Cited by 189Advanced MRI Techniques and ApplicationsDementia and Cognitive Impairment ResearchFunctional Brain Connectivity Studies

The DOI matches its Crossref record; 55 of the 57 references it cites were found in a registry or an index.

Comparison of regional cerebral blood flow and glucose metabolism in the normal brain: effect of aging

Bentourkia, M’hamed, Bol, Anne, Ivanoiu, Adrian, Labar, Daniel, Sibomana, Mérence, Coppens, Ann, Michel, Christian, Cosnard, Guy, De Volder, Anne G·2000·Journal of the Neurological Sciences

DOI 10.1016/s0022-510x(00)00396-8

Open this paper in CoChat — free account

Abstract

The regional cerebral blood flow (rCBF) and metabolic rate for glucose (rCMRGlc) are associated with functional activity of the neural cells. The present work reports a comparison study between rCBF and rCMRGlc in a normal population as a function of age. 10 young (25.9+/-5.6 years) and 10 old (65.4+/-6.1 years) volunteers were similarly studied at rest. In each subject, rCBF and rCMRGlc were measured in sequence, during the same session. Both rCBF and rCMRGlc values were found to decrease from young (mean rCBF=43.7 ml/100 g per min; mean rCMRGlc=40.6 micromol/100 g per min) to old age (mean rCBF=37.3 ml/100 g per min; mean rCMRGlc=35.2 micromol/100 g per min), resulting in a drop over 40 years of 14.8% (0.37%/year) and 13.3% (0.34%/year), respectively. On a regional basis, the frontal and the visual cortices were observed to have, respectively, the highest and the lowest reduction in rCBF, while, for rCMRGlc, these extremes were observed in striatum and cerebellum. Despite these differences, the ratio of rCBF to rCMRGlc was found to have a similar behavior in all brain regions for young and old subjects as shown by a correlation coefficient of 88%. This comparative study indicates a decline in rCBF and rCMRGlc values and a coupling between CBF and CMRGlc as a function of age.

Integrity signals

Registry

Crossref · 10.1016/s0022-510x(00)00396-8

Cites

55 of 55 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

This paper’s full text isn’t openly available, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Co-Planar Stereotaxic Atlas of the Human Brain
Talairach, J., & Tournoux, P. (1988) · Medical Entomology and Zoology · Cited by 11,798
Co-planar stereotaxic atlas of the human brain
Laitinen, L. (1989) · Clinical Neurology and Neurosurgery · doi:10.1016/0303-8467(89)90128-5 · Cited by 7,565
Minuit - a system for function minimization and analysis of the parameter errors and correlations
James, F., & Roos, M. (1975) · Computer Physics Communications · doi:10.1016/0010-4655(75)90039-9 · Cited by 3,274
Synaptic density in human frontal cortex —Developmental changes and effects of aging
Peter R., H. (1979) · Brain Research · doi:10.1016/0006-8993(79)90349-4 · Cited by 2,645
Tomographic measurement of local cerebral glucose metabolic rate in humans with (F‐18)2‐fluoro‐2‐deoxy‐D‐glucose: Validation of method
Phelps, M. E., Huang, S. C., Hoffman, E. J., Selin, C. E., Sokoloff, L., & Kuhl, D. E. (1979) · Annals of Neurology · doi:10.1002/ana.410060502 · Cited by 2,417
Quantitative Measurement of Regional Cerebral Blood Flow and Oxygen Metabolism in Man Using 15O and Positron Emission Tomography
Frackowiak, R. S. J., Lenzi, G.-L., Jones, T., & Heather, J. D. (1980) · Journal of Computer Assisted Tomography · doi:10.1097/00004728-198012000-00001 · Cited by 1,241
CEREBRAL BLOOD FLOW, BLOOD VOLUME AND OXYGEN UTILIZATION
Leenders, K. L., Perani, D., Lammertsma, A. A., Heather, J. D., Buckingham, P. D., Jones, T., Healy, M. J. R., GIBBS, J. M., WISE, R. J. S., Hatazawa, J., et al. (1990) · Brain · doi:10.1093/brain/113.1.27 · Cited by 1,094
Brain blood flow measured with intravenous H2(15)O. II. Implementation and validation.
Raichle, M. E., Martin, W. R. W., Herscovitch, P., Mintun, M. A., & Markham, J. (1983) · PubMed · Cited by 1,015
Neocortical cell counts in normal human adult aging
Terry, R. D., DeTeresa, R. M., & Hansen, L. A. (1987) · Annals of Neurology · doi:10.1002/ana.410210603 · Cited by 686
The ECAT EXACT HR
Wienhard, K., Dahlbom, M. L., Eriksson, L., Michel, C. J., Bruckbauer, T., Pietrzyk, U., & Heiss, W. (1994) · Journal of Computer Assisted Tomography · doi:10.1097/00004728-199401000-00023 · Cited by 561
Self-citation

