Cited by 252Dementia and Cognitive Impairment ResearchMedical Imaging Techniques and ApplicationsAlzheimer's disease research and treatments

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Preserved Pontine Glucose Metabolism in Alzheimer Disease: A Reference Region for Functional Brain Image (PET) Analysis

Minoshima, Satoshi, Frey, Kirk A., Foster, Norman L., Kuhl, David E.·1995·Journal of Computer Assisted Tomography

DOI 10.1097/00004728-199507000-00006

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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.

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Items 101–200 of 252

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Murray, J., Tsui, W. H., Li, Y., McHugh, P. F., Williams, S., Cummings, M., Pirraglia, E., Sólnes, L. B., Osorio, R. S., Glodzik, L., et al. (2014) · Advances in Molecular Imaging · doi:10.4236/ami.2014.42003 · Cited by 39
“ROIs included parietal, temporal, medial and pre-frontal cortex, posterior cingulate cortex (PCC), precuneus, and angular gyrus [1]-[7] [11] [27] [30].”
BackgroundMethodSelf-citation
Brain Regional Glucose Metabolism, Neuropsychiatric Symptoms, and the Risk of Incident Mild Cognitive Impairment: The Mayo Clinic Study of Aging
Krell‐Roesch, J., Syrjanen, J. A., Vassilaki, M. E., Lowe, V. J., Vemuri, P., Mielke, M. M., Machulda, M. M., Stokin, G. B., Christianson, T. J. H., Kremers, W. K., et al. (2020) · American Journal of Geriatric Psychiatry · doi:10.1016/j.jagp.2020.06.006 · Cited by 39
Effect of sample size for normal database on diagnostic performance of brain FDG PET for the detection of Alzheimer's disease using automated image analysis
Chen, W.-P., Samuraki, M., Yanase, D., Shima, K., Takeda, N., Ono, K., Yoshita, M., Nishimura, S., Yamada, M., & Matsunari, I. (2008) · Nuclear Medicine Communications · doi:10.1097/mnm.0b013e3282f3fa76 · Cited by 39
Neurotrophins and Alzheimer's disease: Beyond the cholinergic neurons
Knüsel, B., & Gao, H. (1996) · Life Sciences · doi:10.1016/0024-3205(96)00193-2 · Cited by 39
Metabolic brain networks in aging and preclinical Alzheimer's disease
Arnemann, K. L., Stöber, F., Narayan, S., Rabinovici, G. D., & Jagust, W. J. (2017) · NeuroImage Clinical · doi:10.1016/j.nicl.2017.12.037 · Cited by 36
“Compared to other proposed FDG-PET reference regions, the pons has stable FDG tracer uptake across the aging and Alzheimer's disease spectrums (Minoshima et al., 1995).”
Background
The American Psychiatric Publishing Textbook of Alzheimer Disease and Other Dementias
(2009) · American Psychiatric Association Publishing eBooks · doi:10.1176/appi.books.9781585628940 · Cited by 40
Multi-contrast attenuation map synthesis for PET/MR scanners: assessment on FDG and Florbetapir PET tracers
Burgos, N., Cardoso, M. J., Thielemans, K., Marc Modat, A., Dickson, J. C., Schott, J. M., Atkinson, D., Arridge, S., Hutton, B. F., & Sebastien Ourselin, A. (2015) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-015-3082-x · Cited by 37
“For the FDG PETs, the mean uptake value in the pons [19] was used to normalise the PET images of each subject, thus allowing for a comparable range of values.”
BackgroundMethod
Frontal Dysfunction Underlies Depression in Mild Cognitive Impairment: A FDG-PET Study
Lee, H. S., Choo, I. H., Lee, D. Y., Kim, J. W., Seo, E. H., Kim, S. G., Park, S. Y., Shin, J. H., Kim, K. W., & Woo, J. I. (2010) · Psychiatry Investigation · doi:10.4306/pi.2010.7.3.208 · Cited by 38
Computer-assisted diagnostic system for neurodegenerative dementia using brain SPECT and 3D-SSP
Ishii, K., Kanda, T., Uemura, T., Miyamoto, N., Yoshikawa, T., Shimada, K., Ohkawa, S., & Minoshima, S. (2009) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-008-1051-3 · Cited by 37
“Using the pons as a reference in an FDGPET study of patients with AD is useful [25], but in SPECT images, because the pons is a small structure and exists in the central brain, attenuation correction is not perfect; therefore the pons may not be a suitable reference region for SPECT analysis.”
MethodSelf-citation
Time Course of Glucose Metabolism in Relation to Cognitive Performance and Postmortem Neuropathology in Met146Val PSEN1 Mutation Carriers
Schöll, M., Almkvist, O., Bogdanović, N., Wall, A. E., Långström, B., Viitanen, M. H., & Nordberg, A. K. (2011) · Journal of Alzheimer s Disease · doi:10.3233/jad-2011-101563 · Cited by 35
“To correct for intersubject variations in global CMRglc, ROI data were normalized to pons MRglc, a region that is scarcely affected in AD [8].”
Method
Data-driven identification of intensity normalization region based on longitudinal coherency of 18F-FDG metabolism in the healthy brain
Zhang, H., Wu, P., Ziegler, S. I., Guan, Y., Wang, Y., Ge, J., Schwaiger, M., Huang, S., Zuo, C., Förster, S., et al. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2016.09.031 · Cited by 33
“Global mean scaling (intensity normalization to the global mean value in the whole brain) is the default recommendation within the SPM framework and is widely employed in neuroimaging studies (Minoshima et al., 1995; Ma et al., 2007).”
