The DOI matches its Crossref record.
Preserved Pontine Glucose Metabolism in Alzheimer Disease: A Reference Region for Functional Brain Image (PET) Analysis
Abstract
OBJECTIVE: Our goal was to examine regional preservation of energy metabolism in Alzheimer disease (AD) and to evaluate effects of PET data normalization to reference regions. MATERIALS AND METHODS: Regional metabolic rates in the pons, thalamus, putamen, sensorimotor cortex, visual cortex, and cerebellum (reference regions) were determined stereotaxically and examined in 37 patients with probable AD and 22 normal controls based on quantitative 18FDG-PET measurements. Following normalization of metabolic rates of the parietotemporal association cortex and whole brain to each reference region, distinctions of the two groups were assessed. RESULTS: The pons showed the best preservation of glucose metabolism in AD. Other reference regions showed relatively preserved metabolism compared with the parietotemporal association cortex and whole brain, but had significant metabolic reduction. Data normalization to the pons not only enhanced statistical significance of metabolic reduction in the parietotemporal association cortex, but also preserved the presence of global cerebral metabolic reduction indicated in analysis of the quantitative data. CONCLUSION: Energy metabolism in the pons in probable AD is well preserved. The pons is a reliable reference for data normalization and will enhance diagnostic accuracy and efficiency of quantitative and nonquantitative functional brain imaging.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
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?
In the citing paper
“Measurements in each voxel were normalized to that in the pons, which appears to be the region least affected in patients with Alzheimer's disease.27”
From Preclinical Evidence of Alzheimer's Disease in Persons Homozygous for the ε4 Allele for Apolipoprotein E (1996) · cites this paper as [27]
Citations
Cited by
Sorted by citations
Metabolic reduction in the posterior cingulate cortex in very early Alzheimer's disease
Minoshima, S., Giordani, B., Berent, S., Frey, K. A., Foster, N. L., & Kuhl, D. E. (1997) · Annals of Neurology · doi:10.1002/ana.410420114 · Cited by 1,802
Self-citationReiman, E. M., Caselli, R. J., Yun, L. S., Chen, K., Bandy, D., Minoshima, S., Thibodeau, S. N., & Osborne, D. (1996) · New England Journal of Medicine · doi:10.1056/nejm199603213341202 · Cited by 1,366
Self-citationCraft, S. (2012) · Archives of Neurology · doi:10.1001/archneurol.2011.233 · Cited by 1,253
“Taken together, these results provide an impetus for future clinical trials of intranasal insulin therapy and for further mechanistic studies of insulin’s role in the pathogenesis of AD.”
InfluentialTau PET patterns mirror clinical and neuroanatomical variability in Alzheimer’s disease
Ossenkoppele, R., Schonhaut, D. R., Schöll, M., Lockhart, S. N., Ayakta, N., Baker, S. L., O’Neil, J. P., Janabi, M., Lazaris, A., Cantwell, A., et al. (2016) · Brain · doi:10.1093/brain/aww027 · Cited by 1,185
“(18)F-FDG PET images were summed, and standardized uptake value ratios (SUVR) were calculated for the 30–60-min post-injection interval using mean activity in the pons (manually edited from FreeSurferderived brainstem) as the reference region (Minoshima et al., 1995).”
MethodFunctional brain abnormalities in young adults at genetic risk for late-onset Alzheimer's dementia
Reiman, E. M., Chen, K., Alexander, G. E., Caselli, R. J., Bandy, D., Osborne, D., Saunders, A. M., & Hardy, J. (2004) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2635903100 · Cited by 977
Two-year follow-up of amyloid deposition in patients with Alzheimer's disease
Engler, H., Forsberg, A., Almkvist, O., Blomquist, G., Larsson, E., Savitcheva, I., Wall, A. E., Ringheim, A., Långström, B., & Nordberg, A. K. (2006) · Brain · doi:10.1093/brain/awl178 · Cited by 614
“The rCMRGlc values were normalized to the pons value (ROI/ref) to allow inter- and intra-individual comparisons (Minoshima et al., 1995).”
MethodFDG-PET improves accuracy in distinguishing frontotemporal dementia and Alzheimer's disease
Foster, N. L., Heidebrink, J. L., Clark, C. M., Jagust, W. J., Arnold, S. E., Barbas, N. R., DeCarli, C. S., Scott Turner, R., Koeppe, R. A., Higdon, R., et al. (2007) · Brain · doi:10.1093/brain/awm177 · Cited by 608
“We normalized surface pixel values to the pons, which is relatively preserved in AD (Minoshima et al., 1995a).”
MethodSelf-citationMinoshima, S., Foster, N. L., Sima, A. A. F., Frey, K. A., Albin, R. L., & Kuhl, D. E. (2001) · Annals of Neurology · doi:10.1002/ana.1133 · Cited by 560
“Metabolic imaging fulfills many features of a proposed biomarker for AD.56 The accurate antemortem differential diagnosis of interrelated dementing disorders will help select patients who can benefit from drugs specific to diseases and develop drug trials by Minoshima et al: Metabolic Distinction of AD versus DLB 363…”
BackgroundInfluentialSelf-citationHippocampal formation glucose metabolism and volume losses in MCI and AD
De Santi, S., de Leon, M. J., Rusinek, H., Convit, A., Tarshish, C. Y., Roche, A., Tsui, W. H., Kandil, E., Boppana, M., Daisley, K., et al. (2001) · Neurobiology of Aging · doi:10.1016/s0197-4580(01)00230-5 · Cited by 548
Alexander, G. E., Chen, K., Pietrini, P., Rapoport, S. I., & Reiman, E. M. (2002) · American Journal of Psychiatry · doi:10.1176/appi.ajp.159.5.738 · Cited by 532
“The glucose metabolism values in the pons were extracted for each scan as a reference region because these values tend to be relatively preserved in Alzheimer’s disease ( 26 ) and did not differ significantly (p=0.16) over time in our patients with Alzheimer’s disease.”