Show all 57 references

Research works printed but not linked: 2

Raichle, 1983, Brain blood flow measured with intravenous H215O. II. Implementation and validation, J Nucl Med, 24, 790
Lammertsma, 1981, Accuracy of the oxygen-15 steady state technique for measuring rCBF and rCMRO2: tracer modelling, statistics and spatial sampling, J Cereb Blood Flow Metab, 1, S1

Sorted by citations

Pathophysiology of Sleep Apnea
Dempsey, J. A., Veasey, S. C., Morgan, B. J., & O'Donnell, C. P. (2010) · Physiological Reviews · doi:10.1152/physrev.00043.2008 · Cited by 2,243
Alterations in the BOLD fMRI signal with ageing and disease: a challenge for neuroimaging
D’Esposito, M., Deouell, L. Y., & Gazzaley, A. H. (2003) · Nature reviews. Neuroscience · doi:10.1038/nrn1246 · Cited by 852
Aging, sexual dimorphism, and hemispheric asymmetry of the cerebral cortex: replicability of regional differences in volume
Raz, N., Gunning‐Dixon, F. M., Head, D. M., Rodrigue, K. M., Williamson, A. L., & Acker, J. D. (2003) · Neurobiology of Aging · doi:10.1016/s0197-4580(03)00118-0 · Cited by 748
Differential vulnerability of anterior white matter in nondemented aging with minimal acceleration in dementia of the Alzheimer type: Evidence from diffusion tensor imaging.
Head, D. (2004) · Cerebral Cortex · doi:10.1093/cercor/bhh003 · Cited by 645
Brain fuel metabolism, aging, and Alzheimer’s disease
Cunnane, S. C., Nugent, S., Roy, M., Courchesne‐Loyer, A., Croteau, É., Tremblay, S., Castellano, A., Pifferi, F., Bocti, C., Paquet, N., et al. (2010) · Nutrition · doi:10.1016/j.nut.2010.07.021 · Cited by 633
Self-citation
Elevated gene expression levels distinguish human from non-human primate brains
Cáceres, M., Lachuer, J., Zapala, M. A., Redmond, J. C., Kudo, L., Geschwind, D. H., Lockhart, D. J., Preuss, T. M., & Barlow, C. (2003) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2135499100 · Cited by 491
Normal cerebral perfusion measurements using arterial spin labeling: Reproducibility, stability, and age and gender effects
Parkes, L. M., Rashid, W., Chard, D., & Tofts, P. S. (2004) · Magnetic Resonance in Medicine · doi:10.1002/mrm.20023 · Cited by 450
Cardiovascular Risk Factors Promote Brain Hypoperfusion Leading to Cognitive Decline and Dementia
de la Torre, J. C. (2012) · Cardiovascular Psychiatry and Neurology · doi:10.1155/2012/367516 · Cited by 459
Cellular metabolic and autophagic pathways: Traffic control by redox signaling
Dodson, M. B., Darley-Usmar, V. M., & Zhang, J. (2013) · Free Radical Biology and Medicine · doi:10.1016/j.freeradbiomed.2013.05.014 · Cited by 333
The microvascular frontal-subcortical syndrome of aging
Pugh, K. R. (2002) · Neurobiology of Aging · doi:10.1016/s0197-4580(01)00319-0 · Cited by 233
Microvascular plasticity in aging
Riddle, D. R., Sonntag, W. E., & Lichtenwalner, R. J. (2003) · Ageing Research Reviews · doi:10.1016/s1568-1637(02)00064-8 · Cited by 227
Effects of aging on cerebral blood flow, oxygen metabolism, and blood oxygenation level dependent responses to visual stimulation
Ances, B. M., Liang, C. L., Leontiev, O., Perthen, J. E., Fleisher, A., Lansing, A. E., & Buxton, R. B. (2008) · Human Brain Mapping · doi:10.1002/hbm.20574 · Cited by 216
Hormonal and Metabolic Changes of Aging and the Influence of Lifestyle Modifications
Pataky, M. W., Young, W. F., & Nair, K. S. (2021) · Mayo Clinic Proceedings · doi:10.1016/j.mayocp.2020.07.033 · Cited by 207
Central Sleep Apnea
Javaheri, S., & Dempsey, J. A. (2012) · Comprehensive physiology · doi:10.1002/cphy.c110057 · Cited by 231
The cerebellum ages slowly according to the epigenetic clock
Horvath, S., Mah, V., Lu, A. T., Woo, J. S., Choi, O.-W., Jasinska, A. J., Riancho, J. A., Tung, S., Coles, N. S., Braun, J., et al. (2015) · Aging · doi:10.18632/aging.100742 · Cited by 191
Aging and Gene Expression in the Primate Brain
Fraser, H. B., Khaitovich, P., Plotkin, J. B., Pääbo, S., & Eisen, M. B. (2005) · PLoS Biology · doi:10.1371/journal.pbio.0030274 · Cited by 172
Untitled work
Berti (2014) · doi:10.1016/j.cpet.2013.10.006 · Cited by 152
Dietary supplementation with medium-chain TAG has long-lasting cognition-enhancing effects in aged dogs
Pan, Y., Larson, B. T., Araujo, J. A., Lau, W. A. K., de Rivera, C., Santana, R., Gore, A. M., & Milgram, N. W. (2010) · British Journal Of Nutrition · doi:10.1017/s0007114510000097 · Cited by 144
A cognitive training intervention increases resting cerebral blood flow in healthy older adults