Hypometabolism of the posterior cingulate cortex is not restricted to Alzheimer's disease
Scheltens, N., van der Weijden, K., Adriaanse, S., van Assema, D. V., Oomen, P., Krudop, W., Lammertsma, A., Barkhof, F., Koene, T., Teunissen, C., et al. (2018) · NeuroImage: Clinical · doi:10.1016/j.nicl.2018.05.024 · Cited by 29
“Larger scatter in pons-normalised data could be the result of relative better preservation of glucose metabolism in the pons compared with cerebellum in AD (Minoshima et al., 1995).”
Effects of Image Resolution on Autoradiographic Measurements of Posterior Cingulate Activity in PDAPP Mice: Implications for Functional Brain Imaging Studies of Transgenic Mouse Models of Alzheimer's Disease
Valla, J. E., Chen, K., Berndt, J. D., Gonzalez-Lima, F., Cherry, S. R., Games, D., & Reiman, E. M. (2002) · NeuroImage · doi:10.1006/nimg.2002.1080 · Cited by 32
“Fluorodeoxyglucose (FDG) positron emission tomography (PET) studies find that persons with Alzheimer’s disease (AD) characteristically show preferential and progressive reductions in regional measurements of the cerebral metabolic rate for glucose or FDG uptake ( Minoshima et al., 1994, 1995, 1997; Mielke et al., 1994…”
Background
Insular hypoperfusion correlates with the severity of delusions in individuals with Alzheimer's disease
Matsuoka, T., Narumoto, J., Shibata, K., Okamura, A., Nakamura, K., Okuyama, C., Nishimura, T., & Fukui, K. (2010) · Dementia and Geriatric Cognitive Disorders · doi:10.1159/000295115 · Cited by 32
“Moreover, the regional metabolic rate in the cerebellum can be decreased through the mechanism of diaschisis even in mild AD [”
Background
Hypermetabolism in the hippocampal formation of cognitively impaired patients indicates detrimental maladaptation
Apostolova, I. I., Lange, C., Maeurer, A., Suppa, P., Spies, L., Grothe, M. J., Nierhaus, T., Fiebach, J. B., Steinhagen‐Thiessen, E., & Buchert, R. (2018) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2018.01.002 · Cited by 32
“The pons ROI of the “TD Lobes” atlas in the WFU PickAtlas was used for this purpose (after transformation to patient space; Minoshima et al., 1995).”
One-Year Change in Cerebral Glucose Metabolism in Patients With Alzheimer's Disease
Hirono, N., Hashimoto, M., Ishii, K., Kazui, H., & Mori, E. (2004) · Journal of Neuropsychiatry · doi:10.1176/jnp.16.4.488 · Cited by 34
Association between FDG uptake, CSF biomarkers and cognitive performance in patients with probable Alzheimer’s disease
Arlt, S., Brassen, S., Jahn, H., Wilke, F., Eichenlaub, M., Apostolova, I. I., Wenzel, F., Thiele, F. O., Young, S., & Buchert, R. (2009) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-009-1063-7 · Cited by 30
“However, a subtle reduction in pontine glucose metabolism at advanced stages of AD cannot be ruled out [21].”
Influential
PET evidence of preclinical cerebellar amyloid plaque deposition in autosomal dominant Alzheimer’s disease-causing Presenilin-1 E280A mutation carriers
Ghisays, V., Lopera, F. J., Goradia, D. D., Protas, H. D., Malek‐Ahmadi, M. H., Chen, Y., Devadas, V., Luo, J., Lee, W., Baena, A. Y., et al. (2021) · NeuroImage Clinical · doi:10.1016/j.nicl.2021.102749 · Cited by 30
“However, decades before amyloid PET tracers, functional tracers such as FDG (2-[18F]fluoro-2Deoxy-D-glucose) used pons as an alternative reference region in imaging studies (Greve et al., 2016; Minoshima et al., 1995).”
Dementia With Lewy Bodies Studied With Positron Emission Tomography
Cordery, R. J., Tyrrell, P. J., Lantos, P. L., & Rossor, M. N. (2001) · Archives of Neurology · doi:10.1001/archneur.58.3.505 · Cited by 28
Optimized Data Preprocessing for Multivariate Analysis Applied to 99mTc-ECD SPECT Data Sets of Alzheimer's Patients and Asymptomatic Controls
Merhof, D., Markiewicz, P., Platsch, G., Declerck, J., Weih, M., Kornhuber, J., Kuwert, T., Matthews, J., & Herholz, K. (2011) · Journal of Cerebral Blood Flow and Metabolism · doi:10.1038/jcbfm.2010.112 · Cited by 29
Brain 18FDG-PET pattern in patients with alcohol-related cognitive impairment
Clergue‐Duval, V., Questel, F., Azuar, J., Paquet, C., Cognat, E., Amami, J., Queneau, M., Dereux, A., Barré, T., Bellivier, F., et al. (2019) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-019-04487-1 · Cited by 29
Tracer‐specific reference tissues selection improves detection of 18F‐FDG , 18F ‐florbetapir, and 18F ‐flortaucipir PET SUVR changes in Alzheimer's disease
Li, Y., Ng, Y. L., Paranjpe, M. D., Ge, Q., Gu, F., Li, P., Yan, S., Lu, J., Wang, X., Zhou, Y., et al. (2022) · Human Brain Mapping · doi:10.1002/hbm.25774 · Cited by 25
“Minoshima et al. (1995) evaluated pons and other reference tissues in AD by observing the preservation of glucose metabolism.”
