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Richter N, Breidenbach L, Schmieschek MH, Heiss WD, Fink GR, Onur OA. Alzheimer-typical temporo-parietal atrophy and hypoperfusion are associated with a more significant cholinergic impairment in amnestic neurodegenerative syndromes. J Alzheimers Dis 2025; 104:1290-1300. [PMID: 40116674 DOI: 10.1177/13872877251324080] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/23/2025]
Abstract
BackgroundTo date, cholinomimetics remain central in the pharmacotherapy of Alzheimer's disease (AD) dementia. However, postmortem investigations indicate that the AD-typical progressive amnestic syndrome may also result from predominantly limbic non-AD neuropathology such as TDP-43 proteinopathy and argyrophilic grain disease. Experimental evidence links a beneficial response to cholinomimetics in early AD to reduced markers of cholinergic neurotransmission. However, the cholinergic impairment varies among patients with a clinical AD presentation, likely due to non-AD (co)-pathologies.ObjectiveThis study examines whether AD-typical atrophy and hypoperfusion can provide information about the cholinergic system in clinically diagnosed AD.MethodsThirty-two patients with amnestic mild cognitive impairment or mild dementia due to AD underwent positron emission tomography (PET) with the tracer N-methyl-4-piperidyl-acetate (MP4A) to estimate acetylcholinesterase (AChE) activity, neurological examinations, cerebral magnetic resonance imaging (MRI) and neuropsychological assessment. The 'cholinergic deficit' was computed as the deviation of AChE activity from cognitively normal controls across the cerebral cortex and correlated gray matter (GM) and perfusion of temporo-parietal cortices typically affected by AD and basal forebrain (BF) GM.ResultsTemporo-parietal perfusion and GM, as well as the inferior temporal to medial temporal ratio of perfusion correlated negatively with the 'cholinergic deficit'. A smaller Ch4p area of the BF was associated with a more significant 'cholinergic deficit', albeit to a lesser degree than cortical measures.ConclusionsIn clinically diagnosed AD, temporo-parietal GM and perfusion are more closely associated with the 'cholinergic deficit' than BF volumes, making them possible markers for cholinergic treatment response in amnestic neurodegeneration.
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Affiliation(s)
- Nils Richter
- Cognitive Neuroscience, Institute of Neuroscience and Medicine (INM-3), Research Center Jülich, Germany
- Department of Neurology, University Hospital Cologne and Faculty of Medicine, University of Cologne, Germany
| | - Laura Breidenbach
- Department of Neurology, University Hospital Cologne and Faculty of Medicine, University of Cologne, Germany
| | - Maximilian Ht Schmieschek
- Department of Neurology, University Hospital Cologne and Faculty of Medicine, University of Cologne, Germany
| | | | - Gereon R Fink
- Cognitive Neuroscience, Institute of Neuroscience and Medicine (INM-3), Research Center Jülich, Germany
- Department of Neurology, University Hospital Cologne and Faculty of Medicine, University of Cologne, Germany
| | - Oezguer A Onur
- Cognitive Neuroscience, Institute of Neuroscience and Medicine (INM-3), Research Center Jülich, Germany
- Department of Neurology, University Hospital Cologne and Faculty of Medicine, University of Cologne, Germany
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2
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Doering E, Hoenig MC, Giehl K, Dzialas V, Andrassy G, Bader A, Bauer A, Elmenhorst D, Ermert J, Frensch S, Jäger E, Jessen F, Krapf P, Kroll T, Lerche C, Lothmann J, Matusch A, Neumaier B, Onur OA, Ramirez A, Richter N, Sand F, Tellmann L, Theis H, Zeyen P, van Eimeren T, Drzezga A, Bischof GN, Weintraub E. "Fill States": PET-derived Markers of the Spatial Extent of Alzheimer Disease Pathology. Radiology 2025; 314:e241482. [PMID: 40131110 PMCID: PMC11950890 DOI: 10.1148/radiol.241482] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2024] [Revised: 01/27/2025] [Accepted: 02/04/2025] [Indexed: 03/26/2025]
Abstract
Background Alzheimer disease (AD) progression can be monitored by tracking intensity changes in PET standardized uptake value (SUV) ratios of amyloid, tau, and neurodegeneration. The spatial extent ("fill state") of these three hallmark pathologic abnormalities may serve as critical pathophysiologic information, pending further investigation. Purpose To examine the clinical utility and increase the accessibility of PET-derived fill states. Materials and Methods This secondary analysis of two prospective studies used data from two independent cohorts: the Alzheimer's Disease Neuroimaging Initiative (ADNI) and the Tau Propagation over Time study (T-POT). Each cohort comprised amyloid-negative cognitively normal individuals (controls) and patients with subjective cognitive decline, mild cognitive impairment, or probable-AD dementia. Fill states of amyloid, tau, and neurodegeneration were computed as the percentages of significantly abnormal voxels relative to controls across PET scans. Fill states and SUV ratios were compared across stages (Kruskal-Wallis H test, area under the receiver operating characteristic curve analysis) and tested for association with the severity of cognitive impairment (Spearman correlation, multivariate regression analysis). Additionally, a convolutional neural network (CNN) was developed to estimate fill states from patients' PET scans without requiring controls. Results The ADNI cohort included 324 individuals (mean age, 72 years ± 6.8 [SD]; 173 [53%] female), and the T-POT cohort comprised 99 individuals (mean age, 66 years ± 8.7; 63 [64%] female). Higher fill states were associated with higher stages of cognitive impairment (P < .001), and tau and neurodegeneration fill states showed higher diagnostic performance for cognitive impairment compared with SUV ratio (P < .05) across cohorts. Similarly, all fill states were negatively correlated with cognitive performance (P < .001) and uniquely characterized the degree of cognitive impairment even after adjustment for SUV ratio (P < .05). The CNN estimated amyloid and tau accurately, but not neurodegeneration fill states. Conclusion Fill states provided reliable markers of AD progression, potentially improving early detection, staging, and monitoring of AD in clinical practice and trials beyond SUV ratio. Clinical trial registration no. NCT00106899 © RSNA, 2025 Supplemental material is available for this article. See also the editorial by Yun and Kim in this issue.