Mozolic, J. L. (2010) · Frontiers in Human Neuroscience · doi:10.3389/neuro.09.016.2010 · Cited by 148
Aging-Induced Dysregulation of Dicer1-Dependent MicroRNA Expression Impairs Angiogenic Capacity of Rat Cerebromicrovascular Endothelial Cells
Ungvari, Z. I., Tucsek, Z., Sosnowska, D., Toth, P. P., Gautam, T., Podlutsky, A. J., Csiszár, A., Losonczy, G., Valcarcel‐Ares, M. N., Sonntag, W. E., et al. (2012) · The Journals of Gerontology Series A · doi:10.1093/gerona/gls242 · Cited by 139
Nicotinamide mononucleotide (NMN) treatment attenuates oxidative stress and rescues angiogenic capacity in aged cerebromicrovascular endothelial cells: a potential mechanism for the prevention of vascular cognitive impairment
Kiss, T., Balasubramanian, P., Valcarcel‐Ares, M. N., Tarantini, S., Yabluchanskiy, A., Csípő, T., Lipécz, Á., Reglődi, D., Zhang, X. A., Bari, F., et al. (2019) · GeroScience · doi:10.1007/s11357-019-00074-2 · Cited by 134
The Val66Met polymorphism of the brain-derived neurotrophic factor gene affects age-related brain morphology
Nemoto, K., Ohnishi, T., Mori, T., Moriguchi, Y., Hashimoto, R., Asada, T., & Kunugi, H. (2006) · Neuroscience Letters · doi:10.1016/j.neulet.2005.11.067 · Cited by 131
Resistance, vulnerability and resilience: A review of the cognitive cerebellum in aging and neurodegenerative diseases
Liang, K. J., & Carlson, E. S. (2019) · Neurobiology of Learning and Memory · doi:10.1016/j.nlm.2019.01.004 · Cited by 131
Cerebral Blood Flow Measurements in Adults: A Review on the Effects of Dietary Factors and Exercise
Joris, P. J., Mensink, R. P., Adam, T. C., & Liu, T. T. (2018) · Nutrients · doi:10.3390/nu10050530 · Cited by 137
Resting hippocampal blood flow, spatial memory and aging
Heo, S., Prakash, R. S., Voss, M. W., Erickson, K. I., Ouyang, C., Sutton, B. P., & Kramer, A. F. (2009) · Brain Research · doi:10.1016/j.brainres.2009.12.020 · Cited by 126
Interaction of Age and APOE Genotype on Cerebral Blood Flow at Rest
Wierenga, C. E., Clark, L. R., Dev, S. I., Shin, D. D., Jurick, S. M., Rissman, R. A., Liu, T. T., & Bondi, M. W. (2013) · Journal of Alzheimer s Disease · doi:10.3233/jad-121897 · Cited by 126
Decreased functional magnetic resonance imaging activity in the hippocampus in favor of the caudate nucleus in older adults tested in a virtual navigation task
Konishi, K., Etchamendy, N., Roy, S., Marighetto, A., Rajah, M. N., & Bohbot, V. D. (2013) · Hippocampus · doi:10.1002/hipo.22181 · Cited by 118
Cerebral blood flow and BOLD responses to a memory encoding task: A comparison between healthy young and elderly adults
Restom, K., Bangen, K. J., Bondi, M. W., Perthen, J. E., & Liu, T. T. (2007) · NeuroImage · doi:10.1016/j.neuroimage.2007.05.024 · Cited by 113
β-amyloid and tau drive early Alzheimer’s disease decline while glucose hypometabolism drives late decline
Hammond, T. C., Xing, X., Wang, C., Ma, D., Nho, K. T., Crane, P. K., Elahi, F. M., Ziegler, D. A., Liang, G., Cheng, Q. S., et al. (2020) · Communications Biology · doi:10.1038/s42003-020-1079-x · Cited by 115
Compromised microvascular oxygen delivery increases brain tissue vulnerability with age
Moeini, M., Lu, X., Avti, P., Damseh, R., Bélanger, S., Picard, F., Boas, D. A., Kakkar, A. K., & Lesage, F. (2018) · Scientific Reports · doi:10.1038/s41598-018-26543-w · Cited by 109
Human brain evolution: From gene discovery to phenotype discovery
Preuss, T. M. (2012) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1201894109 · Cited by 114
Brain FDG PET study of normal aging in Japanese: effect of atrophy correction
Yanase, D., Matsunari, I., Yajima, K., Chen, W., Fujikawa, A., Nishimura, S., Matsuda, H., & Yamada, M. (2005) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-005-1767-2 · Cited by 104
Functional activation imaging in aging and dementia
Prvulovic, D., van de Ven, V. G., Sack, A. T., Maurer, K., & Linden, D. E. J. (2005) · Psychiatry Research Neuroimaging · doi:10.1016/j.pscychresns.2005.06.006 · Cited by 108
Use of Functional Magnetic Resonance Imaging in the Early Identification of Alzheimer's Disease
Wierenga, C. E., & Bondi, M. W. (2007) · Neuropsychology Review · doi:10.1007/s11065-007-9025-y · Cited by 105
CORRELATION BETWEEN INHIBITION, WORKING MEMORY AND DELIMITED FRONTAL AREA BLOOD FLOW MEASURED BY 99mTc-BICISATE SPECT IN ALCOHOL-DEPENDENT PATIENTS