DSC Perfusion MRI–Derived Fractional Tumor Burden and Relative CBV Differentiate Tumor Progression and Radiation Necrosis in Brain Metastases Treated with Stereotactic Radiosurgery
Kuo, F., Ng, N. N., Nagpal, S., et al. (2022) · American Journal of Neuroradiology · doi:10.3174/ajnr.a7501 · Cited by 26
“SUVmax ratios were then produced by normalizing the SUV maps to the pons, which was chosen as a reference area because its metabolism and volume are least affected by disease.(11) For consistency, the CBFmax of the lesion was also used for ASL, similar to use in prior studies of quantification,(12) and normalized to t…”
Method
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
“and basal ganglia [11], the cerebellum [7], the pons [1,12–14], and the combined cerebellum, vermis and pons [15].”
Evaluation of the early-phase [18F]AV45 PET as an optimal surrogate of [18F]FDG PET in ageing and Alzheimer’s clinical syndrome
Vanhoutte, M., Landeau, B., Sherif, S., Sayette, V. D. L., Dautricourt, S., Abbas, A., Manrique, A., Chocat, A., & Chételat, G. (2021) · NeuroImage Clinical · doi:10.1016/j.nicl.2021.102750 · Cited by 26
“, 2003), which seems to be metabolically least affected in AD (Minoshima et al., 1995) and more stable for lAV45 in MCI (S.”
An efficient combination of quadruple biomarkers in binary classification using ensemble machine learning technique for early onset of Alzheimer disease
Kumari, R., Nigam, A., & Pushkar, S. (2022) · Neural Computing and Applications · doi:10.1007/s00521-022-07076-w · Cited by 26
“Here, the reference region is taken to be Pons for FDG-PET images [41].”
Diagnosis of suspected Alzheimer?s disease is improved by automated analysis of regional cerebral blood flow
Tang, B., Minoshima, S., George, J., Robert, A. R., Swine, C., Laloux, P., & Borght, T. V. (2004) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-004-1597-7 · Cited by 25
Self-citation
Evaluation of Standardized Uptake Value to Assess Cerebral Glucose Metabolism
Yamaji, S., Ishii, K., Sasaki, M., et al. (2000) · Clinical Nuclear Medicine · doi:10.1097/00003072-200001000-00003 · Cited by 24
Imaging Neuroinflammation: Quantification of Astrocytosis in a Multitracer PET Approach
Rodriguez‐Vieitez, E., & Nordberg, A. K. (2018) · Methods in molecular biology · doi:10.1007/978-1-4939-7704-8_16 · Cited by 24
Plasma Neurofilament Light Chain Levels Are Associated With Cortical Hypometabolism in Alzheimer Disease Signature Regions
Mayeli, M., Mirshahvalad, S. A., Aghamollaii, V., Tafakhori, A., Abdolalizadeh, A., Rahmani, F., & Initiative, A. D. N. (2019) · Journal of Neuropathology & Experimental Neurology · doi:10.1093/jnen/nlz054 · Cited by 23
“Energy metabolism in the pons has been conventionally used to normalize measurement of glucose uptake in each voxel as it is reported to be well preserved in AD (17).”
Investigating the clinico-anatomical dissociation in the behavioral variant of Alzheimer disease
Singleton, E. H., Pijnenburg, Y. A. L., Sudre, C. H., Groot, C., Kochova, E., Barkhof, F., Joie, R. L., Rosen, H. J., Seeley, W. W., Miller, B. L., et al. (2020) · Alzheimer s Research & Therapy · doi:10.1186/s13195-020-00717-z · Cited by 23
Functional Neuroanatomical Correlates of The Frontal Assessment Battery Performance in Alzheimer Disease
Lee, J. H., Byun, M. S., Sohn, B. K., Choe, Y. M., Yi, D., Han, J. Y., Choi, H. J., Baek, H., Woo, J. I., & Lee, D. Y. (2015) · Journal of Geriatric Psychiatry and Neurology · doi:10.1177/0891988715573533 · Cited by 22
“Although VF and SCWT are known to mainly reflect frontal functions,25,26 CP performance correlated with bilateral temporal and precuneus and right temporoparietal functions,27 and WLM and WLRc were associated with the functions of the left temporoparietal and posterior cingluate cortices as well as the frontal regions…”
MethodInfluential
Reduced penetrance of the PSEN1 H163Y autosomal dominant Alzheimer mutation: a 22-year follow-up study
Þórðardóttir, S., Rodriguez‐Vieitez, E., Almkvist, O., Ferreira, D., Saint‐Aubert, L., Ståhlbom, A. K., Thonberg, H., Schöll, M., Westman, E., Wall, A. E., et al. (2018) · Alzheimer s Research & Therapy · doi:10.1186/s13195-018-0374-y · Cited by 23
“value ratio (SUVr) units with the pons as a reference region because this region was found to be a reliable reference for metabolism [44] and amyloid-β quantification [45] in both sporadic and familial Alzheimer’s disease.”