MethodInfluentialAβ amyloid and glucose metabolism in three variants of primary progressive aphasia
Rabinovici, G. D., Jagust, W. J., Furst, A. J., Ogar, J. M., Racine, C. A., Mormino, E. C., O'Neil, J. P., Lal, R. A., Dronkers, N. F., Miller, B. L., et al. (2008) · Annals of Neurology · doi:10.1002/ana.21451 · Cited by 477
“PET-FDG frames were summed and normalized to mean activity in the pons for each subject.(44) For PIB, voxelwise distribution volume ratios (DVRs) were calculated using Logan graphical analysis,(45) with the cerebellum ROI timeactivity curve used as a reference tissue input function.”
Method11 C-PIB PET imaging in Alzheimer disease and frontotemporal lobar degeneration
Rabinovici, G. D., Furst, A. J., O’Neil, J. P., Racine, C. A., Mormino, E. C., Baker, S. L., Chetty, S., Patel, P. R., Pagliaro, T. A., Klunk, W. E., et al. (2007) · Neurology · doi:10.1212/01.wnl.0000259035.98480.ed · Cited by 419
Klunk, W. E., Price, J. C., Mathis, C. A., Tsopelas, N. D., Lopresti, B. J., Ziolko, S. K., Bi, W., Hoge, J. A., Cohen, A. D., Ikonomovic, M. D., et al. (2007) · Journal of Neuroscience · doi:10.1523/jneurosci.0730-07.2007 · Cited by 389
“Fagan AM, Mintun MA, Mach RH, Lee SY, Dence CS, Shah AR, Larossa GN, Spinner ML, Klunk WE, Mathis CA, Dekosky ST, Morris JC, Holtzman DM (2006) Inverse relation between in vivo amyloid imaging load and cerebrospinal fluid Abeta(42) in humans.”
Regional variability of imaging biomarkers in autosomal dominant Alzheimer's disease
Benzinger, T. L. S., Blazey, T., Jack, C. R., Koeppe, R. A., Su, Y., Xiong, C., Raichle, M. E., Snyder, A. Z., Ances, B. M., Bateman, R. J., et al. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1317918110 · Cited by 391
“However, there have been reports in normal aging (28) and mild cognitive impairment (29) of an association between early PiB uptake and hypermetabolism, albeit of variable focality, as determined by FDG PET.”
BackgroundInfluentialPGC-1α Expression Decreases in the Alzheimer Disease Brain as a Function of Dementia
Qin, W., Haroutunian, V. H., Katsel, P., Cardozo, C. P., Ho, L., Buxbaum, J. D., & Pasinetti, G. M. (2009) · Archives of Neurology · doi:10.1001/archneurol.2008.588 · Cited by 393
Attenuation Correction Synthesis for Hybrid PET-MR Scanners: Application to Brain Studies
Burgos, N., Cardoso, M. J., Thielemans, K., Marc Modat, A., Pedemonte, S., Dickson, J. C., Barnes, A., Ahmed, R. M., Mahoney, C., Schott, J. M., et al. (2014) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2014.2340135 · Cited by 365
“A common practice in the neuro-imaging community is to normalize PET images using a reference region [35], [36].”
BackgroundLongitudinal evaluation of early Alzheimer's disease using brain perfusion SPECT.
Kogure, D., Matsuda, H., Ohnishi, T., Asada, T., Uno, M., Kunihiro, T., Nakano, S., & Takasaki, M. (2000) · PubMed · Cited by 365
Hippocampal hypometabolism predicts cognitive decline from normal aging
Mosconi, L., De Santi, S., Li, J., Tsui, W. H., Li, Y., Boppana, M., Laska, E., Rusinek, H., & de Leon, M. J. (2008) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2006.12.008 · Cited by 360
Gong, B., Pan, Y., Vempati, P., Zhao, W., Knable, L., Ho, L., Wang, J., Sastre, M., Ono, K., Sauve, A. A., et al. (2013) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2012.12.005 · Cited by 345
“…Hoyer, 1995; Herholz et al., 2002) and positron emission tomography studies demonstrated that glucose utilization is reduced markedly in the brain of mild cognitive impairment and early stage AD (Jagust et al., 1991; Minoshima et al., 1995), which is associated with abnormal mitochondrial function.”
Lehmann, M., Ghosh, P. M., Madison, C., Laforce, R., Corbetta-Rastelli, C., Weiner, M. W., Greicius, M. D., Seeley, W. W., Gorno-Tempini, M. L., Rosen, H. J., et al. (2013) · Brain · doi:10.1093/brain/aws327 · Cited by 325
“FDG-PET frames were summed and standard uptake volume ratios were calculated by normalizing the summed FDG image to mean activity in the pons for each subject (Minoshima et al., 1995).”
MethodGreve, D. N., Salat, D. H., Bowen, S., Izquierdo‐Garcia, D., Schultz, A. P., Catana, C., Becker, J. A., Svarer, C., Knudsen, G. M., Sperling, R. A., et al. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2016.02.042 · Cited by 312
“Pons was chosen because it is commonly used (Ewers et al., 2014; Kantarci et al., 2001; Knopman et al., 2014; Landau et al., 2011), easy to identify, has small PVEs, and is thought to be resistant to atrophy, at least in AD (Minoshima et al., 1995).”