Noël, X. (2001) · Alcohol and Alcoholism · doi:10.1093/alcalc/36.6.556 · Cited by 99
Circulating IGF-1 deficiency exacerbates hypertension-induced microvascular rarefaction in the mouse hippocampus and retrosplenial cortex: implications for cerebromicrovascular and brain aging
Tarantini, S., Tucsek, Z., Valcarcel-Ares, M. N., Toth, P., Gautam, T., Giles, C. B., Ballabh, P., Wei, J. Y., Wren, J. D., Ashpole, N. M., et al. (2016) · AGE · doi:10.1007/s11357-016-9931-0 · Cited by 98
Transcranial laser stimulation: Mitochondrial and cerebrovascular effects in younger and older healthy adults
Saucedo, C. L., Courtois, E. C., Wade, Z. S., Kelley, M. N., Kheradbin, N., Barrett, D. W., & Gonzalez-Lima, F. (2021) · Brain stimulation · doi:10.1016/j.brs.2021.02.011 · Cited by 101
Functional Genomics of Brain Aging and Alzheimers Disease: Focus on Selective Neuronal Vulnerability
Wang, X., Michaelis, M. L., & Michaelis, E. K. (2010) · Current Genomics · doi:10.2174/138920210793360943 · Cited by 94
An arteriolar compliance model of the cerebral blood flow response to neural stimulus
Behzadi, Y., & Liu, T. T. (2005) · NeuroImage · doi:10.1016/j.neuroimage.2004.12.057 · Cited by 92
Caloric restriction increases ketone bodies metabolism and preserves blood flow in aging brain
Lin, A.-L., Zhang, W., Gao, X., & Watts, L. (2015) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2015.03.012 · Cited by 90
Positron Emission Tomography Examination of Cerebral Blood Flow and Glucose Metabolism in Young CADASIL Patients
Tuominen, S., Miao, Q., Kurki, T. J. I., Tuisku, S., Pöyhönen, M., Kalimo, H., Viitanen, M. H., Sipilä, H. T., Bergman, J. R., & Rinne, J. O. (2004) · Stroke · doi:10.1161/01.str.0000124124.69842.2d · Cited by 91
Efficacy of a Therapeutic Diet on Dogs With Signs of Cognitive Dysfunction Syndrome (CDS): A Prospective Double Blinded Placebo Controlled Clinical Study
Pan, Y., Landsberg, G. M., Mougeot, I., Kelly, S., Xu, H., Bhatnagar, S., Gardner, C. L., & Milgram, N. W. (2018) · Frontiers in Nutrition · doi:10.3389/fnut.2018.00127 · Cited by 83
A longitudinal characterization of perfusion in the aging brain and associations with cognition and neural structure
Staffaroni, A. M., Cobigo, Y., Elahi, F. M., Casaletto, K. B., Walters, S. M., Wolf, A. A., Lindbergh, C. A., Rosen, H. J., & Kramer, J. H. (2019) · Human Brain Mapping · doi:10.1002/hbm.24613 · Cited by 85
Increasing measurement accuracy of age-related BOLD signal change: Minimizing vascular contributions by resting-state-fluctuation-of-amplitude scaling
Kannurpatti, S. S., Motes, M. A., Rypma, B., & Biswal, B. B. (2010) · Human Brain Mapping · doi:10.1002/hbm.21097 · Cited by 83
Scaling of Brain Metabolism and Blood Flow in Relation to Capillary and Neural Scaling
Karbowski, J. (2011) · PLoS ONE · doi:10.1371/journal.pone.0026709 · Cited by 88
Caloric restriction preserves memory and reduces anxiety of aging mice with early enhancement of neurovascular functions
Parikh, I. J., Guo, J., Chuang, K., Zhong, Y., Rempe, R. G., Hoffman, J. D., Armstrong, R., Bauer, B., Hartz, A. M. S., & Lin, A. (2016) · Aging · doi:10.18632/aging.101094 · Cited by 84
Dietary medium chain triglycerides for management of epilepsy: New data from human, dog, and rodent studies
Han, F. Y., Conboy-Schmidt, L., Quist‐Rybachuk, G., Volk, H. A., Zanghi, B. M., Pan, Y., & Borges, K. (2021) · Epilepsia · doi:10.1111/epi.16972 · Cited by 76
A longitudinal study of oculomotor function in normal older people
Kerber, K. A., Ishiyama, G. P., & Baloh, R. W. (2005) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2005.07.009 · Cited by 72
Age-related cognitive decline: Can neural stem cells help us?
Artegiani, B., & Calegari, F. (2012) · Aging · doi:10.18632/aging.100446 · Cited by 70
Impaired Cerebrovascular Function in Coronary Artery Disease Patients and Recovery Following Cardiac Rehabilitation
Anazodo, U., Shoemaker, J. K., Suskin, N., Ssali, T., Wang, D. J. J., & Lawrence, K. S. (2016) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2015.00224 · Cited by 67
A Systematic Review of the Application of Functional Near-Infrared Spectroscopy to the Study of Cerebral Hemodynamics in Healthy Aging
Yeung, M. K.-C., & Chan, A. S.-Y. (2020) · Neuropsychology Review · doi:10.1007/s11065-020-09455-3 · Cited by 67
Long‐term mild‐intensity exercise regimen preserves prefrontal cortical volume against aging