Relationships between amyloid levels, glucose metabolism, morphologic changes in the brain and clinical status of patients with Alzheimer’s disease
Thientunyakit, T., Sethanandha, C., Muangpaisan, W., Chawalparit, O., Arunrungvichian, K., Siriprapa, T., Vichianin, Y., Kamal, S., Suppasilp, C., Thongpraparn, T., et al. (2020) · Annals of Nuclear Medicine · doi:10.1007/s12149-020-01453-y · Cited by 21
Statistical maps of cerebral blood flow deficits in Alzheimer’s disease
Johannsen, P., Jakobsen, J., & GJEDDE, A. H. (2000) · European Journal of Neurology · doi:10.1046/j.1468-1331.2000.00088.x · Cited by 22
The associations between synaptic density and “A/T/N” biomarkers in Alzheimer’s disease: An 18 F-SynVesT-1 PET/MR study
Li, J., Huang, Q., Qi, N., He, K., Li, S., Huang, L., Pan, F., Ren, S., Hua, F., Huang, Y. H., et al. (2024) · Journal of Cerebral Blood Flow & Metabolism · doi:10.1177/0271678x241230733 · Cited by 19
Nigrostriatal dopamine transporter availability, and its metabolic and clinical correlates in Parkinson’s disease patients with impulse control disorders
Navalpotro‐Gómez, I., Dacosta‐Aguayo, R., Molinet-Dronda, F., Martín‐Bastida, A., Botas-Peñin, A., Jiménez‐Urbieta, H., Delgado‐Alvarado, M., Gago, B., Quiroga‐Varela, A., & Rodríguez-Oroz, M. C. (2019) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-019-04396-3 · Cited by 22
Simultaneous FDG-PET/MRI detects hippocampal subfield metabolic differences in AD/MCI
Carlson, M. L., DiGiacomo, P., Fan, A. P., Goubran, M., Khalighi, M. M., Chao, S. Z., Vasanawala, M., Wintermark, M., Mormino, E. C., Zaharchuk, G., et al. (2020) · Scientific Reports · doi:10.1038/s41598-020-69065-0 · Cited by 23
Metabolic Connectivity as Index of Verbal Working Memory
Zou, N., Chételat, G., Baydoğan, M. G., Li, J., Fischer, F. U., Titov, D., Dukart, J., Fellgiebel, A., Schreckenberger, M., & Yakushev, I. Y. (2015) · Journal of Cerebral Blood Flow & Metabolism · doi:10.1038/jcbfm.2015.40 · Cited by 20
An Automated Pipeline for the Analysis of PET Data on the Cortical Surface
Marcoux, A., Burgos, N., Bertrand, A., Teichmann, M., Routier, A., Wen, J., Samper‐Gonzàlez, J., Bottani, S., Durrleman, S., Habert, M., et al. (2018) · Frontiers in Neuroinformatics · doi:10.3389/fninf.2018.00094 · Cited by 22
“For FDG PET images, the reference region used is the pons (Minoshima et al., 1995a).”
Method
Functional neuroanatomical correlates of the executive clock drawing task (CLOX) performance in Alzheimer’s disease: A FDG-PET study
Shon, J. M., Lee, D. Y., Seo, E. H., et al. (2013) · Neuroscience · doi:10.1016/j.neuroscience.2013.05.008 · Cited by 19
“The glucose metabolism value of each voxel was normalized for the pontine value, which was extracted for each scan, as glucose metabolism in the pons tends to be relatively preserved in AD (Minoshima et al., 1995).”
Method
Molecular Imaging and the Neuropathologies of Parkinson’s Disease
Cumming, P. D., & Borghammer, P. (2011) · Current topics in behavioral neurosciences · doi:10.1007/7854_2011_165 · Cited by 18
Alteration patterns of brain glucose metabolism: comparisons of healthy controls, subjective memory impairment and mild cognitive impairment
Song, I.-U., Choi, E. K., Oh, J. K., Chung, Y.-A., & Chung, S.-W. (2016) · Acta Radiologica · doi:10.1177/0284185114566088 · Cited by 17
“With an in-house Matlab-based program, the glucose metabolism value of each voxel was normalized to the pontine value, since glucose metabolism in the pons tends to be relatively preserved in AD (14).”
Method
Increased white matter glycolysis in humans with cerebral small vessel disease
Brier, M. R., Blazey, T., Raichle, M. E., Morris, J. C., Benzinger, T. L. S., Vlassenko, A. G., Snyder, A. Z., & Goyal, M. S. (2022) · Nature Aging · doi:10.1038/s43587-022-00303-y · Cited by 16
Differentiating between Normal Aging, Mild Cognitive Impairment, and Alzheimer’s disease with FDG-PET: Effects of Normalization Region and Partial Volume Correction Method
Bauer, C. M. (2013) · Journal of Alzheimer’s Disease & Parkinsonism · doi:10.4172/2161-0460.1000113 · Cited by 17
“[4] found significant disease-related differences in the thalamus; however, this was without any partial volume correction making it difficult to discern whether this was due to changes in metabolism, volume, or both.”