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Affiliation(s)
- Elena Doering
- Department of Nuclear Medicine, Faculty of Medicine and
University Hospital, University of Cologne, Kerpener Str 62, 50937 Cologne,
Germany
- German Center for Neurodegenerative Diseases (DZNE),
Bonn, Germany
| | - Merle C. Hoenig
- Department of Nuclear Medicine, Faculty of Medicine and
University Hospital, University of Cologne, Kerpener Str 62, 50937 Cologne,
Germany
- Institute of Neuroscience and Medicine–Molecular
Organization of the Brain (INM-2), Forschungszentrum Jülich,
Jülich, Germany
| | - Kathrin Giehl
- Department of Nuclear Medicine, Faculty of Medicine and
University Hospital, University of Cologne, Kerpener Str 62, 50937 Cologne,
Germany
- Institute of Neuroscience and Medicine–Molecular
Organization of the Brain (INM-2), Forschungszentrum Jülich,
Jülich, Germany
| | - Verena Dzialas
- Department of Nuclear Medicine, Faculty of Medicine and
University Hospital, University of Cologne, Kerpener Str 62, 50937 Cologne,
Germany
- Faculty of Mathematics and Natural Sciences, University
of Cologne, Cologne, Germany
| | - Grégory Andrassy
- Department of Nuclear Medicine, Faculty of Medicine and
University Hospital, University of Cologne, Kerpener Str 62, 50937 Cologne,
Germany
| | - Abdelmajid Bader
- Department of Psychiatry, Faculty of Medicine and
University Hospital, University of Cologne, Cologne, Germany
| | - Andreas Bauer
- Institute of Neuroscience and Medicine–Molecular
Organization of the Brain (INM-2), Forschungszentrum Jülich,
Jülich, Germany
| | - David Elmenhorst
- Department of Nuclear Medicine, Faculty of Medicine and
University Hospital, University of Cologne, Kerpener Str 62, 50937 Cologne,
Germany
- Institute of Neuroscience and Medicine–Molecular
Organization of the Brain (INM-2), Forschungszentrum Jülich,
Jülich, Germany
| | - Johannes Ermert
- Institute of Neuroscience and Medicine–Nuclear
Chemistry (INM-5), Forschungszentrum Jülich, Jülich, Germany
| | - Silke Frensch
- Institute of Neuroscience and
Medicine–Imaging-Core-Facility (ICF), Forschungszentrum Jülich,
Jülich, Germany
| | - Elena Jäger
- Department of Nuclear Medicine, Faculty of Medicine and
University Hospital, University of Cologne, Kerpener Str 62, 50937 Cologne,
Germany
| | - Frank Jessen
- German Center for Neurodegenerative Diseases (DZNE),
Bonn, Germany
- Department of Psychiatry, Faculty of Medicine and
University Hospital, University of Cologne, Cologne, Germany
| | - Philipp Krapf
- Institute of Neuroscience and Medicine–Nuclear
Chemistry (INM-5), Forschungszentrum Jülich, Jülich, Germany
| | - Tina Kroll
- Department of Nuclear Medicine, Faculty of Medicine and
University Hospital, University of Cologne, Kerpener Str 62, 50937 Cologne,
Germany
| | - Christoph Lerche
- Institute of Neuroscience and Medicine–Medical
Imaging Physics (INM-4), Forschungszentrum Jülich, Jülich,
Germany
| | - Julia Lothmann
- Department of Nuclear Medicine, Faculty of Medicine and
University Hospital, University of Cologne, Kerpener Str 62, 50937 Cologne,
Germany
| | - Andreas Matusch
- Institute of Neuroscience and Medicine–Molecular
Organization of the Brain (INM-2), Forschungszentrum Jülich,
Jülich, Germany
| | - Bernd Neumaier
- Institute of Neuroscience and Medicine–Nuclear
Chemistry (INM-5), Forschungszentrum Jülich, Jülich, Germany
- Department of Nuclear Chemistry, Faculty of Mathematics
and Natural Sciences, University of Cologne, Cologne, Germany
- Faculty of Medicine and University Hospital Cologne,
Institute of Radiochemistry and Experimental Molecular Imaging, University of
Cologne, Cologne, Germany
| | - Oezguer A. Onur
- Department of Neurology, Faculty of Medicine and
University Hospital, University of Cologne, Cologne, Germany
| | - Alfredo Ramirez
- German Center for Neurodegenerative Diseases (DZNE),
Bonn, Germany
- Cologne Excellence Cluster for Aging and
Aging-Associated Diseases (CECAD), University of Cologne, Cologne, Germany
- Department of Psychiatry and Psychotherapy, Division of
Neurogenetics and Molecular Psychiatry, University of Cologne, Medical Faculty,
Cologne, Germany
- Department for Neurodegenerative Diseases and Geriatric
Psychiatry, University Hospital Bonn, Bonn, Germany
- Department of Psychiatry and Glenn Biggs Institute for
Alzheimer’s and Neurodegenerative Diseases, University of Texas Health
Science Center at San Antonio, San Antonio, Tex
| | - Nils Richter
- Department of Neurology, Faculty of Medicine and
University Hospital, University of Cologne, Cologne, Germany
- Institute of Neuroscience and Medicine–Cognitive
Neuroscience (INM-3), Forschungszentrum Jülich, Jülich,
Germany
| | - Frederik Sand
- Department of Psychiatry, Faculty of Medicine and
University Hospital, University of Cologne, Cologne, Germany
| | - Lutz Tellmann
- Institute of Neuroscience and Medicine–Medical
Imaging Physics (INM-4), Forschungszentrum Jülich, Jülich,
Germany
| | - Hendrik Theis
- Department of Nuclear Medicine, Faculty of Medicine and
University Hospital, University of Cologne, Kerpener Str 62, 50937 Cologne,
Germany
- Department of Neurology, Faculty of Medicine and
University Hospital, University of Cologne, Cologne, Germany
| | - Philip Zeyen
- Department of Psychiatry, Faculty of Medicine and
University Hospital, University of Cologne, Cologne, Germany
| | - Thilo van Eimeren
- Department of Nuclear Medicine, Faculty of Medicine and
University Hospital, University of Cologne, Kerpener Str 62, 50937 Cologne,
Germany
- Department of Neurology, Faculty of Medicine and
University Hospital, University of Cologne, Cologne, Germany
| | - Alexander Drzezga
- Department of Nuclear Medicine, Faculty of Medicine and
University Hospital, University of Cologne, Kerpener Str 62, 50937 Cologne,
Germany
- German Center for Neurodegenerative Diseases (DZNE),
Bonn, Germany
- Institute of Neuroscience and Medicine–Molecular
Organization of the Brain (INM-2), Forschungszentrum Jülich,
Jülich, Germany
| | - Gérard N. Bischof
- Department of Nuclear Medicine, Faculty of Medicine and
University Hospital, University of Cologne, Kerpener Str 62, 50937 Cologne,
Germany
- Institute of Neuroscience and Medicine–Molecular
Organization of the Brain (INM-2), Forschungszentrum Jülich,
Jülich, Germany
| | | | - Elizabeth Weintraub
- Department of Nuclear Medicine, Faculty of Medicine and
University Hospital, University of Cologne, Kerpener Str 62, 50937 Cologne,
Germany
- German Center for Neurodegenerative Diseases (DZNE),
Bonn, Germany
- Institute of Neuroscience and Medicine–Molecular
Organization of the Brain (INM-2), Forschungszentrum Jülich,
Jülich, Germany
- Faculty of Mathematics and Natural Sciences, University
of Cologne, Cologne, Germany
- Department of Psychiatry, Faculty of Medicine and
University Hospital, University of Cologne, Cologne, Germany
- Institute of Neuroscience and Medicine–Nuclear
Chemistry (INM-5), Forschungszentrum Jülich, Jülich, Germany
- Institute of Neuroscience and
Medicine–Imaging-Core-Facility (ICF), Forschungszentrum Jülich,
Jülich, Germany
- Institute of Neuroscience and Medicine–Medical
Imaging Physics (INM-4), Forschungszentrum Jülich, Jülich,