MethodRodriguez‐Vieitez, E., Saint‐Aubert, L., Carter, S. F., Almkvist, O., Farid, K., Schöll, M., Chiotis, K., Þórðardóttir, S., Graff, C., Wall, A. E., et al. (2016) · Brain · doi:10.1093/brain/awv404 · Cited by 307
“Registered 18F-FDG and 11CPiB PET images for each participant were sampled using the created individual cortical atlas; the whole pons was used as a reference as it was found to be preserved from pathology in both ADAD and sporadic Alzheimer’s disease (Minoshima et al., 1995).”
MethodBayesian segmentation of brainstem structures in MRI
Iglesias, J. E., Leemput, K. V., Bhatt, P., Casillas, C., Dutt, S., Schuff, N. W., Truran‐Sacrey, D., Boxer, A. L., & Fischl, B. R. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2015.02.065 · Cited by 287
“6.”
Rabinovici, G. D., Furst, A. J., Alkalay, A., Racine, C. A., O’Neil, J. P., Janabi, M., Baker, S. L., Agarwal, N., Bonasera, S. J., Mormino, E. C., et al. (2010) · Brain · doi:10.1093/brain/awp326 · Cited by 289
“…disease and nine with late-onset Alzheimer’s disease) were scanned on a 1.5 Tesla Siemens VISION system (Rosen et al., 2002), and 11 patients (seven early-onset and fou late-onset) were scanned on a Bruker MedSpec 4 Tesla system controlled by a Siemens TrioTM console (Mueller et al., 2009).”
MethodInfluentialWalhovd, K. B., Fjell, A. M., Brewer, J., McEvoy, L. K., Fennema-Notestine, C., Hagler, D. J., Jennings, R. G., Karow, D., Dale, A. M., & Initiative, T. A. D. N. (2010) · American Journal of Neuroradiology · doi:10.3174/ajnr.a1809 · Cited by 279
“pled onto their reconstructed cortical surface, averaged within each region of interest, and normalized to activity within the pons.(45)”
Method(2006) · PubMed · Cited by 269
Cohen, A. D., Price, J. C., Weissfeld, L. A., James, J. A., Rosario, B. L., Bi, W., Nebes, R. D., Saxton, J. A., Snitz, B. E., Aizenstein, H. J., et al. (2009) · Journal of Neuroscience · doi:10.1523/jneurosci.3669-09.2009 · Cited by 240
“The FDG-PET data were analyzed via summed images in a manner consistent with established methods (Minoshima et al., 1995; Herholz et al., 2002; Ziolko et al., 2006).”
MethodCerebral blood flow and metabolic abnormalities in Alzheimer’s disease
Matsuda, H. (2001) · Annals of Nuclear Medicine · doi:10.1007/bf02988596 · Cited by 233
Cerebral Glucose Metabolic Features of Parkinson Disease and Incident Dementia: Longitudinal Study
Bohnen, N. I., Koeppe, R. A., Minoshima, S., Giordani, B., Albin, R. L., Frey, K. A., & Kuhl, D. E. (2011) · Journal of Nuclear Medicine · doi:10.2967/jnumed.111.089946 · Cited by 217
Self-citationDeo, A. K., Borson, S., Link, J. M., Domino, K., Eary, J. F., Ke, B., Richards, T. L., Mankoff, D. A., Minoshima, S., O’Sullivan, F., et al. (2014) · Journal of Nuclear Medicine · doi:10.2967/jnumed.113.130161 · Cited by 193
Self-citationIm, J. J., Jeong, H. S., Bikson, M., Woods, A. J., Unal, G., Oh, J. K., Na, S., Park, J., Knotková, H., Song, I., et al. (2019) · Brain stimulation · doi:10.1016/j.brs.2019.06.003 · Cited by 182
“Then, the images were scaled to the mean uptake of the pons [30] using proportional scaling, followed by grand mean scaling to 50.”
Chen, K., Langbaum, J. B. S., Fleisher, A., Ayutyanont, N., Reschke, C., Lee, W., Liu, X., Bandy, D., Alexander, G. E., Thompson, P. M., et al. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2010.02.064 · Cited by 173
“Pontine ROI measurements were characterized by Dr. Foster's laboratory using NeuroStat software as previously described (Minoshima et al., 1995) and downloaded from the LONI website.”
MethodSelf-citationMinoshima, S., Cross, D. J., Thientunyakit, T., Foster, N. L., & Drzezga, A. E. (2022) · Journal of Nuclear Medicine · doi:10.2967/jnumed.121.263194 · Cited by 185
“The areas of relatively preserved activity, such as the pons, can be used as a reference region for pixel normalization in quantitative image analysis ( 37 ).”
MethodSelf-citationCortisol Reduces Hippocampal Glucose Metabolism in Normal Elderly, but Not in Alzheimer's Disease
de Leon, M. J., McRae, T., Rusinek, H., Convit, A. J., Santi, S. D., Tarshish, C. Y., Golomb, J. B., Volkow, N. D., Daisley, K., Orentreich∥, N., et al. (1997) · The Journal of Clinical Endocrinology & Metabolism · doi:10.1210/jcem.82.10.4305 · Cited by 176
“midbrain) ( 47 ). The contribution of cerebrospinal fluid to the estimated regional metabolic rates was minimized by using precise anatomical drawings followed by a MRI tissue segmentation technique to exclude cerebrospinal fluid from the region of the drawing.”
MethodBorghammer, P., Chakravarty, M., Jonsdottir, K., Sato, N., Matsuda, H., Ito, K., Arahata, Y., Kato, T., & Gjedde, A. (2010) · Brain Structure and Function · doi:10.1007/s00429-010-0246-0 · Cited by 160
“The pons (Minoshima et al. 1995) and cerebellum (Firbank et al. 2003) have previously been proposed as unbiased normalization reference regions in PD and Alzheimer’s disease; (3) we also analyzed the data with the recently published reference cluster method (YAK) (Yakushev et al. 2009).”
