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Jagust WJ, Mattay VS, Krainak DM, Wang SJ, Weidner LD, Hofling AA, Koo H, Hsieh P, Kuo PH, Farrar G, Marzella L. Quantitative Brain Amyloid PET. J Nucl Med 2024; 65:670-678. [PMID: 38514082 PMCID: PMC11064834 DOI: 10.2967/jnumed.123.265766] [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] [Received: 09/19/2023] [Revised: 02/13/2024] [Indexed: 03/23/2024] Open
Abstract
Since the development of amyloid tracers for PET imaging, there has been interest in quantifying amyloid burden in the brains of patients with Alzheimer disease. Quantitative amyloid PET imaging is poised to become a valuable approach in disease staging, theranostics, monitoring, and as an outcome measure for interventional studies. Yet, there are significant challenges and hurdles to overcome before it can be implemented into widespread clinical practice. On November 17, 2022, the U.S. Food and Drug Administration, Society of Nuclear Medicine and Molecular Imaging, and Medical Imaging and Technology Alliance cosponsored a public workshop comprising experts from academia, industry, and government agencies to discuss the role of quantitative brain amyloid PET imaging in staging, prognosis, and longitudinal assessment of Alzheimer disease. The workshop discussed a range of topics, including available radiopharmaceuticals for amyloid imaging; the methodology, metrics, and analytic validity of quantitative amyloid PET imaging; its use in disease staging, prognosis, and monitoring of progression; and challenges facing the field. This report provides a high-level summary of the presentations and the discussion.
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Affiliation(s)
| | - Venkata S Mattay
- Division of Imaging and Radiation Medicine, Office of Specialty Medicine, Office of New Drugs, Center of Drug Evaluation and Research, Food and Drug Administration, Silver Spring, Maryland;
| | - Daniel M Krainak
- Division of Radiological Imaging and Radiation Therapy Devices, Office of Radiological Health, Office of Product Evaluation and Quality, Centers for Devices and Radiological Health, Food and Drug Administration, Silver Spring, Maryland
| | - Sue-Jane Wang
- Division of Biometrics I, Office of Biostatistics, Office of Translational Sciences, Center of Drug Evaluation and Research, Food and Drug Administration, Silver Spring, Maryland
| | - Lora D Weidner
- Division of Radiological Imaging and Radiation Therapy Devices, Office of Radiological Health, Office of Product Evaluation and Quality, Centers for Devices and Radiological Health, Food and Drug Administration, Silver Spring, Maryland
| | - A Alex Hofling
- Division of Imaging and Radiation Medicine, Office of Specialty Medicine, Office of New Drugs, Center of Drug Evaluation and Research, Food and Drug Administration, Silver Spring, Maryland
| | - Hayoung Koo
- Division of Imaging and Radiation Medicine, Office of Specialty Medicine, Office of New Drugs, Center of Drug Evaluation and Research, Food and Drug Administration, Silver Spring, Maryland
| | | | | | | | - Libero Marzella
- Division of Imaging and Radiation Medicine, Office of Specialty Medicine, Office of New Drugs, Center of Drug Evaluation and Research, Food and Drug Administration, Silver Spring, Maryland
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2
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Smith AM, Obuchowski NA, Foster NL, Klein G, Mozley PD, Lammertsma AA, Wahl RL, Sunderland JJ, Vanderheyden JL, Benzinger TLS, Kinahan PE, Wong DF, Perlman ES, Minoshima S, Matthews D. The RSNA QIBA Profile for Amyloid PET as an Imaging Biomarker for Cerebral Amyloid Quantification. J Nucl Med 2023; 64:294-303. [PMID: 36137760 PMCID: PMC9902844 DOI: 10.2967/jnumed.122.264031] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2022] [Revised: 08/05/2022] [Accepted: 08/05/2022] [Indexed: 02/04/2023] Open
Abstract
A standardized approach to acquiring amyloid PET images increases their value as disease and drug response biomarkers. Most 18F PET amyloid brain scans often are assessed only visually (per regulatory labels), with a binary decision indicating the presence or absence of Alzheimer disease amyloid pathology. Minimizing technical variance allows precise, quantitative SUV ratios (SUVRs) for early detection of β-amyloid plaques and allows the effectiveness of antiamyloid treatments to be assessed with serial studies. Methods: The Quantitative Imaging Biomarkers Alliance amyloid PET biomarker committee developed and validated a profile to characterize and reduce the variability of SUVRs, increasing statistical power for these assessments. Results: On achieving conformance, sites can justify a claim that brain amyloid burden reflected by the SUVR is measurable to a within-subject coefficient of variation of no more than 1.94% when the same radiopharmaceutical, scanner, acquisition, and analysis protocols are used. Conclusion: This overview explains the claim, requirements, barriers, and potential future developments of the profile to achieve precision in clinical and research amyloid PET imaging.