Germany
- Department of Nuclear Chemistry, Faculty of Mathematics
and Natural Sciences, University of Cologne, Cologne, Germany
- Faculty of Medicine and University Hospital Cologne,
Institute of Radiochemistry and Experimental Molecular Imaging, University of
Cologne, Cologne, Germany
- Department of Neurology, Faculty of Medicine and
University Hospital, University of Cologne, Cologne, Germany
- Cologne Excellence Cluster for Aging and
Aging-Associated Diseases (CECAD), University of Cologne, Cologne, Germany
- Department of Psychiatry and Psychotherapy, Division of
Neurogenetics and Molecular Psychiatry, University of Cologne, Medical Faculty,
Cologne, Germany
- Department for Neurodegenerative Diseases and Geriatric
Psychiatry, University Hospital Bonn, Bonn, Germany
- Department of Psychiatry and Glenn Biggs Institute for
Alzheimer’s and Neurodegenerative Diseases, University of Texas Health
Science Center at San Antonio, San Antonio, Tex
- Institute of Neuroscience and Medicine–Cognitive
Neuroscience (INM-3), Forschungszentrum Jülich, Jülich,
Germany
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Kroll T, Miranda A, Drechsel A, Beer S, Lang M, Drzezga A, Rosa-Neto P, Verhaeghe J, Elmenhorst D, Bauer A. Dynamic neuroreceptor positron emission tomography in non-anesthetized rats using point source based motion correction: A feasibility study with [ 11C]ABP688. J Cereb Blood Flow Metab 2024; 44:1852-1866. [PMID: 38684219 PMCID: PMC11504418 DOI: 10.1177/0271678x241239133] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/10/2023] [Revised: 01/25/2024] [Accepted: 02/14/2024] [Indexed: 05/02/2024]
Abstract
To prevent motion artifacts in small animal positron emission tomography (PET), animals are routinely scanned under anesthesia or physical restraint. Both may potentially alter metabolism and neurochemistry. This study investigates the feasibility of fully awake acquisition and subsequent absolute quantification of dynamic brain PET data via pharmacokinetic modelling in moving rats using the glutamate 5 receptor radioligand [11C]ABP688 and point source based motion correction. Five male rats underwent three dynamic [11C]ABP688 PET scans: two test-retest awake PET scans and one scan under anesthesia for comparison. Specific radioligand binding was determined via the simplified reference tissue model (reference: cerebellum) and outcome parameters BPND and R1 were evaluated in terms of stability and reproducibility. Test-retest measurements in awake animals gave reliable results with high correlations of BPND (y = 1.08 × -0.2, r = 0.99, p < 0.01) and an acceptable variability (mean over all investigated regions 15.7 ± 2.4%). Regional [11C]ABP688 BPNDs under awake and anesthetized conditions were comparable although in awake scans, absolute radioactive peak uptakes were lower and relative blood flow in terms of R1 was higher. Awake small animal PET with absolute quantification of neuroreceptor availability is technically feasible and reproducible thereby providing a suitable alternative whenever effects of anesthesia are undesirable, e.g. in sleep research.
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Affiliation(s)
- Tina Kroll
- Institute of Neurosciences and Medicine (INM-2), Forschungszentrum Jülich GmbH, Germany
| | - Alan Miranda
- Molecular Imaging Center Antwerp, University of Antwerp, Belgium
| | - Alexandra Drechsel
- Institute of Neurosciences and Medicine (INM-2), Forschungszentrum Jülich GmbH, Germany
| | - Simone Beer
- Institute of Neurosciences and Medicine (INM-2), Forschungszentrum Jülich GmbH, Germany
| | - Markus Lang
- Institute of Neurosciences and Medicine (INM-5), Forschungszentrum Jülich GmbH, Germany
| | - Alexander Drzezga
- Institute of Neurosciences and Medicine (INM-2), Forschungszentrum Jülich GmbH, Germany
- Department of Nuclear Medicine, University Hospital Cologne, Germany
- German Center for Neurodegenerative Diseases (DZNE), Bonn-Cologne, Germany
| | - Pedro Rosa-Neto
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer’s Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal; Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, Canada
| | - Jeroen Verhaeghe
- Molecular Imaging Center Antwerp, University of Antwerp, Belgium
| | - David Elmenhorst
- Institute of Neurosciences and Medicine (INM-2), Forschungszentrum Jülich GmbH, Germany
- Department of Nuclear Medicine, University Hospital Cologne, Germany
| | - Andreas Bauer
- Institute of Neurosciences and Medicine (INM-2), Forschungszentrum Jülich GmbH, Germany
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Gong K, Johnson K, El Fakhri G, Li Q, Pan T. PET image denoising based on denoising diffusion probabilistic model. Eur J Nucl Med Mol Imaging 2024; 51:358-368. [PMID: 37787849 PMCID: PMC10958486 DOI: 10.1007/s00259-023-06417-8] [Citation(s) in RCA: 16] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2022] [Accepted: 08/22/2023] [Indexed: 10/04/2023]
Abstract
PURPOSE Due to various physical degradation factors and limited counts received, PET image quality needs further improvements. The denoising diffusion probabilistic model (DDPM) was a distribution learning-based model, which tried to transform a normal distribution into a specific data distribution based on iterative refinements. In this work, we proposed and evaluated different DDPM-based methods for PET image denoising. METHODS Under the DDPM framework, one way to perform PET image denoising was to provide the PET image and/or the prior image as the input. Another way was to supply the prior image as the network input with the PET image included in the refinement steps, which could fit for scenarios of different noise levels. 150 brain [[Formula: see text]F]FDG datasets and 140 brain [[Formula: see text]F]MK-6240 (imaging neurofibrillary tangles deposition) datasets were utilized to evaluate the proposed DDPM-based methods. RESULTS Quantification showed that the DDPM-based frameworks with PET information included generated better results than the nonlocal mean, Unet and generative adversarial network (GAN)-based denoising methods. Adding additional MR prior in the model helped achieved better performance and further reduced the uncertainty during image denoising. Solely relying on MR prior while ignoring the PET information resulted in large bias. Regional and surface quantification showed that employing MR prior as the network input while embedding PET image as a data-consistency constraint during inference achieved the best performance. CONCLUSION DDPM-based PET image denoising is a flexible framework, which can efficiently utilize prior information and achieve better performance than the nonlocal mean, Unet and GAN-based denoising methods.
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Affiliation(s)
- Kuang Gong
- J. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, Gainesville, 32611, FL, USA.
- Gordon Center for Medical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, 02114, MA, USA.
- Center for Advanced Medical Computing and Analysis, Massachusetts General Hospital and Harvard Medical School, Boston, 02114, MA, USA.