MethodGonzalez-Redondo, R., García‐García, D., Clavero, P., Gasca‐Salas, C., de Eulate, M. R. G., Zubieta, J. L., Arbizu, J., Obeso, J. A., & Rodríguez‐Oroz, M. (2014) · Brain · doi:10.1093/brain/awu159 · Cited by 163
Multi-modal imaging predicts memory performance in normal aging and cognitive decline
Walhovd, K. B., Fjell, A. M., Dale, A. M., McEvoy, L. K., Brewer, J. B., Karow, D. S., Salmon, D. P., & Fennema‐Notestine, C. (2008) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2008.08.013 · Cited by 159
Metabolic syndrome and the role of dietary lifestyles in Alzheimer’s disease
Pasinetti, G. M., & Eberstein, J. A. (2008) · Journal of Neurochemistry · doi:10.1111/j.1471-4159.2008.05454.x · Cited by 160
“This evidence strongly associates abnormal brain glucose metabolism with abnormal OXPHOSmitochondria in the AD brain and possibly provides further evidence supporting a causal role for hyperglycemic conditions associated with metabolic syndrome as risk factors in AD (Jagust et al. 1991; Minoshima et al. 1995; Craft an…”
BackgroundDynamic changes in PET amyloid and FDG imaging at different stages of Alzheimer's disease
Kadir, A., Almkvist, O., Forsberg, A., Wall, A. E., Engler, H., Långström, B., & Nordberg, A. K. (2010) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2010.06.015 · Cited by 161
Nutrient patterns and brain biomarkers of Alzheimer's disease in cognitively normal individuals
Berti, V., Murray, J., Davies, M., Spector, N. C., Tsui, W. H., Li, Y., Williams, S. K., Pirraglia, E., Vallabhajosula, S., McHugh, P. F., et al. (2014) · The journal of nutrition health & aging · doi:10.1007/s12603-014-0534-0 · Cited by 156
“Parametric standardized uptake value ratio (SUVR) images were generated by normalizing PiB uptake by cerebellar grey matter uptake (48) and FDG by pons activity (49).”
Wirth, M., Madison, C. M., Rabinovici, G. D., Oh, H., Landau, S. M., & Jagust, W. J. (2013) · The Journal of Neuroscience · doi:10.1523/jneurosci.4409-12.2013 · Cited by 151
“The choice of reference region was based on evidence indicating preservation of pontine glucose metabolism in AD patients (Minoshima et al., 1995).”
BackgroundTau, amyloid, and hypometabolism in a patient with posterior cortical atrophy
Ossenkoppele, R., Schonhaut, D. R., Baker, S. L., O’Neil, J. P., Janabi, M., Ghosh, P. M., Santos‐Santos, M., Miller, Z., Bettcher, B. M., Gorno‐Tempini, M. L., et al. (2014) · Annals of Neurology · doi:10.1002/ana.24321 · Cited by 151
“[(18)F]FDG-PET images were summed, and standardized uptake value ratios (SUVrs) were calculated for the 30- to 60minute postinjection interval using mean activity in the pons (defined in FreeSurfer and manually edited) as the reference region.(14) Consistent with the initial report on human [(18)F]AV-1451/[(18)F]T807-…”
MethodCognition, glucose metabolism and amyloid burden in Alzheimer's disease
Furst, A. J., Rabinovici, G. D., Rostomian, A. H., Steed, T., Alkalay, A., Racine, C. A., Miller, B. L., & Jagust, W. J. (2010) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2010.03.011 · Cited by 153
“…with the existing literature, we found cognitive decline to be strongly associated with decreased glucose metabolism in frontal and temporo-parietal regions (Heiss et al., 1991a; Heiss et al., 1991b; Herholz et al., 2002; Langbaum et al., 2009; Mielke et al., 1994; Minoshima et al., 1995b).”
BackgroundMethodQuantitative assessment of cerebral blood flow in patients with Alzheimer's disease by SPECT.
Bartenstein, P., Minoshima, S., Hirsch, C., Buch, K., Willoch, F., Mösch, D., Schad, D., Schwaiger, M., & Kurz, A. (1997) · PubMed · Cited by 143
Self-citationRepetitive blast exposure in mice and combat veterans causes persistent cerebellar dysfunction
Meabon, J. S., Huber, B. R., Cross, D. J., Richards, T. L., Minoshima, S., Pagulayan, K. F., Li, G., Meeker, K. D., Kraemer, B. C., Petrie, E. C., et al. (2016) · Science Translational Medicine · doi:10.1126/scitranslmed.aaa9585 · Cited by 138
Self-citationTune, L. E., Tiseo, P. J., Ieni, J. R., Perdomo, C. A., Pratt, R. D., Votaw, J. R., Jewart, R. D., & Hoffman, J. M. (2003) · American Journal of Geriatric Psychiatry · doi:10.1097/00019442-200303000-00007 · Cited by 134
Yakushev, I. Y., Hammers, A., Fellgiebel, A., Schmidtmann, I. M., Scheurich, A., Buchholz, H., Peters, J., Bartenstein, P., Lieb, K., & Schreckenberger, M. (2008) · NeuroImage · doi:10.1016/j.neuroimage.2008.07.015 · Cited by 130
“However, in subjects with AD average whole brain CMRglc is abnormally low (Kumar et al., 1993; Minoshima et al., 1995a) irrespective of atrophy (Alavi et al., 1993; Ibáñez et al., 1998).”