Tamura, M., Nemoto, K., Kawaguchi, A., Kato, M., Arai, T., Kakuma, T., Mizukami, K., Matsuda, H., Soya, H., & Asada, T. (2014) · International Journal of Geriatric Psychiatry · doi:10.1002/gps.4205 · Cited by 67
Quantification of the Biological Age of the Brain Using Neuroimaging
Cole, J. H., Franke, K., & Cherbuin, N. (2019) · Healthy ageing and longevity · doi:10.1007/978-3-030-24970-0_19 · Cited by 65
An investigation of cerebral oxygen utilization, blood flow and cognition in healthy aging
Catchlove, S. J., Macpherson, H., Hughes, M. E., Chen, Y. J., Parrish, T. B., & Pipingas, A. (2018) · PLoS ONE · doi:10.1371/journal.pone.0197055 · Cited by 65
The Age-Related Perfusion Pattern Measured With Arterial Spin Labeling MRI in Healthy Subjects
Zhang, N., Gordon, M. L., Ma, Y., Chi, B., Gomar, J. J., Peng, S., Kingsley, P. B., Eidelberg, D., & Goldberg, T. E. (2018) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2018.00214 · Cited by 65
Transitions in metabolic and immune systems from pre-menopause to post-menopause: implications for age-associated neurodegenerative diseases
Wang, Y., Mishra, A., & Brinton, R. D. (2020) · F1000Research · doi:10.12688/f1000research.21599.1 · Cited by 65
Enhancing Cognitive Function across the Life Span
Korol, D. L. (2002) · Annals of the New York Academy of Sciences · doi:10.1111/j.1749-6632.2002.tb02091.x · Cited by 62
Functional Magnetic Resonance Imaging of Compensatory Neural Recruitment in Aging and Risk for Alzheimer’s Disease: Review and Recommendations
Han, S. D., Bangen, K. J., & Bondi, M. W. (2008) · Dementia and Geriatric Cognitive Disorders · doi:10.1159/000182420 · Cited by 61
Multimodal Imaging in Rats Reveals Impaired Neurovascular Coupling in Sustained Hypertension
Calcinaghi, N., Wyss, M. T., Jolivet, R., Singh, A., Keller, A. L., Winnik, S. H., Fritschy, J., Buck, A., Matter, C. M., & Weber, B. (2013) · Stroke · doi:10.1161/strokeaha.111.000185 · Cited by 59
Regional Differences in the Coupling between Resting Cerebral Blood Flow and Metabolism may Indicate Action Preparedness as a Default State
Gur, R. C., Ragland, J. D., Reivich, M., Greenberg, J. H., Alavi, A. A., & Gur, R. E. (2008) · Cerebral Cortex · doi:10.1093/cercor/bhn087 · Cited by 60
Regional Correlation between Resting State FDG PET and pCASL Perfusion MRI
Cha, Y.-H. K., Jog, M., Kim, Y., Chakrapani, S., Kraman, S. M., & Wang, D. J. J. (2013) · Journal of Cerebral Blood Flow & Metabolism · doi:10.1038/jcbfm.2013.147 · Cited by 58
A million persons, a million dreams: a vision for a national center of radiation epidemiology and biology
Boice, J. D., Quinn, B. M., Al‐Nabulsi, I., Ansari, A. J., Blake, P. K., Blattnig, S. R., Caffrey, E., Cohen, S. S., Golden, A. P., Held, K. D., et al. (2021) · International Journal of Radiation Biology · doi:10.1080/09553002.2021.1988183 · Cited by 49
Effects of vinpocetine on the redistribution of cerebral blood flow and glucose metabolism in chronic ischemic stroke patients: a PET study
Szilágyi, G., Nagy, Z., Balkay, L., Boros, I., Emri, M., Lehel, S., Márián, T., Molnár, T., Szakáll, S., Trón, L., et al. (2005) · Journal of the Neurological Sciences · doi:10.1016/j.jns.2004.11.053 · Cited by 49
Electroconvulsive therapy changes the regional resting state function measured by regional homogeneity (ReHo) and amplitude of low frequency fluctuations (ALFF) in elderly major depressive disorder patients: An exploratory study
Kong, X., Xu, S., Sun, Y., Wang, K., Wang, C., Zhang, J., Xia, J.-X., Zhang, L., Tan, B.-J., & Xie, X. (2017) · Psychiatry Research Neuroimaging · doi:10.1016/j.pscychresns.2017.04.001 · Cited by 45
Immediate effects of a single session of physical exercise on cognition and cerebral blood flow: A randomized controlled study of older adults
Olivo, G., Nilsson, J., Garzón, B., Lebedev, A. V., Wåhlin, A., Tarassova, O., Ekblom, M., & Lövdén, M. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.117500 · Cited by 46
Early metabolic crisis-related brain atrophy and cognition in traumatic brain injury
Wright, M., McArthur, D. L., Alger, J. R., Horn, J. V., Andrei Irimia, A., Filippou-Frye, M., Glenn, T. C., Hovda, D. A., & Vespa, P. M. (2013) · Brain Imaging and Behavior · doi:10.1007/s11682-013-9231-6 · Cited by 44
Comparison of FDG-PET and IMP-SPECT in patients with dementia with Lewy bodies
Ishii, K., Hosaka, K., Mori, T., & Mori, E. (2004) · Annals of Nuclear Medicine · doi:10.1007/bf02984489 · Cited by 44