| | - Keith Johnson
- Gordon Center for Medical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, 02114, MA, USA
| | - Georges El Fakhri
- Gordon Center for Medical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, 02114, MA, USA
| | - Quanzheng Li
- Center for Advanced Medical Computing and Analysis, Massachusetts General Hospital and Harvard Medical School, Boston, 02114, MA, USA
| | - Tinsu Pan
- Department of Imaging Physics, University of Texas MD Anderson Cancer Center, Houston, 77030, TX, USA
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5
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Guehl NJ, Dhaynaut M, Hanseeuw BJ, Moon SH, Lois C, Thibault E, Fu JF, Price JC, Johnson KA, El Fakhri G, Normandin MD. Measurement of Cerebral Perfusion Indices from the Early Phase of [ 18F]MK6240 Dynamic Tau PET Imaging. J Nucl Med 2023; 64:968-975. [PMID: 36997330 PMCID: PMC10241011 DOI: 10.2967/jnumed.122.265072] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2022] [Revised: 01/26/2023] [Accepted: 01/26/2023] [Indexed: 04/01/2023] Open
Abstract
6-(fluoro-18F)-3-(1H-pyrrolo[2,3-c]pyridin-1-yl)isoquinolin-5-amine ([18F]MK6240) has high affinity and selectivity for hyperphosphorylated tau and readily crosses the blood-brain barrier. This study investigated whether the early phase of [18F]MK6240 can be used to provide a surrogate index of cerebral perfusion. Methods: Forty-nine subjects who were cognitively normal (CN), had mild cognitive impairment (MCI), or had Alzheimer's disease (AD) underwent paired dynamic [18F]MK6240 and [11C]Pittsburgh compound B (PiB) PET, as well as structural MRI to obtain anatomic information. Arterial blood samples were collected in a subset of 24 subjects for [18F]MK6240 scans to derive metabolite-corrected arterial input functions. Regional time-activity curves were extracted using atlases available in the Montreal Neurologic Institute template space and using FreeSurfer. The early phase of brain time-activity curves was analyzed using a 1-tissue-compartment model to obtain a robust estimate of the rate of transfer from plasma to brain tissue, K 1 (mL⋅cm-3⋅min-1), and the simplified reference tissue model 2 was investigated for noninvasive estimation of the relative delivery rate, R 1 (unitless). A head-to-head comparison with R 1 derived from [11C]PiB scans was performed. Grouped differences in R 1 were evaluated among CN, MCI, and AD subjects. Results: Regional K 1 values suggested a relatively high extraction fraction. R 1 estimated noninvasively from simplified reference tissue model 2 agreed well with R 1 calculated indirectly from the blood-based compartment modeling (r = 0.99; mean difference, 0.024 ± 0.027), suggesting that robust estimates were obtained. R 1 measurements obtained with [18F]MK6240 correlated strongly and overall agreed well with those obtained from [11C]PiB (r = 0.93; mean difference, -0.001 ± 0.068). Statistically significant differences were observed in regional R 1 measurements among CN, MCI, and AD subjects, notably in the temporal and parietal cortices. Conclusion: Our results provide evidence that the early phase of [18F]MK6240 images may be used to derive a useful index of cerebral perfusion. The early and late phases of a [18F]MK6240 dynamic acquisition may thus offer complementary information about the pathophysiologic mechanisms of the disease.
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Affiliation(s)
- Nicolas J Guehl
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts;
| | - Maeva Dhaynaut
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| | - Bernard J Hanseeuw
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
- Department of Neurology, Cliniques Universitaires Saint-Luc, Université Catholique de Louvain, Brussels, Belgium; and
| | - Sung-Hyun Moon
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| | - Cristina Lois
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| | - Emma Thibault
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| | - Jessie Fanglu Fu
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| | - Julie C Price
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| | - Keith A Johnson
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| | - Georges El Fakhri
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| | - Marc D Normandin
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
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Prange S, Theis H, Banwinkler M, van Eimeren T. Molecular Imaging in Parkinsonian Disorders—What’s New and Hot? Brain Sci 2022; 12:brainsci12091146. [PMID: 36138882 PMCID: PMC9496752 DOI: 10.3390/brainsci12091146] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2022] [Revised: 08/23/2022] [Accepted: 08/24/2022] [Indexed: 12/02/2022] Open
Abstract
Highlights Abstract Neurodegenerative parkinsonian disorders are characterized by a great diversity of clinical symptoms and underlying neuropathology, yet differential diagnosis during lifetime remains probabilistic. Molecular imaging is a powerful method to detect pathological changes in vivo on a cellular and molecular level with high specificity. Thereby, molecular imaging enables to investigate functional changes and pathological hallmarks in neurodegenerative disorders, thus allowing to better differentiate between different forms of degenerative parkinsonism, improve the accuracy of the clinical diagnosis and disentangle the pathophysiology of disease-related symptoms. The past decade led to significant progress in the field of molecular imaging, including the development of multiple new and promising radioactive tracers for single photon emission computed tomography (SPECT) and positron emission tomography (PET) as well as novel analytical methods. Here, we review the most recent advances in molecular imaging for the diagnosis, prognosis, and mechanistic understanding of parkinsonian disorders. First, advances in imaging of neurotransmission abnormalities, metabolism, synaptic density, inflammation, and pathological protein aggregation are reviewed, highlighting our renewed understanding regarding the multiplicity of neurodegenerative processes involved in parkinsonian disorders. Consequently, we review the role of molecular imaging in the context of disease-modifying interventions to follow neurodegeneration, ensure stratification, and target engagement in clinical trials.
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Affiliation(s)
- Stéphane Prange
- Multimodal Neuroimaging Group, Department of Nuclear Medicine, Faculty of Medicine, University Hospital of Cologne, University of Cologne, 50937 Cologne, Germany
- Institut des Sciences Cognitives Marc Jeannerod, CNRS, UMR 5229, Université de Lyon, 69675 Bron, France
- Correspondence: (S.P.); (T.v.E.); Tel.: +49-221-47882843 (T.v.E.)
| | - Hendrik Theis
- Multimodal Neuroimaging Group, Department of Nuclear Medicine, Faculty of Medicine, University Hospital of Cologne, University of Cologne, 50937 Cologne, Germany
- Department of Neurology, Faculty of Medicine, University Hospital of Cologne, University of Cologne, 50937 Cologne, Germany
| | - Magdalena Banwinkler
- Multimodal Neuroimaging Group, Department of Nuclear Medicine, Faculty of Medicine, University Hospital of Cologne, University of Cologne, 50937 Cologne, Germany
| | - Thilo van Eimeren
- Multimodal Neuroimaging Group, Department of Nuclear Medicine, Faculty of Medicine, University Hospital of Cologne, University of Cologne, 50937 Cologne, Germany
- Department of Neurology, Faculty of Medicine, University Hospital of Cologne, University of Cologne, 50937 Cologne, Germany
- Correspondence: (S.P.); (T.v.E.); Tel.: +49-221-47882843 (T.v.E.)
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7
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Barthel H, Villemagne VL, Drzezga A. Future Directions in Molecular Imaging of Neurodegenerative Disorders. J Nucl Med 2022; 63:68S-74S. [PMID: 35649650 DOI: 10.2967/jnumed.121.263202] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Revised: 04/19/2022] [Indexed: 12/12/2022] Open
Abstract
The improvement of existing techniques and the development of new molecular imaging methods are an exciting and rapidly developing field in clinical care and research of neurodegenerative disorders. In the clinic, molecular imaging has the potential to improve early and differential diagnosis and to stratify and monitor therapy in these disorders. Meanwhile, in research, these techniques improve our understanding of the underlying pathophysiology and pathobiochemistry of these disorders and allow for drug testing. This article is an overview on our perspective on future developments in neurodegeneration tracers and the associated imaging technologies. For example, we predict that the current portfolio of β-amyloid and tau aggregate tracers will be improved and supplemented by tracers allowing imaging of other protein aggregation pathologies, such as α-synuclein and transactive response DNA binding protein 43 kDa. Future developments will likely also be observed in imaging neurotransmitter systems. This refers to both offering imaging to a broader population in cases involving the dopaminergic, cholinergic, and serotonergic systems and making possible the imaging of systems not yet explored, such as the glutamate and opioid systems. Tracers will be complemented by improved tracers of neuroinflammation and synaptic density. Technologywise, the use of hybrid PET/MRI, dedicated brain PET, and total-body PET scanners, as well as advanced image acquisition and processing protocols, will open doors toward broader and more efficient clinical use and novel research applications. Molecular imaging has the potential of becoming a standard and essential clinical and research tool to diagnose and study neurodegenerative disorders and to guide treatments. On that road, we will need to redefine the role of molecular imaging in relation to that of emerging blood-based biomarkers. Taken together, the unique features of molecular imaging-that is, the potential to provide direct noninvasive information on the presence, extent, localization, and quantity of molecular pathologic processes in the living body-together with the predicted novel tracer and imaging technology developments, provide optimism about a bright future for this approach to improved care and research on neurodegenerative disorders.
