Skip to main content Accessibility help
×
Hostname: page-component-78c5997874-m6dg7 Total loading time: 0 Render date: 2024-11-19T14:44:02.024Z Has data issue: false hasContentIssue false

9 - MR perfusion imaging in neurodegenerative disease

from Section 2 - Clinical applications

Published online by Cambridge University Press:  05 May 2013

Peter B. Barker
Affiliation:
The Johns Hopkins University School of Medicine
Xavier Golay
Affiliation:
National Hospital for Neurology and Neurosurgery, London
Gregory Zaharchuk
Affiliation:
Stanford University Medical Center
Get access

Summary

Introduction

Neurodegenerative diseases, such as Alzheimer's disease (AD), frontotemporal lobar degeneration (FTLD), Lewy body dementia (DLB), and other forms of dementia, are characterized pathologically by slowly progressive dysfunction and loss of neurons. The risk for neurodegenerative diseases usually increases dramatically with advancing age, although familial variants of these conditions exist but occur at much lower frequency than the sporadic versions. Many of these diseases also share a common neuropathology associated with the malicious accumulation of misfolded protein aggregates in the brain [1]. On structural brain MRI, however, most neurodegenerative diseases do not show characteristic lesions that are readily identifiable by a radiologist's eye. Accordingly, the diagnostic value of structural MRI for neurodegenerative diseases has been limited (except to rule out the presence of other brain pathologies, such as tumors and stroke). Aside from brain structure, the importance of perfusion to maintain brain viability is well documented [2] and there is substantial evidence for alterations of brain perfusion in neurodegenerative diseases from radioactive labeled tracer studies using positron emission tomography (PET) or single-photon computed emission tomography (SPECT) [3]. There is also broad agreement that functional alterations in the brain generally precede neuronal/synaptic loss. Accordingly, perfusion imaging in general holds great promise for detecting neurodegeneration at an early stage, before advanced neuronal loss. Perfusion imaging should also be useful for the assessment of potentially disease-modifying treatments. Finally, by mapping brain perfusion researchers hope to learn more about the physiological and functional underpinnings of neurodegenerative diseases, thereby uncovering the biometric fingerprints of these devastating conditions.

Type
Chapter
Information
Clinical Perfusion MRI
Techniques and Applications
, pp. 164 - 178
Publisher: Cambridge University Press
Print publication year: 2013