Longitudinal evaluation of surrogates of regional cerebral blood flow computed from dynamic amyloid PET imaging
Bilgel, M., Beason‐Held, L. L., An, Y., Zhou, Y., Wong, D. F., & Resnick, S. M. (2019) · Journal of Cerebral Blood Flow & Metabolism · doi:10.1177/0271678x19830537 · Cited by 42
Cerebral Hemodynamics in the Elderly
Yang, D., Cabral, D., Gaspard, E. N., Lipton, R. B., Rundek, T., & Derby, C. A. (2016) · Journal of Ultrasound in Medicine · doi:10.7863/ultra.15.10040 · Cited by 41
Coupling of cerebral blood flow and functional connectivity is decreased in healthy aging
Galiano, A., Mengual, E., de Eulate, M. R. G., Galdeano, I., Vidorreta, M., Recio, M., Riverol, M., Zubieta, J. L., & Fernández‐Seara, M. A. (2019) · Brain Imaging and Behavior · doi:10.1007/s11682-019-00157-w · Cited by 39
Polyphenols as an Effective Therapeutic Intervention Against Cognitive Decline During Normal and Pathological Brain Aging
Devi, S. A., & Chamoli, A. (2020) · Advances in experimental medicine and biology · doi:10.1007/978-3-030-42667-5_7 · Cited by 43
Glucose Tolerance during Moderate Alcohol Intake: Insights on Insulin Action from Glucose/Lactate Dynamics
Avogaro, A., Watanabe, R. M., Gottardo, L., de Kreutzenberg, S., Tiengo, A., & Pacini, G. (2002) · The Journal of Clinical Endocrinology & Metabolism · doi:10.1210/jcem.87.3.8347 · Cited by 41
Polyphenols and brain health
Vauzour, D. (2017) · OCL · doi:10.1051/ocl/2017008 · Cited by 43
Intrinsic Brain Connectivity Related to Age in Young and Middle Aged Adults
Hampson, M., Tokoglu, F., Shen, X., Scheinost, D., Papademetris, X., & Constable, R. T. (2012) · PLoS ONE · doi:10.1371/journal.pone.0044067 · Cited by 42
Striatal size, glucose metabolic rate, and verbal learning in normal aging
Brickman, A. M., Buchsbaum, M. S., Shihabuddin, L., Hazlett, E. A., Borod, J. C., & Mohs, R. C. (2003) · Cognitive Brain Research · doi:10.1016/s0926-6410(03)00085-5 · Cited by 38
Neuropsychological picture of 33 spinocerebellar ataxia cases
Orsi, L., D’Agata, F., Caroppo, P., Franco, A., Caglio, M., Avidano, F., Manzone, C., & Mortara, P. (2011) · Journal of Clinical and Experimental Neuropsychology · doi:10.1080/13803395.2010.518139 · Cited by 37
Basal and hypercapnia-altered cerebrovascular perfusion predict mild cognitive impairment in aging rodents
Mitschelen, M. C., Garteiser, P., Carnes, B. A., Farley, J. A., Doblas, S., DeMoe, J. H., Warrington, J. P., Yan, H., Nicolle, M. M., Towner, R. A., et al. (2009) · Neuroscience · doi:10.1016/j.neuroscience.2009.08.070 · Cited by 36
Perfusion shift from white to gray matter may account for processing speed deficits in schizophrenia
Wright, S. N., Hong, L. E., Winkler, A. M., Chiappelli, J., Nugent, K. L., Muellerklein, F., Du, X., Rowland, L. M., Wang, D. J. J., & Kochunov, P. (2015) · Human Brain Mapping · doi:10.1002/hbm.22878 · Cited by 35
The Use of Heptamethine Cyanine Dyes as Drug-Conjugate Systems in the Treatment of Primary and Metastatic Brain Tumors
Cooper, E., Choi, P. J., Denny, W. A., Jose, J., Dragunow, M., & Park, T. (2021) · Frontiers in Oncology · doi:10.3389/fonc.2021.654921 · Cited by 36
A Potential Role for Glucose Transporters in the Evolution of Human Brain Size
Fedrigo, O. D., Pfefferle, A. D., Babbitt, C. C., Haygood, R., Wall, C. E., & Wray, G. A. (2011) · Brain Behavior and Evolution · doi:10.1159/000329852 · Cited by 36
Endothelial deficiency of insulin‐like growth factor‐1 receptor leads to blood–brain barrier disruption and accelerated endothelial senescence in mice, mimicking aspects of the brain aging phenotype
Gulej, R., Csík, B., Faakye, J., Tarantini, S., Shanmugarama, S., Chandragiri, S. S., Mukli, P., Conley, S. M., Csiszár, A., Ungvari, Z. I., et al. (2023) · Microcirculation · doi:10.1111/micc.12840 · Cited by 32
Links Between Metabolic and Structural Changes in the Brain of Cognitively Normal Older Adults: A 4-Year Longitudinal Follow-Up
Castellano, C., Hudon, C., Croteau, É., Fortier, M., St‐Pierre, V., Vandenberghe, C., Nugent, S., Tremblay, S., Paquet, N., Lepage, M., et al. (2019) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2019.00015 · Cited by 32
Feasibility of simultaneous whole-brain imaging on an integrated PET-MRI system using an enhanced 2-point Dixon attenuation correction method
Anazodo, U., Thiessen, J. D., Ssali, T., Mandel, J., nther, M. G. ⁄., Butler, J., Pavlosky, W. F., Prato, F. S., Thompson, R. T., & Lawrence, K. S. (2015) · Frontiers in Neuroscience · doi:10.3389/fnins.2014.00434 · Cited by 31
