umetsu A, Pfeuffer J, Kuribayashi H, Kinoshita T: Spatial coefficient of variation in pseudo-continuous arterial spin labeling cerebral blood flow images as a hemodynamic measure for cerebrovascular steno-occlusive disease: a comparative 15O positron emission tomography study. J Cereb Blood Flow Metab 2018. doi: 10.1177/0271678X18781667 [Epub ahead of Print] – reference: 5) Powers WJ, Grubb RL, Raichle ME: Physiological responses to focal cerebral ischemia in humans. Ann Neurol 16: 546–552, 1984 – reference: 25) Kudomi N, Maeda Y, Yamamoto Y, Nishiyama Y: Reconstruction of an input function from a dynamic PET water image using multiple tissue curves. Phys Med Biol 61: 5755–5767, 2016 – reference: 19) Alsop DC, Detre JA, Golay X, Günther M, Hendrikse J, Hernandez-Garcia L, Lu H, MacIntosh BJ, Parkes LM, Smits M, van Osch MJ, Wang DJ, Wong EC, Zaharchuk G: 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 73: 102–116, 2015 – reference: 13) Wu O, Østergaard L, Weisskoff RM, Benner T, Rosen BR, Sorensen AG: Tracer arrival timing-insensitive technique for estimating flow in MR perfusion-weighted imaging using singular value decomposition with a block-circulant deconvolution matrix. Magn Reson Med 50: 164–174, 2003 – reference: 16) Boutelier T, Kudo K, Pautot F, Sasaki M: Bayesian hemodynamic parameter estimation by bolus tracking perfusion weighted imaging. IEEE Trans Med Imaging 31: 1381–1395, 2012 – reference: 12) Østergaard L, Weisskoff RM, Chesler DA, Gyldensted C, Rosen BR: High resolution measurement of cerebral blood flow using intravascular tracer bolus passages. Part I: Mathematical approach and statistical analysis. Magn Reson Med 36: 715–725, 1996 – reference: 15) Ibaraki M, Shimosegawa E, Toyoshima H, Takahashi K, Miura S, Kanno I: Tracer delay correction of cerebral blood flow with dynamic susceptibility contrast-enhanced MRI. J Cereb Blood Flow Metab 25: 378–390, 2005 – reference: 4) Ito H, Kanno I, Fukuda H: Human cerebral circulation: positron emission tomography studies. Ann Nucl Med 19: 65–74, 2005 – reference: 18) Detre JA, Rao H, Wang DJ, Chen YF, Wang Z: Applications of arterial spin labeled MRI in the brain. J Magn Reson Imaging 35: 1026–1037, 2012 – reference: 1) Frackowiak RS, Lenzi GL, Jones T, Heather JD: Quantitative measurement of regional cerebral blood flow and oxygen metabolism in man using 15O and positron emission tomography: theory, procedure, and normal values. J Comput Assist Tomogr 4: 727–736, 1980 – reference: 26) Su Y, Arbelaez AM, Benzinger TL, Snyder AZ, Vlassenko AG, Mintun MA, Raichle ME: Noninvasive estimation of the arterial input function in positron emission tomography imaging of cerebral blood flow. J Cereb Blood Flow Metab 33: 115–121, 2013 – reference: 23) Robertson AD, Matta G, Basile VS, Black SE, Macgowan CK, Detre JA, MacIntosh BJ: Temporal and spatial variances in arterial spin-labeling are inversely related to large-artery blood velocity. AJNR Am J Neuroradiol 38: 1555–1561, 2017 – reference: 21) Zaharchuk G, Bammer R, Straka M, Shankaranarayan A, Alsop DC, Fischbein NJ, Atlas SW, Moseley ME: Arterial spin-label imaging in patients with normal bolus perfusion-weighted MR imaging findings: pilot identification of the borderzone sign. Radiology 252: 797–807, 2009 – reference: 9) MacDonald ME, Smith MR, Frayne R: Deconvolution with simple extrapolation for improved cerebral blood flow measurement in dynamic susceptibility contrast magnetic resonance imaging during acute ischemic stroke. Magn Reson Imaging 29: 620–629, 2011 – reference: 28) Islam MM, Tsujikawa T, Mori T, Kiyono Y, Okazawa H: Estimation of arterial input by a noninvasive image derived method in brain H215O PET study: confirmation of arterial location using MR angiography. Phys Med Biol 62: 4514–4524, 2017 |
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Snippet | 酸素15 標識ガスおよび標識水を用いたPET 測定(15O-PET)により,脳血流量(CBF)を含む主要な脳循環パラメータが高精度に,しかも1 回の検査で取得可能である.脳血管障... |
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SubjectTerms | ポジトロン断層撮影法 脳血流量 酸素15 酸素代謝 |
Title | 15O-PET による脳循環測定:他モダリティ評価のためのツールとして |
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