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Matus, S, Glimcher, LH, Hetz, C.Protein folding stress in neurodegenerative diseases: a glimpse into the ER. Curr Opin Cell Biol 2011;23(2):239–52.CrossRefGoogle ScholarPubMed
Raichle, ME.Behind the scenes of functional brain imaging: a historical and physiological perspective. Proc Natl Acad Sci U S A 1998;95(3):765–72.CrossRefGoogle ScholarPubMed
Szymanski, P, Markowicz, M, Janik, A, Ciesielski, M, Mikiciuk-Olasik, E.Neuroimaging diagnosis in neurodegenerative diseases. Nucl Med Rev Cent East Eur. 2010;13(1):23–31.Google ScholarPubMed
Harris, GJ, Lewis, RF, Satlin, A, et al. Dynamic susceptibility contrast MR imaging of regional cerebral blood volume in Alzheimer disease: a promising alternative to nuclear medicine. AJNR Am J Neuroradiol 1998;19(9):1727–32.Google ScholarPubMed
Agosta, F, Pievani, M, Geroldi, C, et al. Resting state fMRI in Alzheimer's disease: beyond the default mode network. Neurobiol Aging 2012;33(8):1564–78. Epub 2011/08/03.CrossRefGoogle ScholarPubMed
Ferri, CP, Prince, M, Brayne, C, et al. Global prevalence of dementia: a Delphi consensus study. Lancet 2005;366(9503):2112–17.CrossRefGoogle ScholarPubMed
Sandson, TA, O'Connor, M, Sperling, RA, Edelman, RR, Warach, S.Noninvasive perfusion MRI in Alzheimer's disease: a preliminary report. Neurology 1996;47(5):1339–42.CrossRefGoogle ScholarPubMed
Alsop, DC, Detre, JA, Grossman, M.Assessment of cerebral blood flow in Alzheimer's disease by spin-labeled magnetic resonance imaging. Ann Neurol 2000;47(1):93–100.3.0.CO;2-8>CrossRefGoogle ScholarPubMed
Johnson, NA, Jahng, GH, Weiner, MW, et al. Pattern of cerebral hypoperfusion in Alzheimer disease and mild cognitive impairment measured with arterial spin-labeling MR imaging: initial experience. Radiology 2005;234(3):851–9.CrossRefGoogle ScholarPubMed
Alsop, DC, Casement, M, de Bazelaire, C, Fong, T, Press, DZ.Hippocampal hyperperfusion in Alzheimer's disease. Neuroimage 2008;42(4):1267–74.CrossRefGoogle ScholarPubMed
Dai, W, Lopez, OL, Carmichael, OT, et al. Mild cognitive impairment and alzheimer disease: patterns of altered cerebral blood flow at MR imaging. Radiology 2009;250(3):856–66.CrossRefGoogle ScholarPubMed
Asllani, I, Habeck, C, Scarmeas, N, et al. Multivariate and univariate analysis of continuous arterial spin labeling perfusion MRI in Alzheimer's disease. J Cereb Blood Flow Metab 2008;28(4):725–36.CrossRefGoogle ScholarPubMed
Hu, WT, Wang, Z, Lee, VM, et al. Distinct cerebral perfusion patterns in FTLD and AD. Neurology 2010;75(10):881–8.CrossRefGoogle ScholarPubMed
Braak, H, Braak, E.Neuropathological staging of Alzheimer-related changes. Acta Neuropathol 1991;82(4):239–59.CrossRefGoogle Scholar
Sperling, R.Functional MRI studies of associative encoding in normal aging, mild cognitive impairment, and Alzheimer's disease. Ann N Y Acad Sci 2007;1097:146–55.CrossRefGoogle ScholarPubMed
Yoshiura, T, Hiwatashi, A, Yamashita, K, et al. Simultaneous measurement of arterial transit time, arterial blood volume, and cerebral blood flow using arterial spin-labeling in patients with Alzheimer disease. AJNR Am J Neuroradiol 2009;30(7):1388–93.CrossRefGoogle ScholarPubMed
Liu, Y, Rosen, H, Miller, BL, Weiner, MW, Schuff, N, editors. Cerebral Blood Perfusion Dynamics in Alzheimer's Disease and Mild Cognitive Impairment Using Discrete Modeling of Arterial Spin Labeling MRI. Proc Intl Soc Magn Reson Med, Montreal, Canada, 2011.
Scheff, SW, Price, DA, Schmitt, FA, Mufson, EJ.Hippocampal synaptic loss in early Alzheimer's disease and mild cognitive impairment. Neurobiol Aging 2006;27(10):1372–84.CrossRefGoogle ScholarPubMed
Petersen, RC, Doody, R, Kurz, A, et al. Current concepts in mild cognitive impairment. Arch Neurol 2001;58(12):1985–92.CrossRefGoogle ScholarPubMed
Geslani, DM, Tierney, MC, Herrmann, N, Szalai, JP.Mild cognitive impairment: an operational definition and its conversion rate to Alzheimer's disease. Dement Geriatr Cogn Disord 2005;19(5–6):383–9.CrossRefGoogle ScholarPubMed
Chao, LL, Pa, J, Duarte, A, et al. Patterns of cerebral hypoperfusion in amnestic and dysexecutive MCI. Alzheimer Dis Assoc Disord 2009;23(3):245–52.CrossRefGoogle ScholarPubMed
Young, K, Du, AT, Kramer, J, et al. Patterns of structural complexity in Alzheimer's disease and frontotemporal dementia. Hum Brain Mapp 2009;30(5):1667–77.CrossRefGoogle ScholarPubMed
Rosen, HJ, Allison, SC, Schauer, GF, et al. Neuroanatomical correlates of behavioural disorders in dementia. Brain 2005;128(Pt 11):2612–25.CrossRefGoogle ScholarPubMed
Laforce, R, Buteau, JP, Paquet, N, et al. The value of PET in mild cognitive impairment, typical and atypical/unclear dementias: a retrospective memory clinic study. Am J Alzheimers Dis Other Demen 2010;25(4):324–32.CrossRefGoogle ScholarPubMed
Du, AT, Jahng, GH, Hayasaka, S, et al. Hypoperfusion in frontotemporal dementia and Alzheimer disease by arterial spin labeling MRI. Neurology 2006;67(7):1215–20.CrossRefGoogle ScholarPubMed