Cerebral hemodynamic and oxygenation changes induced by inner and heard speech: a study combining functional near-infrared spectroscopy and capnography
Scholkmann, F., Klein, S. D., Gerber, U., Wolf, M., & Wolf, U. (2014) · Journal of Biomedical Optics · doi:10.1117/1.jbo.19.1.017002 · Cited by 31
On the time course of attentional focusing in older adults
Jefferies, L. N., Roggeveen, A. B., Enns, J. T., Bennett, P., Sekuler, A. B., & Lollo, V. D. (2013) · Psychological Research · doi:10.1007/s00426-013-0528-2 · Cited by 29
Impairments in Brain Bioenergetics in Aging and Tau Pathology: A Chicken and Egg Situation?
Grimm, A. (2021) · Cells · doi:10.3390/cells10102531 · Cited by 26
Resting cerebral glucose metabolism and perfusion patterns in women with posttraumatic stress disorder related to sexual assault
Kim, S.-Y., Chung, Y. K., Kim, B. S., Lee, S. J., Yoon, J., & An, Y. (2012) · Psychiatry Research Neuroimaging · doi:10.1016/j.pscychresns.2011.08.007 · Cited by 28
Brain perfusion imaging in amyotrophic lateral sclerosis: Extent of cortical changes according to the severity and topography of motor impairment
Habert, M., Lacomblez, L., Maksud, P., Fakhri, G. E., Pradat, J., & Meininger, V. (2007) · Amyotrophic Lateral Sclerosis · doi:10.1080/14660820601048815 · Cited by 28
Cerebrovascular hemodynamic correlates of aging in the Lou/c rat: A model of healthy aging
Dubeau, S., Ferland, G., Gaudreau, P., Beaumont, É., & Lesage, F. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2011.03.076 · Cited by 32
Age-Related Increase in Cross-Sensory Noise in Resting and Steady-State Cerebral Perfusion
Hugenschmidt, C. E., Mozolic, J. L., Tan, H., Kraft, R., & Laurienti, P. J. (2009) · Brain Topography · doi:10.1007/s10548-009-0098-1 · Cited by 27
Scaling of cerebral blood perfusion in primates and marsupials
Seymour, R. S., Angove, S. E., Snelling, E. P., & Cassey, P. (2015) · Journal of Experimental Biology · doi:10.1242/jeb.124826 · Cited by 26
Diverging roles of the anterior insula in trauma-exposed individuals vulnerable or resilient to posttraumatic stress disorder
Jeong, H. S., Chung, Y., Ma, J., Kim, J., Hong, G., Oh, J. K., Kim, M., Ha, E., Hong, H., Yoon, S. J., et al. (2019) · Scientific Reports · doi:10.1038/s41598-019-51727-3 · Cited by 27
Empirical derivation of the reference region for computing diagnostic sensitive 18fluorodeoxyglucose ratios in Alzheimer's disease based on the ADNI sample
Rasmussen, J. M., Lakatos, A., van Erp, T. G. M., Kruggel, F., Keator, D. B., Fallon, J., Macciardi, F. M., & Potkin, S. G. (2011) · Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease · doi:10.1016/j.bbadis.2011.09.008 · Cited by 26
A statistical investigation of normal regional intra-subject heterogeneity of brain metabolism and perfusion by F-18 FDG and O-15 H2O PET imaging
Wong, C.-Y. O., Thie, J. A., Gaskill, M., Ponto, R. A., Hill, J., Tian, H.-Y., Balon, H. R., Wu, D., FINK-BENNETT, D. M., & Nagle, C. E. (2006) · BMC Nuclear Medicine · doi:10.1186/1471-2385-6-4 · Cited by 26
Aging is not equal across memory systems
Gardner, R. S., Newman, L. A., Mohler, E. G., Tunur, T., Gold, P. E., & Korol, D. L. (2020) · Neurobiology of Learning and Memory · doi:10.1016/j.nlm.2020.107232 · Cited by 24
Nutrients, Cognitive Function, and Brain Aging: What We Have Learned from Dogs
Pan, Y. (2021) · Medical Sciences · doi:10.3390/medsci9040072 · Cited by 30
The association of regional cerebral blood flow and glucose metabolism in normative ageing and insulin resistance
Deery, H. A., Liang, E. X., Paolo, R. D., Voigt, K., Murray, G., Siddiqui, M. N., Egan, G. F., Moran, C., & Jamadar, S. D. (2024) · Scientific Reports · doi:10.1038/s41598-024-65396-4 · Cited by 24
Kinetic modeling of PET data without blood sampling
Bentourkia, M. (2005) · IEEE Transactions on Nuclear Science · doi:10.1109/tns.2005.851442 · Cited by 23
Self-citation
Changes in diffusion path length with old age in diffuse optical tomography
Bonnéry, C., Desjardins, M., Pouliot, P., Lesage, F., Leclerc, P.-O., Hoge, R. D., & Bherer, L. (2012) · Journal of Biomedical Optics · doi:10.1117/1.jbo.17.5.056002 · Cited by 21
Regional cerebral blood flow in natives at high altitude: An arterial spin labeled MRI study
Wang, X., Wei, W., Yuan, F., Li, S., Lin, J., & Zhang, J. (2018) · Journal of Magnetic Resonance Imaging · doi:10.1002/jmri.25996 · Cited by 21