BackgroundResult
Cortical thickness, brain metabolic activity, and in vivo amyloid deposition in asymptomatic, middle-aged offspring of patients with late-onset Alzheimer's disease
Duarte-Abritta, B., Villarreal, M. F., Abulafia, C., Loewenstein, D., Curiel, R. E., Castro, M. N., Surace, E. I., Sánchez, S. M., Vigo, D. E., Vázquez, S., et al. (2018) · Journal of Psychiatric Research · doi:10.1016/j.jpsychires.2018.10.008 · Cited by 17
FDG-PET assessment of the locus coeruleus in Alzheimer’s disease
Liu, K. Y., Acosta‐Cabronero, J., Hong, Y. T., Yi, Y., Hämmerer, D., & Howard, R. J. (2021) · Neuroimage Reports · doi:10.1016/j.ynirp.2020.100002 · Cited by 17
“Hence, we normalized median ROI SUV values to both the cerebellar vermis and pons, as these have been the most widely used reference regions in past FDG-PET studies in Alzheimer ’ s disease (Meltzer et al., 1996; Minoshima et al., 1995; Nestor et al., 2003; Scheltens et al., 2018).”
Influence of the Apolipoprotein E Type 4 Allele on Cerebral Glucose Metabolism in Alzheimer's Disease Patients
Lee, K. U., Lee, J. S., Kim, K. W., Jhoo, J. H., Lee, D. Y., Yoon, J. C., Lee, H., Lee, D. S., Lee, M. C., & Woo, J. I. (2003) · Journal of Neuropsychiatry · doi:10.1176/jnp.15.1.78 · Cited by 15
“The count of each voxel was normalized to the pontine activity, under the assumption that energy metabolism in the pons is minimally affected in Alzheimer’s disease.(31) After spatial and count normalization, the significant difference in cerebral glucose metabolism between the APOE E4 andAPOEE4– groups was estimated…”
Method
Classification of Alzheimer’s Disease from 18F-FDG and 11C-PiB PET Imaging Biomarkers Using Support Vector Machine
Yang, B., Chen, J., Chou, W.-H., Huang, W.-S., Fuh, J., Liu, R., & Wu, C.-H. (2020) · Journal of Medical and Biological Engineering · doi:10.1007/s40846-020-00548-1 · Cited by 13
Interactions Between Neuropsychiatric Symptoms and Alzheimer's Disease Neuroimaging Biomarkers in Predicting Longitudinal Cognitive Decline
Pink, A., Krell‐Roesch, J., Syrjanen, J. A., Christenson, L. R., Lowe, V. J., Vemuri, P., Fields, J. A., Stokin, G. B., Kremers, W. K., Scharf, E. L., et al. (2023) · Psychiatric Research and Clinical Practice · doi:10.1176/appi.prcp.20220036 · Cited by 13
“SUVR was formed by the ratio of this AD signature ROI and two reference regions, namely the pons and the cerebellar vermis which have preserved glucose metabolism in AD (40).”
Method
Imaging Neuroinflammation: Quantification of Astrocytosis in a Multitracer PET Approach
Rodriguez‐Vieitez, E., Kumar, A., Malarte, M., Ioannou, K., Rocha, F. M., & Chiotis, K. (2024) · Methods in molecular biology · doi:10.1007/978-1-0716-3774-6_13 · Cited by 14
Region-specific association between basal blood insulin and cerebral glucose metabolism in older adults
Byun, M. S., Kim, H. J., Yi, D., Choi, H. J., Baek, H., Lee, J. H., Choe, Y. M., Lee, S. H., Ko, K., Sohn, B. K., et al. (2019) · NeuroImage Clinical · doi:10.1016/j.nicl.2019.101765 · Cited by 13
“Finally, intensity normalization was performed using the pons as the reference region (Ewers et al., 2014; Jack et al., 2012; Jagust et al., 2010; Kantarci et al., 2010; Minoshima et al., 1995; Walhovd et al., 2010a; Walhovd et al., 2010b), by applying the pons mask provided by the WFU PickAtlas (http://fmri.”
Feeling of presence in dementia with Lewy bodies is related to reduced left frontoparietal metabolism
Nicastro, N., Eger, A. F., Assal, F., & Garibotto, V. (2018) · Brain Imaging and Behavior · doi:10.1007/s11682-018-9997-7 · Cited by 13
The role of PET quantification in neurological imaging: FDG and amyloid imaging in dementia
Herholz, K. (2014) · Clinical and Translational Imaging · doi:10.1007/s40336-014-0073-z · Cited by 13
“The pons has been identified in one study [22] as the region that is least affected even at late stages of AD, but it is relatively small and located deep in the skull and is thus subject to potentially high measurement variation.”
Background
Comparing Fludeoxyglucose F18–PET Assessment of Regional Cerebral Glucose Metabolism and [11C]Dihydrotetrabenazine–PET in Evaluation of Early Dementia and Mild Cognitive Impairment
Albin, R. L., Koeppe, R. A., Burke, J. F., Giordani, B., Kilbourn, M. R., Gilman, S., & Frey, K. A. (2010) · Archives of Neurology · doi:10.1001/archneurol.2010.34 · Cited by 12
“The FDG and DTBZ K1 images were normalized to the mean VOI value obtained from the pons and cerebellar vermis.(65) These 2 regions were selected as the normalizing factor because they are structures known to be minimally involved in these disorders, enhancing the ability to detect regional cortical deficits by removal…”
MethodSelf-citation
Quantitative and clinical impact of MRI-based attenuation correction methods in [18F]FDG evaluation of dementia
Øen, S. K., Keil, T. M., Berntsen, E. M., Aanerud, J., Schwarzlmüller, T., Ladefoged, C. N., Karlberg, A. M., & Eikenes, L. (2019) · EJNMMI Research · doi:10.1186/s13550-019-0553-2 · Cited by 12
“Although glucose metabolism in the pons have been found to be least affected by dementia among several reference regions [26], the small size makes this region prone to bias and the surrounding inhomogeneous bone affects both attenuation and scatter [25].”