InfluentialEffect of phenserine treatment on brain functional activity and amyloid in Alzheimer's disease
Kadir, A., Andreasen, N., Almkvist, O., Wall, A. E., Forsberg, A., Engler, H., Hagman, G., Lärksäter, M., Winblad, B. G., Zetterberg, H., et al. (2008) · Annals of Neurology · doi:10.1002/ana.21345 · Cited by 132
“Plasma A 42 concentrations were determined by using the high-sensitivity INNOTEST -AMYLOID(1-42) assay (Innogenetics, Ghent, Belgium).”
MethodDukart, J., Mueller, K., Horstmann, A., Vogt, B., Frisch, S., Barthel, H., Becker, G., Möller, H. E., Villringer, A., Sabri, O., et al. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2009.09.017 · Cited by 134
“Second, normalization to the cerebellum provides an easily determined and reliable alternative to the sensorimotor cortex which is also frequently used (Minoshima et al., 1995; Santens et al., 2001; Sakamoto et al., 2002; Yakushev et al., 2008, 2009), but which has the disadvantage that the surface appearance and stru…”
BackgroundMethodInfluentialA SPECT study of apathy in Alzheimer's disease
Lanctôt, K. L., Moosa, S., Herrmann, N., Leibovitch, F. S., Rothenburg, L., Cotter, A., & Black, S. E. (2007) · Dementia and Geriatric Cognitive Disorders · doi:10.1159/000103633 · Cited by 126
“The cerebellum was chosen as the reference region because blood perfusion in the cerebellum remains fairly unaffected in AD, even as the disease progresses [”
MethodBailly, M., Destrieux, C., Hommet, C., Mondon, K., Cottier, J., Beaufils, É., Vierron, E., Vercouillie, J., Ibazizène, M., Voisin, T., et al. (2015) · BioMed Research International · doi:10.1155/2015/583931 · Cited by 124
“Other regions have been described as reliable references for data normalization: pons [40] or cerebral global normalization which might be superior for differential diagnostic purposes in dementia syndromes [41].”
BackgroundDistinct clinical and metabolic deficits in PCA and AD are not related to amyloid distribution
Rosenbloom, M. H., Alkalay, A., Agarwal, N., Baker, S. L., O’Neil, J. P., Janabi, M., Yen, I. V., Growdon, M. E., Jang, J., Madison, C. M., et al. (2011) · Neurology · doi:10.1212/wnl.0b013e31821cccad · Cited by 125
Karow, D. S., McEvoy, L. K., Fennema‐Notestine, C., Hagler, D. J., Jennings, R. G., Brewer, J. B., Hoh, C. K., Dale, A. M., & Initiative, A. D. N. (2010) · Radiology · doi:10.1148/radiol.10091402 · Cited by 120
Yakushev, I. Y., Landvogt, C., Buchholz, H., Fellgiebel, A., Hammers, A., Scheurich, A., Schmidtmann, I. M., Gerhard, A., Schreckenberger, M., & Bartenstein, P. (2008) · Psychiatry Research Neuroimaging · doi:10.1016/j.pscychresns.2007.11.004 · Cited by 118
“In that ROI study as well as in our study, regional metabolic values were determined stereotactically (Minoshima et al., 1995a).”
InfluentialZiolko, S. K., Weissfeld, L. A., Klunk, W. E., Mathis, C. A., Hoge, J. A., Lopresti, B. J., DeKosky, S. T., & Price, J. C. (2006) · NeuroImage · doi:10.1016/j.neuroimage.2006.05.063 · Cited by 119
García‐García, D., Clavero, P., Gasca‐Salas, C., Lamet, I., Arbizu, J., Gonzalez-Redondo, R., Obeso, J. A., & Rodríguez-Oroz, M. C. (2012) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-012-2198-5 · Cited by 125
“0 [12, 36–38].”
Willette, A. A., Modanlo, N., Kapogiannis, D., & Initiative, A. D. N. (2015) · Diabetes · doi:10.2337/db14-1507 · Cited by 118
“We then normalized FDG-PET pixel intensity to the pons, due to its preserved glucose metabolism in AD (30), to derive the standardized uptake value ratio.”
MethodOssenkoppele, R., Iaccarino, L., Schonhaut, D. R., Brown, J. A., Joie, R. L., O’Neil, J. P., Janabi, M., Baker, S. L., Kramer, J. H., Gorno‐Tempini, M., et al. (2019) · NeuroImage Clinical · doi:10.1016/j.nicl.2019.101848 · Cited by 109
Higdon, R., Foster, N. L., Koeppe, R. A., DeCarli, C. S., Jagust, W. J., Clark, C. M., Barbas, N. R., Arnold, S. E., Turner, R. S., Heidebrink, J. L., et al. (2004) · Statistics in Medicine · doi:10.1002/sim.1719 · Cited by 94
“To eliminate between subject (and PET scanner) variability the 3D-SSP image is standardized by dividing by the pons value (autonomic function region) [ 9 ].”