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Affiliation(s)
- Henryk Barthel
- Department of Nuclear Medicine, University Medical Center, University of Leipzig, Leipzig, Germany;
| | - Victor L Villemagne
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania; and
| | - Alexander Drzezga
- Department of Nuclear Medicine, Faculty of Medicine and University Hospital Cologne, University of Cologne, German Center for Neurodegenerative Diseases, Bonn, Germany, and Institute of Neuroscience and Medicine, Molecular Organization of the Brain, Forschungszentrum Jülich, Jülich, Germany
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8
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Tuncel H, Visser D, Yaqub M, Timmers T, Wolters EE, Ossenkoppele R, van der Flier WM, van Berckel BNM, Boellaard R, Golla SSV. Effect of Shortening the Scan Duration on Quantitative Accuracy of [ 18F]Flortaucipir Studies. Mol Imaging Biol 2021; 23:604-613. [PMID: 33496930 PMCID: PMC8277654 DOI: 10.1007/s11307-021-01581-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2020] [Revised: 12/31/2020] [Accepted: 01/06/2021] [Indexed: 12/04/2022]
Abstract
PURPOSE Dynamic positron emission tomography (PET) protocols allow for accurate quantification of [18F]flortaucipir-specific binding. However, dynamic acquisitions can be challenging given the long required scan duration of 130 min. The current study assessed the effect of shorter scan protocols for [18F]flortaucipir on its quantitative accuracy. PROCEDURES Two study cohorts with Alzheimer's disease (AD) patients and healthy controls (HC) were included. All subjects underwent a 130-min dynamic [18F]flortaucipir PET scan consisting of two parts (0-60/80-130 min) post-injection. Arterial sampling was acquired during scanning of the first cohort only. For the second cohort, a second PET scan was acquired within 1-4 weeks of the first PET scan to assess test-retest repeatability (TRT). Three alternative time intervals were explored for the second part of the scan: 80-120, 80-110 and 80-100 min. Furthermore, the first part of the scan was also varied: 0-50, 0-40 and 0-30 min time intervals were assessed. The gap in the reference TACs was interpolated using four different interpolation methods: population-based input function 2T4k_VB (POP-IP_2T4k_VB), cubic, linear and exponential. Regional binding potential (BPND) and relative tracer delivery (R1) values estimated using simplified reference tissue model (SRTM) and/or receptor parametric mapping (RPM). The different scan protocols were compared to the respective values estimated using the original scan acquisition. In addition, TRT of the RPM BPND and R1 values estimated using the optimal shortest scan duration was also assessed. RESULTS RPM BPND and R1 obtained using 0-30/80-100 min scan and POP-IP_2T4k_VB reference region interpolation had an excellent correlation with the respective parametric values estimated using the original scan duration (r2 > 0.95). The TRT of RPM BPND and R1 using the shortest scan duration was - 1 ± 5 % and - 1 ± 6 % respectively. CONCLUSIONS This study demonstrated that [18F]flortaucipir PET scan can be acquired with sufficient quantitative accuracy using only 50 min of dual-time-window scanning time.
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Affiliation(s)
- Hayel Tuncel
- Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands.
| | - Denise Visser
- Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands
| | - Maqsood Yaqub
- Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands
| | - Tessa Timmers
- Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Emma E Wolters
- Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Rik Ossenkoppele
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
- Clinical Memory Research Unit, Lund University, Lund, Sweden
| | - Wiesje M van der Flier
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
- Department of Epidemiology and Data Sciences, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Bart N M van Berckel
- Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands
| | - Ronald Boellaard
- Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands
| | - Sandeep S V Golla
- Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands
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9
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Oh M, Lee N, Kim C, Son HJ, Sung C, Oh SJ, Lee SJ, Chung SJ, Lee CS, Kim JS. Diagnostic accuracy of dual-phase 18F-FP-CIT PET imaging for detection and differential diagnosis of Parkinsonism. Sci Rep 2021; 11:14992. [PMID: 34294739 PMCID: PMC8298455 DOI: 10.1038/s41598-021-94040-8] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2021] [Accepted: 06/25/2021] [Indexed: 11/25/2022] Open
Abstract
Delayed phase 18F-FP-CIT PET (dCIT) can assess the striatal dopamine transporter binding to detect degenerative parkinsonism (DP). Early phase 18F-FP-CIT (eCIT) can assess the regional brain activity for differential diagnosis among parkinsonism similar with 18F-FDG PET. We evaluated the diagnostic performance of dual phase 18F-FP-CIT PET (dual CIT) and 18F-FDG PET compared with clinical diagnosis in 141 subjects [36 with idiopathic Parkinson's disease (IPD), 77 with multiple system atrophy (MSA), 18 with progressive supranuclear palsy (PSP), and 10 with non-DP)]. Visual assessment of eCIT, dCIT, dual CIT, 18F-FDG and 18F-FDG PET with dCIT was in agreement with the clinical diagnosis in 61.7%, 69.5%, 95.7%, 81.6%, and 97.2% of cases, respectively. ECIT showed about 90% concordance with non-DP and MSA, and 8.3% and 27.8% with IPD and PSP, respectively. DCIT showed ≥ 88% concordance with non-DP, IPD, and PSP, and 49.4% concordance with MSA. Dual CIT showed ≥ 90% concordance in all groups. 18F-FDG PET showed ≥ 90% concordance with non-DP, MSA, and PSP, but only 33.3% concordance with IPD. The combination of 18F-FDG and dCIT yielded ≥ 90% concordance in all groups. Dual CIT may represent a powerful alternative to the combination of 18F-FDG PET and dCIT for differential diagnosis of parkinsonian disorders.
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Affiliation(s)
- Minyoung Oh
- Department of Nuclear Medicine, Asan Medical Center, University of Ulsan College of Medicine, 88, Olympic-ro 43-gil, Songpa-gu, Seoul, 05505, Korea
| | - Narae Lee
- Department of Nuclear Medicine, Wonju Severance Christian Hospital, Yonsei University Wonju College of Medicine, Wonju, Korea
| | - Chanwoo Kim
- Department of Nuclear Medicine, Kyung Hee University School of Medicine, Kyung Hee University Hospital At Gangdong, Seoul, Korea
| | - Hye Joo Son
- Department of Nuclear Medicine, Asan Medical Center, University of Ulsan College of Medicine, 88, Olympic-ro 43-gil, Songpa-gu, Seoul, 05505, Korea
| | - Changhwan Sung
- Department of Nuclear Medicine, Asan Medical Center, University of Ulsan College of Medicine, 88, Olympic-ro 43-gil, Songpa-gu, Seoul, 05505, Korea
| | - Seung Jun Oh
- Department of Nuclear Medicine, Asan Medical Center, University of Ulsan College of Medicine, 88, Olympic-ro 43-gil, Songpa-gu, Seoul, 05505, Korea
| | - Sang Ju Lee
- Department of Nuclear Medicine, Asan Medical Center, University of Ulsan College of Medicine, 88, Olympic-ro 43-gil, Songpa-gu, Seoul, 05505, Korea
| | - Sun Ju Chung
- Department of Neurology, Asan Medical Center, College of Medicine, University of Ulsan, Seoul, Korea
| | - Chong Sik Lee
- Department of Neurology, Asan Medical Center, College of Medicine, University of Ulsan, Seoul, Korea
| | - Jae Seung Kim
- Department of Nuclear Medicine, Asan Medical Center, University of Ulsan College of Medicine, 88, Olympic-ro 43-gil, Songpa-gu, Seoul, 05505, Korea.