Zhang, Y, Schuff, N, Ching, C, et al. Joint assessment of structural, perfusion, and diffusion MRI in Alzheimer's disease and frontotemporal dementia. Int J Alzheimers Dis 2011;2011:546–871.Google ScholarPubMed
Kamagata, K, Motoi, Y, Hori, M, et al. Posterior hypoperfusion in Parkinson's disease with and without dementia measured with arterial spin labeling MRI. J Magn Reson Imaging 2011;33(4):803–7.CrossRefGoogle ScholarPubMed
Fong, T, Inouye, S, Dai, W, Press, D, Alsop, D.Association cortex hypoperfusion in mild dementia with Lewy bodies: a potential indicator of cholinergic dysfunction?Brain Imaging Behav 2011;5(1):25–35.CrossRefGoogle ScholarPubMed
Schuff, N, Matsumoto, S, Kmiecik, J, et al. Cerebral blood flow in ischemic vascular dementia and Alzheimer's disease, measured by arterial spin-labeling magnetic resonance imaging. Alzheimers Dement 2009;5(6):454–62.CrossRefGoogle ScholarPubMed
Deutsch, G, Tweedy, JR.Cerebral blood flow in severity-matched Alzheimer and multi-infarct patients. Neurology 1987;37(3):431–8.CrossRefGoogle ScholarPubMed
Tohgi, H, Yonezawa, H, Takahashi, S, et al. Cerebral blood flow and oxygen metabolism in senile dementia of Alzheimer's type and vascular dementia with deep white matter changes. Neuroradiology 1998;40(3):131–7.CrossRefGoogle ScholarPubMed
Nagata, K, Maruya, H, Yuya, H, et al. Can PET data differentiate Alzheimer's disease from vascular dementia?Ann N Y Acad Sci 2000;903:252–61.CrossRefGoogle ScholarPubMed
Hanyu, H, Shimuzu, S, Tanaka, Y, et al. Cerebral blood flow patterns in Binswanger's disease: a SPECT study using three-dimensional stereotactic surface projections. J Neurol Sci 2004;220(1–2):79–84.CrossRefGoogle ScholarPubMed
Shim, YS, Yang, DW, Kim, BS, Shon, YM, Chung, YA.Comparison of regional cerebral blood flow in two subsets of subcortical ischemic vascular dementia: statistical parametric mapping analysis of SPECT. J Neurol Sci 2006;250(1–2):85–91.CrossRefGoogle ScholarPubMed
Tullberg, M, Fletcher, E, DeCarli, C, et al. White matter lesions impair frontal lobe function regardless of their location. Neurology 2004;63(2):246–53.CrossRefGoogle ScholarPubMed
Kraut, MA, Beason-Held, LL, Elkins, WD, Resnick, SM.The impact of magnetic resonance imaging-detected white matter hyperintensities on longitudinal changes in regional cerebral blood flow. J Cereb Blood Flow Metab 2008;28(1):190–7.CrossRefGoogle ScholarPubMed
Hayasaka, S, Du, AT, Duarte, A, et al. A non-parametric approach for co-analysis of multi-modal brain imaging data: application to Alzheimer's disease. Neuroimage 2006;30(3):768–79.CrossRefGoogle ScholarPubMed
Matsuda, H, Kitayama, N, Ohnishi, T, et al. Longitudinal evaluation of both morphologic and functional changes in the same individuals with Alzheimer's disease. J Nucl Med 2002;43(3):304–11.Google ScholarPubMed
Shimizu, S, Zhang, Y, Laxamana, J, et al. Concordance and discordance between brain perfusion and atrophy in frontotemporal dementia. Brain Imaging Behav 2010;4(1):46–54.CrossRefGoogle ScholarPubMed
Tosun, D, Mojabi, P, Weiner, MW, Schuff, N.Joint analysis of structural and perfusion MRI for cognitive assessment and classification of Alzheimer's disease and normal aging. Neuroimage 2010;52(1):186–97.CrossRefGoogle ScholarPubMed
Tosun, D, Schuff, N, Weiner, M.An integrated multimodality MR brain imaging study: gray matter tissue loss mediates the association between cerebral hypoperfusion and Alzheimer's disease. Conf Proc IEEE Eng Med Biol Soc 2009;1:6981–4.Google Scholar
Dai, W, Garcia, D, de Bazelaire, C, Alsop, DC.Continuous flow driven inversion for arterial spin labeling using pulsed radiofrequency and gradient fields. Magn Reson Med 2008;60(6):1488–97.CrossRefGoogle Scholar
Nezamzadeh, M, Matson, GB, Young, K, Weiner, MW, Schuff, N.Improved pseudo-continuous arterial spin labeling for mapping brain perfusion. J Magn Reson Imaging 2010;31(6):1419–27.CrossRefGoogle ScholarPubMed
Kornak, J, Young, K, Schuff, N, et al. K-Bayes reconstruction for perfusion MRI. I: concepts and application. J Digit Imaging 2009;23(3):277–86.CrossRefGoogle ScholarPubMed
Habeck, C, Rakitin, BC, Moeller, J, et al. An event-related fMRI study of the neural networks underlying the encoding, maintenance, and retrieval phase in a delayed-match-to-sample task. Brain Res Cogn Brain Res 2005;23(2–3):207–20.CrossRefGoogle Scholar
Davatzikos, C, Resnick, SM, Wu, X, Parmpi, P, Clark, CM.Individual patient diagnosis of AD and FTD via high-dimensional pattern classification of MRI. Neuroimage 2008;41(4):1220–7.CrossRefGoogle ScholarPubMed
Stonnington, CM, Chu, C, Kloppel, S, et al. Predicting clinical scores from magnetic resonance scans in Alzheimer's disease. Neuroimage 2010;51(4):1405–13.CrossRefGoogle ScholarPubMed

Save book to Kindle

To save this book to your Kindle, first ensure [email protected] is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Available formats
×

Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

Available formats
×