MethodSelf-citationImabayashi, E., Matsuda, H., Asada, T., Ohnishi, T., Sakamoto, S., Nakano, S., & Inoue, T. (2004) · PubMed · Cited by 89
Minoshima, S., Mosci, K., Cross, D. J., & Thientunyakit, T. (2021) · Seminars in Nuclear Medicine · doi:10.1053/j.semnuclmed.2021.01.002 · Cited by 93
Self-citationMosconi, L., Murray, J., Davies, M., Williams, S., Pirraglia, E., Spector, N. C., Tsui, W. H., Li, Y., Butler, T., Osorio, R. S., et al. (2014) · BMJ Open · doi:10.1136/bmjopen-2014-004850 · Cited by 89
“Standardised uptake value ratios were generated for each ROI by normalising PiB uptake by cerebellar grey matter uptake(29) and FDG by pons activity.(30) A composite cortical PiB retention mask (AVGPiB) was created by combining parietotemporal, frontal and PCC regions, and an FDG mask (AVGFDG) by combining parietotemp…”
MethodKnight, W. D., Okello, A., Ryan, N. S., Turkheimer, F., de Llano, S. R. M., Edison, P., Douglas, J., Fox, N. C., Brooks, D. J., & Rossor, M. N. (2010) · Brain · doi:10.1093/brain/awq310 · Cited by 86
Mosconi, L., Santi, S. D., Li, Y., Li, J., Zhan, J., Tsui, W. H., Boppana, M., Pupi, A., & de Leon, M. J. (2005) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-005-1956-z · Cited by 81
“As a reference region for normalization of the regional ROI MRglc data, pons MRglc was sampled at the center of a mid pontine slice at the level of the middle cerebral peduncles with a 16×16 mm box [14] and was used to adjust for between-subject variations in the global MRglc [50].”
Functional O-GlcNAc modifications: Implications in molecular regulation and pathophysiology
Vaidyanathan, K., Durning, S. P., & Wells, L. (2014) · Critical Reviews in Biochemistry and Molecular Biology · doi:10.3109/10409238.2014.884535 · Cited by 81
“Considering the accelerated decline of glucose utilization in the Alzheimer’s disease brain (Heiss et al., 1991; McGeer et al., 1989, 1990; Minoshima et al., 1995, Smith et al., 1992), many groups have investigated the role O-GlcNAylation plays in disease progression.”
Background2- 18 F-fluoro-2-deoxyglucose positron emission tomography in delirium
Haggstrom, L. R., Nelson, J. A., Wegner, E. A., & Caplan, G. A. (2017) · Journal of Cerebral Blood Flow & Metabolism · doi:10.1177/0271678x17701764 · Cited by 78
Ishii, K., Kono, A. K., Sasaki, H., Miyamoto, N., Fukuda, T., Sakamoto, S., & Mori, E. (2006) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-005-0015-0 · Cited by 75
“[23] reported the utility of using the pons as a reference in an FDG PET study of patients with AD.”
Probable diffuse Lewy body disease presenting as REM sleep behavior disorder
Turner, R. S., Chervin, R. D., Frey, K. A., Minoshima, S., & Kuhl, D. E. (1997) · Neurology · doi:10.1212/wnl.49.2.523 · Cited by 73
Self-citationClinical application of positron emission tomography for diagnosis of dementia
Ishii, K. (2002) · Annals of Nuclear Medicine · doi:10.1007/bf02988628 · Cited by 72
Buck, B. H. (1997) · Brain · doi:10.1093/brain/120.7.1229 · Cited by 73
Jin, N., Wu, Q., Yin, X., Zhang, L., Iqbal, K., Grundke, I., Gong, C., & Liu, F. (2013) · Nucleic Acids Research · doi:10.1093/nar/gks1227 · Cited by 68
Wirth, M., Oh, H., Mormino, E. C., Markley, C., Landau, S. M., & Jagust, W. J. (2013) · Alzheimer s & Dementia · doi:10.1016/j.jalz.2012.10.012 · Cited by 70
“The native space realigned images were summed to create one FDG scan that was then intensity normalized to the pons, expressing preserved metabolism in AD patients [31].”
MethodImaging Alzheimer's disease: clinical applications
Minoshima, S. (2003) · Neuroimaging Clinics of North America · doi:10.1016/s1052-5149(03)00099-6 · Cited by 65
“In comparison, the overall sensitivity and specificity of retrospective or case series studies without autopsy confirmation for the differentiation of AD from normal subjects or non-Alzheimer type dementia (see references [72,73,90,105–115]) are 85%.”
BackgroundSelf-citationCatafau, A. M., Bullich, S., Seibyl, J. P., Barthel, H., Ghetti, B. F., Leverenz, J. B., Ironside, J. W., Schulz‐Schaeffer, W., Hoffmann, A., & Sabri, O. (2016) · Journal of Nuclear Medicine · doi:10.2967/jnumed.115.171652 · Cited by 66
“Whereas the pons has similar blood flow characteristics to the cerebral cortex (27), supporting its use as a reference region in brain 18FFDG and 18F-flutemetamol PET scans, this is not the case for the subcortical white matter (23,28).”
BackgroundCiarmiello, A., Giovacchini, G., Orobello, S., Bruselli, L., Elifani, F., & Squitieri, F. (2012) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-012-2114-z · Cited by 63
“The pons was chosen for normalization of the data because it is not usually affected in HD or in other neurodegenerative diseases [20].”
MethodDiagnostic utility of ASL‐MRI and FDG‐PET in the behavioral variant of FTD and AD
Tosun, D., Schuff, N. W., Rabinovici, G. D., Ayakta, N., Miller, B. L., Jagust, W., Kramer, J. H., Weiner, M. W., & Rosen, H. J. (2016) · Annals of Clinical and Translational Neurology · doi:10.1002/acn3.330 · Cited by 65
“Briefly, FDG-PET frames were summed and standard uptake volume ratios (SUVR) were calculated by normalizing the summed FDG image to mean activity in the pons for each subject.(42) First imaging frames of ASL-MRI and FDG-PET data were coregistered to the subject’s structural MRI using boundary-based registration.”