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Hammes J, Bischof GN, Bohn KP, Onur Ö, Schneider A, Fliessbach K, Hönig MC, Jessen F, Neumaier B, Drzezga A, van Eimeren T. One-Stop Shop: 18F-Flortaucipir PET Differentiates Amyloid-Positive and -Negative Forms of Neurodegenerative Diseases. J Nucl Med 2020; 62:240-246. [PMID: 32620704 DOI: 10.2967/jnumed.120.244061] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2020] [Accepted: 05/30/2020] [Indexed: 02/06/2023] Open
Abstract
Tau protein aggregations are a hallmark of amyloid-associated Alzheimer disease and some forms of non-amyloid-associated frontotemporal lobar degeneration. In recent years, several tracers for in vivo tau imaging have been under evaluation. This study investigated the ability of 18F-flortaucipir PET not only to assess tau positivity but also to differentiate between amyloid-positive and -negative forms of neurodegeneration on the basis of different 18F-flortaucipir PET signatures. Methods: The 18F-flortaucipir PET data of 35 patients with amyloid-positive neurodegeneration, 19 patients with amyloid-negative neurodegeneration, and 17 healthy controls were included in a data-driven scaled subprofile model (SSM)/principal-component analysis (PCA) identifying spatial covariance patterns. SSM/PCA pattern expression strengths were tested for their ability to predict amyloid status in a receiver-operating-characteristic analysis and validated with a leave-one-out approach. Results: Pattern expression strengths predicted amyloid status with a sensitivity of 0.94 and a specificity of 0.83. A support vector machine classification based on pattern expression strengths in 2 different SSM/PCA components yielded a prediction accuracy of 98%. Anatomically, prediction performance was driven by parietooccipital gray matter in amyloid-positive patients versus predominant white matter binding in amyloid-negative patients. Conclusion: SSM/PCA-derived binding patterns of 18F-flortaucipir differentiate between amyloid-positive and -negative neurodegenerative diseases with high accuracy. 18F-flortaucipir PET alone may convey additional information equivalent to that from amyloid PET. Together with a perfusion-weighted early-phase acquisition (18F-FDG PET-equivalent), a single scan potentially contains comprehensive information on amyloid (A), tau (T), and neurodegeneration (N) status as required by recent biomarker classification algorithms (A/T/N).
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Affiliation(s)
- Jochen Hammes
- Multimodal Neuroimaging, Department of Nuclear Medicine, University Hospital and Medical Faculty, University of Cologne, Cologne, Germany .,Radiologische Allianz, Hamburg, Germany
| | - Gérard N Bischof
- Multimodal Neuroimaging, Department of Nuclear Medicine, University Hospital and Medical Faculty, University of Cologne, Cologne, Germany.,Faculty of Mathematics and Natural Sciences, University of Cologne, Cologne, Germany
| | - Karl P Bohn
- Multimodal Neuroimaging, Department of Nuclear Medicine, University Hospital and Medical Faculty, University of Cologne, Cologne, Germany.,Department of Nuclear Medicine, Inselspital University Hospital, University of Bern, Bern, Switzerland
| | - Özgür Onur
- Department of Neurology, University Hospital and Medical Faculty, University of Cologne, Cologne, Germany.,Cognitive Neuroscience (INM-3), Institute of Neuroscience and Medicine, Research Center Jülich, Jülich, Germany
| | - Anja Schneider
- German Center for Neurodegenerative Diseases, Bonn and Cologne, Germany.,Department of Neurodegenerative Diseases and Geriatric Psychiatry, University Hospital Bonn, University of Bonn, Bonn, Germany
| | - Klaus Fliessbach
- German Center for Neurodegenerative Diseases, Bonn and Cologne, Germany.,Department of Neurodegenerative Diseases and Geriatric Psychiatry, University Hospital Bonn, University of Bonn, Bonn, Germany
| | - Merle C Hönig
- Multimodal Neuroimaging, Department of Nuclear Medicine, University Hospital and Medical Faculty, University of Cologne, Cologne, Germany.,Molecular Organization of the Brain (INM-2), Institute of Neuroscience and Medicine, Research Center Jülich, Jülich, Germany
| | - Frank Jessen
- German Center for Neurodegenerative Diseases, Bonn and Cologne, Germany.,Department of Psychiatry, University Hospital and Medical Faculty, University of Cologne, Cologne, Germany.,Excellence Cluster on Cellular Stress Responses in Aging-Associated Diseases, University Hospital and Medical Faculty, University of Cologne, Cologne, Germany; and
| | - Bernd Neumaier
- Nuclear Chemistry (INM-5), Institute of Neuroscience and Medicine, Research Center Jülich, Jülich, Germany, and Institute of Radiochemistry and Experimental Molecular Imaging, University Hospital and Medical Faculty, University of Cologne, Cologne, Germany
| | - Alexander Drzezga
- Multimodal Neuroimaging, Department of Nuclear Medicine, University Hospital and Medical Faculty, University of Cologne, Cologne, Germany.,German Center for Neurodegenerative Diseases, Bonn and Cologne, Germany.,Molecular Organization of the Brain (INM-2), Institute of Neuroscience and Medicine, Research Center Jülich, Jülich, Germany
| | - Thilo van Eimeren
- Multimodal Neuroimaging, Department of Nuclear Medicine, University Hospital and Medical Faculty, University of Cologne, Cologne, Germany.,Department of Neurology, University Hospital and Medical Faculty, University of Cologne, Cologne, Germany.,German Center for Neurodegenerative Diseases, Bonn and Cologne, Germany
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11
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Garabadu D, Agrawal N, Sharma A, Sharma S. Mitochondrial metabolism: a common link between neuroinflammation and neurodegeneration. Behav Pharmacol 2020; 30:642-652. [PMID: 31625975 DOI: 10.1097/fbp.0000000000000505] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
Abstract
Neurodegenerative disorders have been considered as a growing health concern for decades. Increasing risk of neurodegenerative disorders creates a socioeconomic burden to both patients and care givers. Mitochondria are organelle that are involved in both neuroinflammation and neurodegeneration. There are few reports on the effect of mitochondrial metabolism on the progress of neurodegeneration and neuroinflammation. Therefore, the present review summarizes the potential contribution of mitochondrial metabolic pathways in the pathogenesis of neuroinflammation and neurodegeneration. Mitochondrial pyruvate metabolism plays a critical role in the pathogenesis of neurodegenerative disorders such as Parkinson's disease and Alzheimer's disease. However, there its potential contribution in other neurodegenerative disorders is as yet unproven. The mitochondrial pyruvate carrier and pyruvate dehydrogenase can modulate mitochondrial pyruvate metabolism to attenuate neuroinflammation and neurodegeneration. Further, it has been observed that the mitochondrial citric acid cycle can regulate the pathogenesis of neuroinflammation and neurodegeneration. Additional research should be undertaken to target tricarboxylic acid cycle enzymes to minimize the progress of neuroinflammation and neurodegeneration. It has also been observed that the mitochondrial urea cycle can potentially contribute to the progression of neurodegenerative disorders. Therefore, targeting this pathway may control the mitochondrial dysfunction-induced neuroinflammation and neurodegeneration. Furthermore, the mitochondrial malate-aspartate shuttle could be another target to control mitochondrial dysfunction-induced neuroinflammation and neurodegeneration in neurodegenerative disorders.