Background
Anomaly detection for the individual analysis of brain PET images
Burgos, N., Cardoso, M. J., Samper‐Gonzàlez, J., Habert, M., Durrleman, S., Sebastien Ourselin, A., & Colliot, O. (2021) · Journal of medical imaging · doi:10.1117/1.jmi.8.2.024003 · Cited by 12
“The pons was used for the FDG PET images 39 and the whole cerebellum for the Florbetapir PET images.”
Method
Towards an optimal reference region in single-photon emission tomography difference images in epilepsy
Boussion, N., Ryvlin, P., Isnard, J., et al. (2000) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s002590050021 · Cited by 12
Comparison of 18F-FDG PET and arterial spin labeling MRI in evaluating Alzheimer’s disease and amnestic mild cognitive impairment using integrated PET/MR
Bi, S., Yan, S., Chen, Z., Cui, B., Shan, Y., Yang, H., Qi, Z., Zhao, Z., Han, Y., & Lu, J. (2024) · EJNMMI Research · doi:10.1186/s13550-024-01068-8 · Cited by 11
“Furthermore, research findings by Li et al. revealed that the reference tissue pons ‐ based 18 F ‐ FDG SUVR exhibits superior sensitivity in identifying longitudinal alterations compared with the reference tissue cer- ebellum-and centrum semiovale-based 18 F ‐ FDG SUVR [29, 48–50].”
Method
Chemotherapy effects on brain glucose metabolism at restPreprint
Baudino, B., D’Agata, F., Castellano, G., Caroppo, P., Cauda, S., Parente, A., Manfredi, M., Geda, E., Orsi, L., Cauda, F., et al. (2011) · Nature Precedings · doi:10.1038/npre.2011.5637.1 · Cited by 11
“The pons was chosen on the basis of its relative stability an late involvement in neurodegenerative diseases such as Alzheimer disease [33], a finding leading other investigators to use it as reference region [11, 37, 57].”
BackgroundResult
Cerebellar metabolic reduction in Alzheimer's disease and data normalization.
Minoshima, S., Frey, K. A., & Kuhl, D. E. (1998) · PubMed · Cited by 11
Self-citation
Functional Neural Correlates of Semantic Fluency Task Performance in Mild Cognitive Impairment and Alzheimer’s Disease: An FDG-PET Study
Ahn, H., Yi, D., Chu, K., Joung, H., Lee, Y., Jung, G., Sung, K., Han, D., Lee, J. H., Byun, M. S., et al. (2021) · Journal of Alzheimer s Disease · doi:10.3233/jad-215292 · Cited by 11
Quantitative Analysis in Functional Brain Imaging
Laere, K. V., & Zaidi, H. (2006) · Springer eBooks · doi:10.1007/0-387-25444-7_14 · Cited by 10
Predicting cognitive decline from neuropsychiatric symptoms and Alzheimer's disease biomarkers: A machine learning approach to a population-based data
Shah, J., Krell‐Roesch, J., Forzani, E., Knopman, D. S., Jack, C. R., Petersen, R. C., Che, Y., Wu, T., & Geda, Y. E. (2025) · Journal of Alzheimer s Disease · doi:10.1177/13872877241306654 · Cited by 10
Correlations between Alzheimer’s Disease Cerebrospinal Fluid Biomarkers and Cerebral Glucose Metabolism after 12 Months of Phenserine Treatment
Nordberg, A. K., Kadir, A., Andreasen, N., Almkvist, O., Wall, A. E., Blennow, K., Långström, B., & Zetterberg, H. (2015) · Journal of Alzheimer s Disease · doi:10.3233/jad-132474 · Cited by 10
“The rCMRglc values were normalized to the pons value (ROI/ref) to allow inter- and intraindividual comparisons [39].”
Use of Positron Emission Tomography and Other Neuroimaging Techniques in the Diagnosis and Management of Alzheimer’s Disease and Dementia
Matchar, D. B., Kulasingam, S., McCrory, D. C., Mb, P., Rutschmann, O. T., Samsa, G. P., & De, S. (2001) · Cited by 8
Premotor and fronto-striatal mechanisms associated with presence hallucinations in dementia with Lewy bodies
Nicastro, N., Stripeikyte, G., Assal, F., Garibotto, V., & Blanke, O. (2021) · NeuroImage Clinical · doi:10.1016/j.nicl.2021.102791 · Cited by 9
Measurement of neurodegeneration using a multivariate early frame amyloid PET classifier
Matthews, D. C., Lukic, A. S., Andrews, R. D., Wernick, M. N., Strother, S. C., Schmidt, M. E., & Initiative, A. D. N. (2022) · Alzheimer s & Dementia Translational Research & Clinical Interventions · doi:10.1002/trc2.12325 · Cited by 8
“Regions in which metabolism is relatively preserved in AD, and thathavebeenusedasreferenceregionsinFDGanalyses 42 wereeval-uated including cerebellum, pons, and thalamus.”
Background
Computer-Assisted System for Diagnosis of Alzheimer Disease Using Data Base− Independent Estimation and Fluorodeoxyglucose− Positron-Emission Tomography and 3D-Stereotactic Surface Projection
Uemura, T., Ishii, K., Miyamoto, N., et al. (2011) · American Journal of Neuroradiology · doi:10.3174/ajnr.a2342 · Cited by 8
“In contrast, glucose metabolism in the primary sensorimotor cortices, primary visual cortices, basal ganglia, thalami, and the cerebellum is relatively preserved in AD.(4,5) In particular, a pattern of parietotemporal and posterior cingulate cortical hypometabolism is considered a reliable hallmark of AD.”