MethodLehmann, M., Ghosh, P., Madison, C. A., Karydas, A., Coppola, G., O’Neil, J. P., Huang, Y., Miller, B. L., Jagust, W., & Rabinovici, G. D. (2013) · Journal of Neurology Neurosurgery & Psychiatry · doi:10.1136/jnnp-2013-305858 · Cited by 61
Choo, I. H., Lee, D. Y., Youn, J. C., Jhoo, J. H., Kim, K. W., Lee, D. S., Lee, J. S., & Woo, J. I. (2007) · Alzheimer Disease & Associated Disorders · doi:10.1097/wad.0b013e3180687418 · Cited by 62
“Figure 3 illustrates the correlation between CDR-SOB score and normalized glucose metabolism at PCC in AD. r 2007 Lippincott Williams & Wilkins 79”
MethodInfluentialRodriguez‐Vieitez, E., Leuzy, A., Chiotis, K., Saint‐Aubert, L., Wall, A. E., & Nordberg, A. K. (2016) · Journal of Cerebral Blood Flow & Metabolism · doi:10.1177/0271678x16645593 · Cited by 61
“Although consensus has yet to be reached as to which reference region is most suitable for normalisation of [(18)F]FDG SUV images, the pons has frequently been selected due to it being purported to be the brain region that is least affected, from a metabolic standpoint, in AD.(33) The cerebellar cortex was used in the…”
MethodInfluentialDissociation of Down syndrome and Alzheimer's disease effects with imaging
Matthews, D. C., Lukic, A. S., Andrews, R. D., Marendic, B., Brewer, J. B., Rissman, R. A., Mosconi, L., Strother, S. C., Wernick, M. N., Mobley, W. C., et al. (2016) · Alzheimer s & Dementia Translational Research & Clinical Interventions · doi:10.1016/j.trci.2016.02.004 · Cited by 59
“In AD, a characteristic pattern of glucose hypometabolism emerges in hippocampus and posterior cingulate, expands to temporo-parietal regions, and gradually affects most cortical tissue, whereas pons, cerebellum, and motor and visual cortices are relatively preserved [4–6].”
BackgroundBorghammer, P., Aanerud, J., & GJEDDE, A. H. (2009) · NeuroImage · doi:10.1016/j.neuroimage.2009.03.021 · Cited by 58
Lange, C., Suppa, P., Frings, L., Brenner, W., Spies, L., Buchert, R., & Initiative, A. D. N. (2015) · Journal of Alzheimer s Disease · doi:10.3233/jad-150814 · Cited by 58
The use of PIB-PET as a dual pathological and functional biomarker in AD
Forsberg, A., Engler, H., Blomquist, G., Långström, B., & Nordberg, A. K. (2011) · Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease · doi:10.1016/j.bbadis.2011.11.006 · Cited by 59
“To account for global differences between patients the CMRglc data was normalised to the pons, a region with quite stable glucose metabolism during disease progression [25].”
Glucose metabolism and PIB binding in carriers of a His163Tyr presenilin 1 mutation
Schöll, M., Almkvist, O., Axelman, K., Stefanova, E. D., Wall, A. E., Westman, E., Långström, B., Lannfelt, L., Graff, C., & Nordberg, A. K. (2009) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2009.08.016 · Cited by 57
Ottoy, J., Verhaeghe, J. A. J., Niemantsverdriet, E., Roeck, E. E. D., Wyffels, L., Ceyssens, S. K., Broeckhoven, C. V., Engelborghs, S., Stroobants, S. G., & Staelens, S. G. (2019) · Alzheimer s & Dementia · doi:10.1016/j.jalz.2019.05.010 · Cited by 56
“On the other hand, for FDG PET, we selected the pons as an alternative reference region based on previous literature [41].”
Haense, C., Büerger, K., Kalbe, E., Drzezga, A. E., Teipel, S. J., Markiewicz, P. J., Herholz, K., Heiß, W.-D., & Hampel, H. J. (2008) · European Journal of Neurology · doi:10.1111/j.1468-1331.2008.02274.x · Cited by 54
“Intensity normalization was performed by dividing the mean value of each VOI by the mean value of a VOI both of the right and the left pons, which was used as the reference region for glucose metabolism [33].”
MethodMehranian, A., Arabi, H., & Zaidi, H. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2016.01.060 · Cited by 53
“In neurological studies, it is common practice to normalize PET images with respect to a reference region in the brain, such as the pons (located in brainstem) (Minoshima et al., 1995).”
Brain imaging of cognitively normal individuals with 2 parents affected by late-onset AD
Mosconi, L., Murray, J., Tsui, W. H., Li, Y., Spector, N. C., Goldowsky, A. M., Williams, S., Osorio, R. S., McHugh, P. F., Glodzik, L., et al. (2014) · Neurology · doi:10.1212/wnl.0000000000000181 · Cited by 51
“ric standardized uptake value ratio images were generated by normalizing PiB uptake by cerebellar gray matter (GM) uptake(21) and FDG by pons activity.(22) MRIs were segmented into GM,”
MethodMosconi, L., Tsui, W. H., Rusinek, H., Santi, S. D., Li, Y., Wang, G., Pupi, A., Fowler, J. S., & de Leon, M. J. (2007) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-007-0406-5 · Cited by 53
“PON was chosen as the reference region to adjust for between-subject variations in the global CMRglc because it was shown to be the region least affected by CMRglc reductions in AD [ 29 ].”
BackgroundMethodInfluentialGuenther, T., Schönknecht, P., Becker, G., Olbrich, S., Sander, C., Hesse, S., Meyer, P., Luthardt, J., Hegerl, U., & Sabri, O. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2011.01.059 · Cited by 47
“Best preserved unbiased regions in patients with AD as compared to same aged healthy controls were the pons and cerebellum (Kushner et al., 1987; Minoshima et al., 1995), and the cerebellar intensity is more reliable and easy to determine than the pontine intensity from a [18F] FDG-PET image.”