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Affiliation(s)
- Debapriya Garabadu
- Division of Pharmacology, Institute of Pharmaceutical Research, GLA University, Mathura, India
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12
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Sun X, Liang S, Fu L, Zhang X, Feng T, Li P, Zhang T, Wang L, Yin X, Zhang W, Hu Y, Liu H, Zhao S, Nie B, Xu B, Shan B. A human brain tau PET template in MNI space for the voxel-wise analysis of Alzheimer's disease. J Neurosci Methods 2019; 328:108438. [PMID: 31542346 DOI: 10.1016/j.jneumeth.2019.108438] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2018] [Revised: 09/18/2019] [Accepted: 09/18/2019] [Indexed: 12/15/2022]
Abstract
BACKGROUND Positron emission tomography (PET) imaging techniques of tau retention in the human brain are important for mechanistic studies of Alzheimer's disease (AD). However, the method for effectively conducting voxel-wise analysis on tau PET images still needs to be improved. In the present study, we introduced a tau PET template for the human brain in Montreal Neurological Institute (MNI) space for the convenient and reliable voxel-wise analysis of tau PET images in AD studies. NEW METHOD Twenty-four AD patients and 22 controls were used to construct the tau PET template, and an additional 22 subjects (11 AD patients and 11 controls) were enrolled to evaluate the performance of the template. Thirty regions (28 cortical and 2 subcortical regions) throughout the brain were used to evaluate the accuracy of the tau PET template. RESULTS A significant relationship (R2 = 0.848, P < 0.001) was found between the standardized uptake value ratios (SUVRs) obtained by the tau PET template and magnetic resonance imaging (MRI)-aided approach, and the paired-sample t-test showed no significant difference (P = 0.62) between the values. These two approaches revealed consistent brain regions with high tau retention. COMPARISON WITH EXISTING METHODS The tau PET template was comparable with the traditional MRI-aided strategy. Furthermore, compared to the MRI-aided approach, the tau PET template was more convenient and easier to use. More importantly, in most clinical settings, AD patients who underwent PET/computed tomography (CT) typically do not have MR images, in which case the traditional MRI-aided approach would not be applicable. Our tau PET template overcame this deficiency and may serve as a useful tool in AD research. CONCLUSIONS This tau PET template performed well and may serve as a useful tool in future AD studies.
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Affiliation(s)
- Xi Sun
- College of Physical Science and Technology, Zhengzhou University, Zhengzhou 450001, China; Beijing Engineering Research Center of Radiographic Techniques and Equipment, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
| | - Shengxiang Liang
- National-Local Joint Engineering Research Center of Rehabilitation Medicine Technology, Fujian University of Traditional Chinese Medicine, Fuzhou, Fujian 350122, China; Fujian Key Laboratory of Rehabilitation Technology, Fuzhou, Fujian 350122, China
| | - Liping Fu
- Department of Nuclear Medicine, General Hospital of the Chinese People's Liberation Army, Beijing 100049, China
| | - Xiaojun Zhang
- Department of Nuclear Medicine, General Hospital of the Chinese People's Liberation Army, Beijing 100049, China
| | - Ting Feng
- College of Physical Science and Technology, Zhengzhou University, Zhengzhou 450001, China; Beijing Engineering Research Center of Radiographic Techniques and Equipment, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
| | - Panlong Li
- College of Physical Science and Technology, Zhengzhou University, Zhengzhou 450001, China; Beijing Engineering Research Center of Radiographic Techniques and Equipment, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
| | - Tianhao Zhang
- Beijing Engineering Research Center of Radiographic Techniques and Equipment, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China; School of Nuclear Science and Technology, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Luying Wang
- College of Physical Science and Technology, Zhengzhou University, Zhengzhou 450001, China; Beijing Engineering Research Center of Radiographic Techniques and Equipment, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
| | - Xiaolong Yin
- College of Physical Science and Technology, Zhengzhou University, Zhengzhou 450001, China; Beijing Engineering Research Center of Radiographic Techniques and Equipment, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
| | - Wei Zhang
- Beijing Engineering Research Center of Radiographic Techniques and Equipment, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China; School of Nuclear Science and Technology, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yichao Hu
- Beijing Engineering Research Center of Radiographic Techniques and Equipment, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China; College of Information Engineering, Xiangtan University, Hunan 411105, China
| | - Hua Liu
- Beijing Engineering Research Center of Radiographic Techniques and Equipment, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China; School of Nuclear Science and Technology, University of Chinese Academy of Sciences, Beijing 100049, China; CAS Center for Excellence in Brain Science and Intelligence Technology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Shujun Zhao
- College of Physical Science and Technology, Zhengzhou University, Zhengzhou 450001, China.
| | - Binbin Nie
- Beijing Engineering Research Center of Radiographic Techniques and Equipment, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China; School of Nuclear Science and Technology, University of Chinese Academy of Sciences, Beijing 100049, China; CAS Center for Excellence in Brain Science and Intelligence Technology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China.
| | - Baixuan Xu
- Department of Nuclear Medicine, General Hospital of the Chinese People's Liberation Army, Beijing 100049, China.
| | - Baoci Shan
- Beijing Engineering Research Center of Radiographic Techniques and Equipment, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China; School of Nuclear Science and Technology, University of Chinese Academy of Sciences, Beijing 100049, China; CAS Center for Excellence in Brain Science and Intelligence Technology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China
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Richter N, Nellessen N, Dronse J, Dillen K, Jacobs HIL, Langen KJ, Dietlein M, Kracht L, Neumaier B, Fink GR, Kukolja J, Onur OA. Spatial distributions of cholinergic impairment and neuronal hypometabolism differ in MCI due to AD. NEUROIMAGE-CLINICAL 2019; 24:101978. [PMID: 31422337 PMCID: PMC6706587 DOI: 10.1016/j.nicl.2019.101978] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/08/2019] [Revised: 07/24/2019] [Accepted: 08/08/2019] [Indexed: 12/31/2022]
Abstract
Elucidating the relationship between neuronal metabolism and the integrity of the cholinergic system is prerequisite for a profound understanding of cholinergic dysfunction in Alzheimer's disease. The cholinergic system can be investigated specifically using positron emission tomography (PET) with [11C]N-methyl-4-piperidyl-acetate (MP4A), while neuronal metabolism is often assessed with 2-deoxy-2-[18F]fluoro-d-glucose-(FDG) PET. We hypothesised a close correlation between MP4A-perfusion and FDG-uptake, permitting inferences about metabolism from MP4A-perfusion, and investigated the patterns of neuronal hypometabolism and cholinergic impairment in non-demented AD patients. MP4A-PET was performed in 18 cognitively normal adults and 19 patients with mild cognitive impairment (MCI) and positive AD biomarkers. In nine patients with additional FDG-PET, the sum images of every combination of consecutive early MP4A-frames were correlated with FDG-scans to determine the optimal time window for assessing MP4A-perfusion. Acetylcholinesterase (AChE) activity was estimated using a 3-compartmental model. Group comparisons of MP4A-perfusion and AChE-activity were performed using the entire sample. The highest correlation between MP4A-perfusion and FDG-uptake across the cerebral cortex was observed 60-450 s after injection (r = 0.867). The patterns of hypometabolism (FDG-PET) and hypoperfusion (MP4A-PET) in MCI covered areas known to be hypometabolic early in AD, while AChE activity was mainly reduced in the lateral temporal cortex and the occipital lobe, sparing posterior midline structures. Data indicate that patterns of cholinergic impairment and neuronal hypometabolism differ significantly at the stage of MCI in AD, implying distinct underlying pathologies, and suggesting potential predictors of the response to cholinergic pharmacotherapy.