Background
Spatially Adaptive Varying Correlation Analysis for Multimodal Neuroimaging Data
Li, L., Kang, J., Lockhart, S. N., Adams, J. N., & Jagust, W. J. (2018) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2018.2857221 · Cited by 8
“and their use as reference for PET analysis has longstanding support [19]–[21].”
18F-FDG PET for Dementia Evaluation: Co-pathologies, New Diseases, and Its Roles in the Era of Antiamyloid Treatment
Thientunyakit, T., Muangpaisan, W., & Minoshima, S. (2025) · Seminars in Nuclear Medicine · doi:10.1053/j.semnuclmed.2025.04.007 · Cited by 8
“3,5 It normalizes the pixel values on FDG PET images to the value of a reference region (such as pons or cerebellum) producing FDG SUVR values, then compares to a database obtained from multiple normal or control subjects and expresses the regional alterations of the normalized FDG uptake as…”
Self-citation
Interactions Between Brain 18F-FDG PET Metabolism and Hemodynamic Parameters at Different Ages of Life: Results From a Prospective Cross-Sectional Study
Zimmermann, G., Joly, L., Schoepfer, P., Doyen, M., Roch, V., Grignon, R., Salvi, P., Marie, P., Bénétos, A., & Verger, A. (2022) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2022.908063 · Cited by 7
“, 2021) or by the presence of neurodegenerative pathologies (Minoshima et al., 1995).”
Background
Clinical impact of digital and conventional PET control databases for semi-quantitative analysis of brain 18F-FDG digital PET scans
Mairal, E., Doyen, M., Jonveaux, T., Malaplate, C., Guedj, É., & Verger, A. (2020) · EJNMMI Research · doi:10.1186/s13550-020-00733-y · Cited by 7
Longitudinal Positron Emission Tomography in Preventive Alzheimer's Disease Drug Trials, Critical Barriers from Imaging Science Perspective
Shokouhi, S., Campbell, D. L., Brill, A. B., Gwirtsman, H. E., & Initiative, T. A. D. N. (2016) · Brain Pathology · doi:10.1111/bpa.12399 · Cited by 7
“Different local and global normalization schemes are utilized in FDG-PET for brain studies and the selection of the optimal method has been debated (6, 16, 32, 51, 54).”
Method
Impairment of Everyday Spatial Navigation Abilities in Mild Cognitive Impairment Is Weakly Associated with Reduced Grey Matter Volume in the Medial Part of the Entorhinal Cortex
Hallab, A., Initiative, A. D. N., Lange, C., Apostolova, I. I., Özden, C., González‐Escamilla, G., Klutmann, S., Brenner, W., Grothe, M. J., & Buchert, R. (2020) · Journal of Alzheimer s Disease · doi:10.3233/jad-200520 · Cited by 5
Absolute SPECT/CT quantification of cerebral uptake of 99mTc-HMPAO for patients with neurocognitive disorders
Welz, F., Sanders, J. C., Kuwert, T., et al. (2015) · Nuklearmedizin - NuclearMedicine · doi:10.3413/nukmed-0765-15-09 · Cited by 6
“Nevertheless, some evidence exists that specific sub-regions of the brain could be more suitable for diagnosing neurodegenerative diseases (27, 31).”
Background
Positron Emission Tomography in Alzheimer Disease
Schmidt, M. E., Matthews, D. C., Andrews, R. D., & Mosconi, L. (2012) · Elsevier eBooks · doi:10.1016/b978-0-12-386945-6.00005-6 · Cited by 7
Enhancing diagnosis of mild cognitive impairment through brain-heart-gut metabolic networks in whole-body PET imaging
Li, F., Bai, S., Liu, Y., Chen, Z., Zhao, S., Ding, Z., Xie, F., Xu, Y., Yue, L., Zhang, H., et al. (2026) · Cell Reports Medicine · doi:10.1016/j.xcrm.2026.102629 · Cited by 8
Using the rPatlak plot and dynamic FDG-PET to generate parametric images of relative local cerebral metabolic rate of glucose
Wu, Y., Zhou, Y., Bao, S., et al. (2012) · Chinese Science Bulletin · doi:10.1007/s11434-012-5401-y · Cited by 5
Arterial spin labeling perfusion MRI differentiates between radiation necrosis and tumor in brain metastases treated with stereotactic radiosurgery
Nguyen, H. H., Ng, N. N., Awasthi, S., et al. (2025) · Neuro-Oncology Advances · doi:10.1093/noajnl/vdaf091 · Cited by 4
The need for “objective measurements” in FDG and amyloid PET neuroimaging
Perani, D., Iaccarino, L., & Bettinardi, V. (2014) · Clinical and Translational Imaging · doi:10.1007/s40336-014-0072-0 · Cited by 4
“Various reference regions have been proposed for (18)F-FDG PET imaging in AD, such as the cerebellum and sensorimotor cortex [17, 18] or pons [19].”