InfluentialLimbic system perfusion in Alzheimer's disease measured by MRI-coregistered HMPAO SPET
Callen, D. J. A., Black, S. E., & Caldwell, C. B. (2002) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-002-0816-3 · Cited by 48
“Although other regions, such as the occipital lobes [22] and pons [ 23 ], have been suggested as alternatives to the cerebellum, these regions are not uncommonly affected in AD (e.g.”
BackgroundNeural Correlates of the Clock Drawing Test Performance in Alzheimer’s Disease: A FDG-PET Study
Lee, D. Y., Seo, E. H., Choo, I. H., Kim, S. G., Lee, J. S., Lee, D. S., Jhoo, J. H., Kim, K. W., Youn, J. C., & Woo, J. I. (2008) · Dementia and Geriatric Cognitive Disorders · doi:10.1159/000161055 · Cited by 48
“An affine transformation was performed to determine the 12 optimal parameters essential for registering the brain on the template. Subtle differences between the transformed image and the template were removed by the nonlinear registration method, using the weighted sum of predefined smooth basis functions used in a d…”
MethodBlanc‐Durand, P., Khalifé, M., Sgard, B., Kaushik, S. S., Soret, M., Tiss, A., Fakhri, G. E., Habert, M., Wiesinger, F., & Kas, A. (2019) · PLoS ONE · doi:10.1371/journal.pone.0223141 · Cited by 47
Dukart, J., Perneczky, R., Förster, S., Barthel, H., Diehl‐Schmid, J., Draganski, B., Obrig, H., Santarnecchi, E., Drzezga, A. E., Fellgiebel, A., et al. (2013) · PLoS ONE · doi:10.1371/journal.pone.0055415 · Cited by 47
Verger, A., Doyen, M., Campion, J., & Guedj, É. (2021) · EJNMMI Research · doi:10.1186/s13550-021-00771-0 · Cited by 47
“, intensity normalization based on the whole-brain, and that related to specific brain areas, such as the cerebellum [4] and the pons [5], have been proposed, especially for the diagnosis of neurodegenerative disorders.”
BackgroundKrell‐Roesch, J., Ruider, H., Lowe, V. J., Stokin, G. B., Pink, A., Roberts, R. O., Mielke, M. M., Knopman, D. S., Christianson, T. J. H., Machulda, M. M., et al. (2016) · Journal of Alzheimer s Disease · doi:10.3233/jad-160326 · Cited by 48
“These two regions of references were chosen because they have preserved glucose metabolism in AD [29].”
BackgroundOssenkoppele, R., Madison, C. M., Oh, H., Wirth, M., van Berckel, B. N. M., & Jagust, W. J. (2013) · Cerebral Cortex · doi:10.1093/cercor/bht076 · Cited by 45
“The native space realigned images were summed to create one [(18)F]FDG image that was then intensity normalized to the pons, as pontine glucose metabolism is known to be preserved in AD patients (Minoshima et al. 1995).”
Sleep moderates the relationship between amyloid beta and memory recall
Wilckens, K. A., Tudorascu, D., Snitz, B. E., Price, J. C., Aizenstein, H. J., López, O. L., Erickson, K. I., Lopresti, B. J., Laymon, C. M., Minhas, D. S., et al. (2018) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2018.07.011 · Cited by 46
“Analysis of the PiB-PET data was performed on time-averaged images in a manner consistent with established methods (Herholz et al., 2002; Minoshima et al., 1995; Ziolko et al., 2006).”
MethodBuchert, R., Wilke, F., Chakrabarti, B., Martin, B., Brenner, W., Mester, J., & Clausen, M. (2005) · Journal of Neuroimaging · doi:10.1111/j.1552-6569.2005.tb00335.x · Cited by 51
“This problem of proportional scaling has been recognized before,(9) and a number of alternative scaling methods have been proposed by different authors.(10-17) These methods reduce underestimation of local changes,(18) but they are either restricted to certain experimental conditions not available in single-subject an…”
MethodBuchert, R. (2005) · Journal of Neuroimaging · doi:10.1177/1051228405280169 · Cited by 40
Metadata
- Authors
- Minoshima, S., Frey, K. A., Foster, N. L., & Kuhl, D. E.
- Affiliations
- University of Michigan (US)
- Venue
- Journal of Computer Assisted Tomography
- Published
- 1995-07
- Volume
- 19
- Issue
- 4
- Pages
- 541-547
- ISSN
- 0363-8715 (ISSN-L)
- OpenAlex
- W1964006251
- Cited by
- 252
- References
- 0
- Citations by year
- 2026: 3 · 2025: 6 · 2024: 4 · 2023: 2 · 2022: 8 · 2021: 9 · 2020: 16 · 2019: 9 · 2018: 9 · 2017: 3 · 2016: 13 · 2015: 10 · 2014: 13 · 2013: 11 · 2012: 4
- FWCI
- 2.48
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Computer Assisted Tomography (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Institutes of Health (5r01ns024896-15)
- National Institute of Neurological Disorders and Stroke (R01 NS24896)
- Topics
- Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Medical Imaging Techniques and Applications
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Alzheimer's disease research and treatments
- Keywords
- Alzheimer's disease, glucose metabolism, passive optical networks, 18F-FDG PET, thalamus, putamen, cerebellum, sensorimotor cortex, visual cortex
- MeSH terms
- Aged, Alzheimer Disease, Brain, Deoxyglucose, Energy Metabolism, Fluorine Radioisotopes, Glucose, Humans, Middle Aged, Pons, Tomography, Emission-Computed, Case-Control Studies, Fluorodeoxyglucose F18
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