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Affiliation(s)
- Anne M Smith
- Siemens Medical Solutions USA, Inc., Knoxville, Tennessee;
| | | | - Norman L Foster
- Department of Neurology, University of Utah, Salt Lake City, Utah
| | | | - P David Mozley
- Weill Medical College of Cornell University, New York, New York
| | - Adriaan A Lammertsma
- Amsterdam Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, Location VUmc, Amsterdam, The Netherlands
- Medical Imaging Center, Department of Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Richard L Wahl
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, Missouri
- Department of Radiation Oncology, Washington University in Saint Louis, St. Louis, Missouri
| | - John J Sunderland
- Division of Nuclear Medicine, Department of Radiology, University of Iowa, Iowa City, Iowa
| | | | - Tammie L S Benzinger
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, Missouri
- Department of Radiation Oncology, Washington University in Saint Louis, St. Louis, Missouri
| | - Paul E Kinahan
- Department of Radiology, School of Medicine, University of Washington, Seattle, Washington
| | - Dean F Wong
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, Missouri
| | | | - Satoshi Minoshima
- Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, Utah; and
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3
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Scott CJ, Jiao J, Melbourne A, Burgos N, Cash DM, De Vita E, Markiewicz PJ, O'Connor A, Thomas DL, Weston PS, Schott JM, Hutton BF, Ourselin S. Reduced acquisition time PET pharmacokinetic modelling using simultaneous ASL-MRI: proof of concept. J Cereb Blood Flow Metab 2019; 39:2419-2432. [PMID: 30182792 PMCID: PMC6891000 DOI: 10.1177/0271678x18797343] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/31/2023]
Abstract
Pharmacokinetic modelling on dynamic positron emission tomography (PET) data is a quantitative technique. However, the long acquisition time is prohibitive for routine clinical use. Instead, the semi-quantitative standardised uptake value ratio (SUVR) from a shorter static acquisition is used, despite its sensitivity to blood flow confounding longitudinal analysis. A method has been proposed to reduce the dynamic acquisition time for quantification by incorporating cerebral blood flow (CBF) information from arterial spin labelling (ASL) magnetic resonance imaging (MRI) into the pharmacokinetic modelling. In this work, we optimise and validate this framework for a study of ageing and preclinical Alzheimer's disease. This methodology adapts the simplified reference tissue model (SRTM) for a reduced acquisition time (RT-SRTM) and is applied to [18F]-florbetapir PET data for amyloid-β quantification. Evaluation shows that the optimised RT-SRTM can achieve amyloid burden estimation from a 30-min PET/MR acquisition which is comparable with the gold standard SRTM applied to 60 min of PET data. Conversely, SUVR showed a significantly higher error and bias, and a statistically significant correlation with tracer delivery due to the influence of blood flow. The optimised RT-SRTM produced amyloid burden estimates which were uncorrelated with tracer delivery indicating its suitability for longitudinal studies.