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Affiliation(s)
- Nils Richter
- Department of Neurology, University Hospital Cologne, 50937 Cologne, Germany; Cognitive Neuroscience, Institute of Neuroscience and Medicine (INM-3), Research Center Jülich, 52425 Jülich, Germany; Max-Planck-Institute for Metabolism Research, 50937 Cologne, Germany.
| | - Nils Nellessen
- Department of Neurology, University Hospital Cologne, 50937 Cologne, Germany; Cognitive Neuroscience, Institute of Neuroscience and Medicine (INM-3), Research Center Jülich, 52425 Jülich, Germany
| | - Julian Dronse
- Department of Neurology, University Hospital Cologne, 50937 Cologne, Germany; Cognitive Neuroscience, Institute of Neuroscience and Medicine (INM-3), Research Center Jülich, 52425 Jülich, Germany
| | - Kim Dillen
- Cognitive Neuroscience, Institute of Neuroscience and Medicine (INM-3), Research Center Jülich, 52425 Jülich, Germany
| | - Heidi I L Jacobs
- Cognitive Neuroscience, Institute of Neuroscience and Medicine (INM-3), Research Center Jülich, 52425 Jülich, Germany; Division of Nuclear Medicine and Molecular Imaging, Department of Radiology, Massachusetts General Hospital/Harvard Medical School, Boston, MA, United States of America; The Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital/Harvard Medical School, Boston, MA, United States of America; Faculty of Health, Medicine and Life Sciences, School for Mental Health and Neuroscience, Alzheimer Centre Limburg, Maastricht University, Maastricht, the Netherlands
| | - Karl-Josef Langen
- Medical Imaging Physics (INM-4), Institute of Neuroscience and Medicine (INM-4), Research Center Jülich, 52425 Jülich, Germany
| | - Markus Dietlein
- Department of Nuclear Medicine, University Hospital Cologne, 50937 Cologne, Germany
| | - Lutz Kracht
- Max-Planck-Institute for Metabolism Research, 50937 Cologne, Germany; Department of Nuclear Medicine, University Hospital Cologne, 50937 Cologne, Germany
| | - Bernd Neumaier
- Institute for Radiochemistry and Experimental Molecular Imaging, University Hospital Cologne, 50937 Cologne, Germany; Nuclear Chemistry, Institute of Neuroscience and Medicine (INM-5), Research Center Jülich, 52425 Jülich, Germany
| | - Gereon R Fink
- Department of Neurology, University Hospital Cologne, 50937 Cologne, Germany; Cognitive Neuroscience, Institute of Neuroscience and Medicine (INM-3), Research Center Jülich, 52425 Jülich, Germany
| | - Juraj Kukolja
- Cognitive Neuroscience, Institute of Neuroscience and Medicine (INM-3), Research Center Jülich, 52425 Jülich, Germany; Department of Neurology and Neurophysiology, Helios University Hospital Wuppertal, 42283 Wuppertal, Germany
| | - Oezguer A Onur
- Department of Neurology, University Hospital Cologne, 50937 Cologne, Germany; Cognitive Neuroscience, Institute of Neuroscience and Medicine (INM-3), Research Center Jülich, 52425 Jülich, Germany
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Peretti DE, Vállez García D, Reesink FE, Doorduin J, de Jong BM, De Deyn PP, Dierckx RAJO, Boellaard R. Diagnostic performance of regional cerebral blood flow images derived from dynamic PIB scans in Alzheimer's disease. EJNMMI Res 2019; 9:59. [PMID: 31273465 PMCID: PMC6609664 DOI: 10.1186/s13550-019-0528-3] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2019] [Accepted: 06/20/2019] [Indexed: 12/28/2022] Open
Abstract
BACKGROUND In clinical practice, visual assessment of glucose metabolism images is often used for the diagnosis of Alzheimer's disease (AD) through 2-[18F]-fluoro-2-deoxy-D-glucose (FDG) positron emission tomography (PET) scans. However, visual assessment of the characteristic AD hypometabolic pattern relies on the expertise of the reader. Therefore, user-independent pipelines are preferred to evaluate the images and to classify the subjects. Moreover, glucose consumption is highly correlated with cerebral perfusion. Regional cerebral blood flow (rCBF) images can be derived from dynamic 11C-labelled Pittsburgh Compound B PET scans, which are also used for the assessment of the deposition of amyloid-β plaques on the brain, a fundamental characteristic of AD. The aim of this study was to explore whether these rCBF PIB images could be used for diagnostic purposes through the PMOD Alzheimer's Discrimination Tool. RESULTS Both tracer relative cerebral flow (R1) and early PIB (ePIB) (20-130 s) uptake presented a good correlation when compared to FDG standardized uptake value ratio (SUVR), while ePIB (1-8 min) showed a worse correlation. All receiver operating characteristic curves exhibited a similar shape, with high area under the curve values, and no statistically significant differences were found between curves. However, R1 and ePIB (1-8 min) had the highest sensitivity, while FDG SUVR had the highest specificity. CONCLUSION rCBF images were suggested to be a good surrogate for FDG scans for diagnostic purposes considering an adjusted threshold value.
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Affiliation(s)
- Débora E. Peretti
- Department of Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, University of Groningen, Hanzeplein 1, 9713 GZ Groningen, The Netherlands
| | - David Vállez García
- Department of Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, University of Groningen, Hanzeplein 1, 9713 GZ Groningen, The Netherlands
| | - Fransje E. Reesink
- Department of Neurology, Alzheimer Centrum Groningen, University Medical Center Groningen, University of Groningen, Hanzeplein 1, 9713 GZ Groningen, The Netherlands
| | - Janine Doorduin
- Department of Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, University of Groningen, Hanzeplein 1, 9713 GZ Groningen, The Netherlands
| | - Bauke M. de Jong
- Department of Neurology, Alzheimer Centrum Groningen, University Medical Center Groningen, University of Groningen, Hanzeplein 1, 9713 GZ Groningen, The Netherlands
| | - Peter P. De Deyn
- Department of Neurology, Alzheimer Centrum Groningen, University Medical Center Groningen, University of Groningen, Hanzeplein 1, 9713 GZ Groningen, The Netherlands
- Laboratory of Neurochemistry and Behaviour, Institute Born-Bunge, University of Antwerp, Universiteitsplein 1, 2610 Antwerpen, Belgium
| | - Rudi A. J. O. Dierckx
- Department of Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, University of Groningen, Hanzeplein 1, 9713 GZ Groningen, The Netherlands
| | - Ronald Boellaard
- Department of Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, University of Groningen, Hanzeplein 1, 9713 GZ Groningen, The Netherlands
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Abstract
PURPOSE OF REVIEW Differential diagnosis of atypical Parkinson syndromes (APS) is difficult as clinical presentations may vary and as there is a strong overlap between disease entities. Aggregations of misfolded and hyperphosphorylated tau proteins are the common denominator of many of these diseases. RECENT FINDINGS Several tau targeting positron emission tomography (PET) tracers have been evaluated as possible biomarkers in APS in the recent years. For Parkinson's disease, dementia with Lewy bodies, progressive supranuclear palsy, and corticobasal degeneration, promising results have been reported with regard to the ability to detect the presence of disease and to discriminate patients from controls. However, the discussion about the specificity of the first-generation radiotracers and their value in the clinical context is ongoing. A combined interpretation of signal strength and distribution pattern in PET scans with first- and second-generation tracers may be helpful in clinical diagnosis and follow-up of patients with APS.
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