Authors: Bentourkia, M., Bol, A., Ivanoiu, A., Labar, D., Sibomana, M., Coppens, A., Michel, C., Cosnard, G., & De Volder, A. G.
Affiliations: UCLouvain (BE)
ORCID: Bentourkia, M’hamed
Michel, Christian
Venue: Journal of the Neurological Sciences
Publisher: Elsevier BV
Published: 2000-12
Volume: 181
Issue: 1-2
Pages: 19-28
ISSN: 0022-510X (ISSN-L)
DOI: 10.1016/s0022-510x(00)00396-8
OpenAlex: W1963947389
Cited by: 189
References: 57
Citations by year: 2026: 2 · 2025: 2 · 2024: 10 · 2023: 8 · 2022: 10 · 2021: 14 · 2020: 9 · 2019: 12 · 2018: 11 · 2017: 6 · 2016: 8 · 2015: 9 · 2014: 4 · 2013: 11 · 2012: 9
FWCI: 3.88
Type: journal article
Language: en
Open access: closed
Licence: www.elsevier.com/tdm/userlicense/1.0/ (tdm)
Locations: Journal of the Neurological Sciences (publishedVersion)
PubMed (publishedVersion)
DIAL (Catholic University of Leuven) (submittedVersion)
Topics: Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
Keywords: regional cerebral blood flow, brain glucose metabolism, aging, brain aging, frontal cortex, visual cortex, striatum, cerebellum, regional brain metabolism, normal brain
MeSH terms: Adult, Aged, Aging, Brain, Cerebrovascular Circulation, Female, Glucose, Humans, Male, Middle Aged, Tomography, Emission-Computed

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Comparison of regional cerebral blood flow and glucose metabolism in the normal brain: effect of aging

Abstract

Overview

Integrity signals

Verification

Claims the paper makes

Claims other papers make about this one

Citations

Cites

Cited by

Related

Metadata

Record

About these checks