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Affiliation(s)
- Catherine J Scott
- Translational Imaging Group, CMIC, University College London, London, UK
| | - Jieqing Jiao
- Translational Imaging Group, CMIC, University College London, London, UK
| | - Andrew Melbourne
- Translational Imaging Group, CMIC, University College London, London, UK
| | - Ninon Burgos
- Translational Imaging Group, CMIC, University College London, London, UK.,Inria, Aramis project-team, Institut du Cerveau et de la Moelle épinière, Inserm, CNRS, Sorbonne Université, Paris, France
| | - David M Cash
- Translational Imaging Group, CMIC, University College London, London, UK.,Dementia Research Centre, Institute of Neurology, University College London, London, UK
| | - Enrico De Vita
- Neuroradiological Academic Unit, UCL Institute of Neurology, London, UK.,Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, UCL Hospitals Foundation Trust, London, UK.,Department of Biomedical Engineering, School of Biomedical Engineering & Imaging Sciences, King's College London, King's Health Partners, St Thomas' Hospital, London, UK
| | - Pawel J Markiewicz
- Translational Imaging Group, CMIC, University College London, London, UK
| | - Antoinette O'Connor
- Dementia Research Centre, Institute of Neurology, University College London, London, UK
| | - David L Thomas
- Translational Imaging Group, CMIC, University College London, London, UK.,Neuroradiological Academic Unit, UCL Institute of Neurology, London, UK.,Leonard Wolfson Experimental Neurology Centre, UCL Institute of Neurology London, UK
| | - Philip Sj Weston
- Dementia Research Centre, Institute of Neurology, University College London, London, UK
| | - Jonathan M Schott
- Dementia Research Centre, Institute of Neurology, University College London, London, UK
| | - Brian F Hutton
- Institute of Nuclear Medicine, University College London, London, UK.,Centre for Medical Radiation Physics, University of Wollongong, NSW, Australia
| | - Sébastien Ourselin
- School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK
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Lois C, Gonzalez I, Johnson KA, Price JC. PET imaging of tau protein targets: a methodology perspective. Brain Imaging Behav 2019; 13:333-344. [PMID: 29497982 PMCID: PMC6119534 DOI: 10.1007/s11682-018-9847-7] [Citation(s) in RCA: 36] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/17/2022]
Abstract
The two neuropathological hallmarks of Alzheimer's disease (AD) are amyloid-[Formula: see text] plaques and neurofibrillary tangles of tau protein. Fifteen years ago, Positron Emission Tomography (PET) with Pittsburgh Compound B (11C-PiB) enabled selective in-vivo visualization of amyloid-[Formula: see text] plaque deposits and has since provided valuable information about the role of amyloid-[Formula: see text] deposition in AD. The progression of tau deposition has been shown to be highly associated with neuronal loss, neurodegeneration, and cognitive decline. Until recently it was not possible to visualize tau deposition in-vivo, but several tau PET tracers are now available in different stages of clinical development. To date, no tau tracer has been approved by the Food and Drug Administration for use in the evaluation of AD or other tauopathies, despite very active research efforts. In this paper we review the recent developments in tau PET imaging with a focus on in-vivo findings in AD and discuss the challenges associated with tau tracer development, the status of development and validation of different tau tracers, and the clinical information these provide.
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Affiliation(s)
- Cristina Lois
- Gordon Center for Medical Imaging, Division of Nuclear Medicine and Molecular Imaging, Department of Radiology, Massachusetts General Hospital / Harvard Medical School, Boston, MA, USA.