Background
Combined 18F‐FDG PET‐CT markers in dementia with Lewy bodies
Mattoli, M. V., Cocciolillo, F., Chiacchiaretta, P., Dotta, F., Trevisi, G., Carrarini, C., Thomas, A., Sensi, S. L., Pizzi, A. D., Nicola, A. D. D., et al. (2023) · Alzheimer s & Dementia Diagnosis Assessment & Disease Monitoring · doi:10.1002/dad2.12515 · Cited by 5
Imaging Aging: Present and Future
Hayes, S. M., & Cabeza, R. E. L. (2008) · Sage eBooks · doi:10.4135/9781412976589.n19 · Cited by 4
Subject-specific Models for the Analysis of Pathological FDG PET Data
Burgos, N., Cardoso, M. J., Mendelson, A., et al. (2015) · Lecture notes in computer science · doi:10.1007/978-3-319-24571-3_78 · Cited by 3
“PET images were intensity normalised using the mean uptake of the pons [9].”
Method
Contribution of FDG-PET and MRI to improve Understanding, Detection and Differentiation of Dementia
Dukart, J. (2011) · Qucosa (Saxon State and University Library Dresden) · Cited by 3
PET imaging in Down syndrome and Alzheimer's disease
Handen, B. L., & Christian, B. T. (2021) · Elsevier eBooks · doi:10.1016/b978-0-12-818845-3.00013-x · Cited by 2
Statistical Diagnostic Radiology
UCHIDA, Y. (2002) · Japanese Journal of Radiological Technology · doi:10.6009/jjrt.kj00000921533 · Cited by 2
Physical and Cognitive Activities and Trajectories of AD Neuroimaging Biomarkers
Krell‐Roesch, J., Syrjanen, J. A., Hansen, A. L., Vemuri, P., Scharf, E. L., Fields, J. A., Kremers, W. K., Lowe, V. J., Graff‐Radford, J., Jack, C. R., et al. (2025) · Neurology · doi:10.1212/wnl.0000000000214405 · Cited by 2
Resting State Glucose Utilization and Adult Reading Test Performance
Lee, Y., Yi, D., Seo, E. H., Han, J., Joung, H., Byun, M. S., Lee, J. H., Jun, J., & Lee, D. Y. (2020) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2020.00048 · Cited by 1
Neuronal activity and amyloid-β cause tau seeding in the entorhinal cortex in Alzheimer’s diseasePreprint
Alexandersen, C. G., Bassett, D. S., Goriely, A., Chaggar, P., & Initiative, T. A. D. N. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.03.07.642054 · Cited by 1
“32,33 For the FDG PET scans, we extracted in total 321 scans (138 scans in A β − , 48 scans in A β + τ MTL − τ NEO − , 39 scans in A β + τ MTL + τ NEO − , and 90 scans in A β + τ MTL + τ NEO + ).”
Metabolic Topography of Parkinsonism
Kim, J. S. (2007) · Nuclear Medicine and Molecular Imaging · Cited by 1
Molecular Imaging in Alzheimer Clinical Trials
Schmidt, M. E., Matthews, D. C., & Staelens, S. G. (2016) · Elsevier eBooks · doi:10.1016/b978-0-12-802173-6.00020-4
13 Functional Imaging with FDG-PET in Mild Cognitive Impairment
Herholz, K. (2009) · Oxford University Press eBooks · doi:10.1093/acprof:oso/9780195328875.003.0013 · Cited by 1
Alzheimer' sDiseas eversu sDementi awith Lew yBodies :Cerebra lMetaboli cDistinction wit hAutops yConfirmation
iMinoshima, S. (2001)
PET studies on disease progression and treatment efficacy in Alzheimer’s disease and mild cognitive impairment
Okello, A. (2011) · Spiral (Imperial College London) · doi:10.25560/7110
Analysis of 18F-DMFP-PET data using Hidden Markov Random Field and the Gaussian distribution to assist the diagnosis of Parkinsonism
Segovia, F., Salas-Gonzalez, D., Górriz, J. M., et al. (2017) · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · doi:10.1117/12.2250281
AmyloidDepositionBeginsintheStriatumofPresenilin-1 MutationCarriersfromTwoUnrelatedPedigrees
Lopresti, B., & Ikonomovic, M. D. (2007)
Comprehensive Evaluation of the effects of Time-of-flight Technique on Regional Brain PET using Hybrid PET/MRIPreprint
Wimalarathne, D., Sun, X., Liu, F., et al. (2022) · Research Square · doi:10.21203/rs.3.rs-2319905/v1
18F-FDG PET for Neurodegenerative Diseases: Principles and Progress
Thientunyakit, T., Wannasoupol, N., Sethanandha, C., Piyapittayanan, S., Siriprapa, T., Thongpraparn, T., Muangpaisan, W., & Gelovani, J. G. (2025) · Neuromethods · doi:10.1007/978-1-0716-4494-2_6
Appendixe B: Level of Function Scale
(2009) · American Psychiatric Association Publishing eBooks · doi:10.1176/appi.books.9781585628940.app02

Authors: Minoshima, S., Frey, K. A., Foster, N. L., & Kuhl, D. E.
Affiliations: University of Michigan (US)
ORCID: Minoshima, Satoshi
Frey, Kirk A.
Foster, Norman L.
Venue: Journal of Computer Assisted Tomography
Publisher: Ovid Technologies (Wolters Kluwer Health)
Published: 1995-07
Volume: 19
Issue: 4
Pages: 541-547
ISSN: 0363-8715 (ISSN-L)
DOI: 10.1097/00004728-199507000-00006
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

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Preserved Pontine Glucose Metabolism in Alzheimer Disease: A Reference Region for Functional Brain Image (PET) Analysis

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