| | - Ivan Gonzalez
- Athinoula A. Martinos Center for Biomedical Research, Department of Radiology, Massachusetts General Hospital / Harvard Medical School, Boston, MA, USA
| | - Keith A Johnson
- Gordon Center for Medical Imaging, Division of Nuclear Medicine and Molecular Imaging, Department of Radiology, Massachusetts General Hospital / Harvard Medical School, Boston, MA, USA
| | - Julie C Price
- Athinoula A. Martinos Center for Biomedical Research, Department of Radiology, Massachusetts General Hospital / Harvard Medical School, Boston, MA, USA
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5
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Wooten DW, Guehl NJ, Verwer EE, Shoup TM, Yokell DL, Zubcevik N, Vasdev N, Zafonte RD, Johnson KA, El Fakhri G, Normandin MD. Pharmacokinetic Evaluation of the Tau PET Radiotracer 18F-T807 ( 18F-AV-1451) in Human Subjects. J Nucl Med 2016; 58:484-491. [PMID: 27660144 DOI: 10.2967/jnumed.115.170910] [Citation(s) in RCA: 65] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2016] [Accepted: 08/26/2016] [Indexed: 12/14/2022] Open
Abstract
18F-T807 is a PET radiotracer developed for imaging tau protein aggregates, which are implicated in neurologic disorders including Alzheimer disease and traumatic brain injury (TBI). The current study characterizes 18F-T807 pharmacokinetics in human subjects using dynamic PET imaging and metabolite-corrected arterial input functions. Methods: Nine subjects (4 controls, 3 with a history of TBI, 2 with mild cognitive impairment due to suspected Alzheimer disease) underwent dynamic PET imaging for up to 120 min after bolus injection of 18F-T807 with arterial blood sampling. Total volume of distribution (VT) was estimated using compartmental modeling (1- and 2-tissue configurations) and graphical analysis techniques (Logan and multilinear analysis 1 [MA1] regression methods). Reference region-based methods of quantification were explored including Logan distribution volume ratio (DVR) and static SUV ratio (SUVR) using the cerebellum as a reference tissue. Results: The percentage of unmetabolized 18F-T807 in plasma followed a single exponential with a half-life of 17.0 ± 4.2 min. Metabolite-corrected plasma radioactivity concentration fit a biexponential (half-lives, 18.1 ± 5.8 and 2.4 ± 0.5 min). 18F-T807 in gray matter peaked quickly (SUV > 2 at ∼5 min). Compartmental modeling resulted in good fits, and the 2-tissue model with estimated blood volume correction (2Tv) performed best, particularly in regions with elevated binding. VT was greater in mild cognitive impairment subjects than controls in the occipital, parietal, and temporal cortices as well as the posterior cingulate gyrus, precuneus, and mesial temporal cortex. High focal uptake was found in the posterior corpus callosum of a TBI subject. Plots from Logan and MA1 graphical methods became linear by 30 min, yielding regional estimates of VT in excellent agreement with compartmental analysis and providing high-quality parametric maps when applied in voxelwise fashion. Reference region-based approaches including Logan DVR (t* = 55 min) and SUVR (80- to 100-min interval) were highly correlated with DVR estimated using 2Tv (R2 = 0.97, P < 0.0001). Conclusion:18F-T807 showed rapid clearance from plasma and properties suitable for tau quantification with PET. Furthermore, simplified approaches using DVR (t* = 55 min) and static SUVR (80-100 min) with cerebellar reference tissue were found to correlate highly with compartmental modeling outcomes.
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Affiliation(s)
- Dustin W Wooten
- Gordon Center for Medical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts.,Division of Nuclear Medicine and Molecular Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| | - Nicolas J Guehl
- Gordon Center for Medical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts.,Division of Nuclear Medicine and Molecular Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| | - Eline E Verwer
- Gordon Center for Medical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts.,Division of Nuclear Medicine and Molecular Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| | - Timothy M Shoup
- Gordon Center for Medical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts.,Division of Nuclear Medicine and Molecular Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| | - Daniel L Yokell
- Gordon Center for Medical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts.,Division of Nuclear Medicine and Molecular Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| | - Nevena Zubcevik
- Department of Physical Medicine and Rehabilitation, Spaulding Rehabilitation Hospital, Massachusetts General Hospital, Boston, Massachusetts; and
| | - Neil Vasdev
- Gordon Center for Medical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts.,Division of Nuclear Medicine and Molecular Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| | - Ross D Zafonte
- Department of Physical Medicine and Rehabilitation, Spaulding Rehabilitation Hospital, Massachusetts General Hospital, Boston, Massachusetts; and.,Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts
| | - Keith A Johnson
- Division of Nuclear Medicine and Molecular Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| | - Georges El Fakhri
- Gordon Center for Medical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts.,Division of Nuclear Medicine and Molecular Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| | - Marc D Normandin
- Gordon Center for Medical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts .,Division of Nuclear Medicine and Molecular Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
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Dumas N, Moulin-Sallanon M, Fender P, Tournier BB, Ginovart N, Charnay Y, Millet P. In Vivo Quantification of 5-HT2A Brain Receptors in Mdr1a KO Rats with 123I-R91150 Single-Photon Emission Computed Tomography. Mol Imaging 2016; 14. [PMID: 26105563 DOI: 10.2310/7290.2015.00006] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Our goal was to identify suitable image quantification methods to image 5-hydroxytryptamine2A (5-HT2A) receptors in vivo in Mdr1a knockout (KO) rats (i.e., P-glycoprotein KO) using 123I-R91150 single-photon emission computed tomography (SPECT). The 123I-R91150 binding parameters estimated with different reference tissue models (simplified reference tissue model [SRTM], Logan reference tissue model, and tissue ratio [TR] method) were compared to the estimates obtained with a comprehensive three-tissue/seven-parameter (3T/7k)-based model. The SRTM and Logan reference tissue model estimates of 5-HT2A receptor (5-HT2AR) nondisplaceable binding potential (BPND) correlated well with the absolute receptor density measured with the 3T/7k gold standard (r > .89). Quantification of 5-HT2AR using the Logan reference tissue model required at least 90 minutes of scanning, whereas the SRTM required at least 110 minutes. The TR method estimates were also highly correlated to the 5-HT2AR density (r > .91) and only required a single 20-minute scan between 100 and 120 minutes postinjection. However, a systematic overestimation of the BPND values was observed. The Logan reference tissue method is more convenient than the SRTM for the quantification of 5-HT2AR in Mdr1a KO rats using 123I-R91150 SPECT. The TR method is an interesting and simple alternative, despite its bias, as it still provides a valid index of 5-HT2AR density.
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7
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Gunn RN, Slifstein M, Searle GE, Price JC. Quantitative imaging of protein targets in the human brain with PET. Phys Med Biol 2015; 60:R363-411. [DOI: 10.1088/0031-9155/60/22/r363] [Citation(s) in RCA: 48] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
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9
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Chen YJ, Rosario BL, Mowrey W, Laymon CM, Lu X, Lopez OL, Klunk WE, Lopresti BJ, Mathis CA, Price JC. Relative 11C-PiB Delivery as a Proxy of Relative CBF: Quantitative Evaluation Using Single-Session 15O-Water and 11C-PiB PET. J Nucl Med 2015; 56:1199-205. [PMID: 26045309 DOI: 10.2967/jnumed.114.152405] [Citation(s) in RCA: 54] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2014] [Accepted: 05/24/2015] [Indexed: 11/16/2022] Open
Abstract
UNLABELLED The primary goal of this study was to assess the suitability of (11)C-Pittsburgh compound B ((11)C-PiB) blood-brain barrier delivery (K1) and relative delivery (R1) parameters as surrogate indices of cerebral blood flow (CBF), with a secondary goal of directly examining the extent to which simplified uptake measures of (11)C-PiB retention (amyloid-β load) may be influenced by CBF, in a cohort of controls and patients with mild cognitive impairment (MCI) and Alzheimer disease (AD). METHODS Nineteen participants (6 controls, 5 AD, 8 MCI) underwent MR imaging, (15)O-water PET, and (11)C-PiB PET in a single session. Fourteen regions of interest (including cerebellar reference region) were defined on MR imaging and applied to dynamic coregistered PET to generate time-activity curves. Multiple analysis approaches provided regional (15)O-water and (11)C-PiB measures of delivery and (11)C-PiB retention that included compartmental modeling distribution volume ratio (DVR), arterial- and reference-based Logan DVR, simplified reference tissue modeling 2 (SRTM2) DVR, and standardized uptake value ratios. Spearman correlation was performed among delivery measures (i.e., (15)O-water K1 and (11)C-PiB K1, relative K1 normalized to cerebellum [Rel-K1-Water and Rel-K1-PiB], and (11)C-PiB SRTM2-R1) and between delivery measures and (11)C-PiB retention, using the Bonferroni method for multiple-comparison correction. RESULTS Primary analysis showed positive correlations (ρ ≈0.2-0.5) between (15)O-water K1 and (11)C-PiB K1 that did not survive Bonferroni adjustment. Significant positive correlations were found between Rel-K1-Water and Rel-K1-PiB and between Rel-K1-Water and (11)C-PiB SRTM2-R1 (ρ ≈0.5-0.8, P < 0.0036) across primary cortical regions. Secondary analysis showed few significant correlations between (11)C-PiB retention and relative (11)C-PiB delivery measures (but not (15)O-water delivery measures) in primary cortical areas that arose only after accounting for cerebrospinal fluid dilution. CONCLUSION (11)C-PiB SRTM2-R1 is highly correlated with regional relative CBF, as measured by (15)O-water K1 normalized to cerebellum, and cross-sectional (11)C-PiB retention did not strongly depend on CBF across primary cortical regions. These results provide further support for potential dual-imaging assessments of regional brain status (i.e., amyloid-β load and relative CBF) through dynamic (11)C-PiB imaging.
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Affiliation(s)
- Yin J Chen
- Department of Radiology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Bedda L Rosario
- Department of Biostatistics, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Wenzhu Mowrey
- Department of Biostatistics, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Charles M Laymon
- Department of Radiology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Xueling Lu
- Department of Radiology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Oscar L Lopez
- Department of Neurology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania; and
| | - William E Klunk
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Brian J Lopresti
- Department of Radiology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Chester A Mathis
- Department of Radiology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Julie C Price
- Department of Radiology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
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10
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Logan J, Kim SW, Pareto D, Telang F, Wang GJ, Fowler JS, Biegon A. Kinetic Analysis of [11C]Vorozole Binding in the Human Brain with Positron Emission Tomography. Mol Imaging 2014. [DOI: 10.2310/7290.2014.00004] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Affiliation(s)
- Jean Logan
- From the Biosciences Department, Brookhaven National Laboratory, Upton, NY; National Institute on Alcoholism and Alcohol Abuse, Bethesda, MD; Magnetic Resonance Unit Hospital Vall Hebron, Psg Vall Hebron 119–129, Barcelona, Spain; CIBER BBN, Zaragoza, Spain; Department of Psychiatry, Mount Sinai School of Medicine, New York, NY; Department of Chemistry, State University of New York at Stony Brook, Stony Brook, NY; and Department of Neurology, Stony Brook University School of Medicine, Stony Brook, NY
| | - Sung Won Kim
- From the Biosciences Department, Brookhaven National Laboratory, Upton, NY; National Institute on Alcoholism and Alcohol Abuse, Bethesda, MD; Magnetic Resonance Unit Hospital Vall Hebron, Psg Vall Hebron 119–129, Barcelona, Spain; CIBER BBN, Zaragoza, Spain; Department of Psychiatry, Mount Sinai School of Medicine, New York, NY; Department of Chemistry, State University of New York at Stony Brook, Stony Brook, NY; and Department of Neurology, Stony Brook University School of Medicine, Stony Brook, NY
| | - Deborah Pareto
- From the Biosciences Department, Brookhaven National Laboratory, Upton, NY; National Institute on Alcoholism and Alcohol Abuse, Bethesda, MD; Magnetic Resonance Unit Hospital Vall Hebron, Psg Vall Hebron 119–129, Barcelona, Spain; CIBER BBN, Zaragoza, Spain; Department of Psychiatry, Mount Sinai School of Medicine, New York, NY; Department of Chemistry, State University of New York at Stony Brook, Stony Brook, NY; and Department of Neurology, Stony Brook University School of Medicine, Stony Brook, NY
| | - Frank Telang
- From the Biosciences Department, Brookhaven National Laboratory, Upton, NY; National Institute on Alcoholism and Alcohol Abuse, Bethesda, MD; Magnetic Resonance Unit Hospital Vall Hebron, Psg Vall Hebron 119–129, Barcelona, Spain; CIBER BBN, Zaragoza, Spain; Department of Psychiatry, Mount Sinai School of Medicine, New York, NY; Department of Chemistry, State University of New York at Stony Brook, Stony Brook, NY; and Department of Neurology, Stony Brook University School of Medicine, Stony Brook, NY
| | - Gene-Jack Wang
- From the Biosciences Department, Brookhaven National Laboratory, Upton, NY; National Institute on Alcoholism and Alcohol Abuse, Bethesda, MD; Magnetic Resonance Unit Hospital Vall Hebron, Psg Vall Hebron 119–129, Barcelona, Spain; CIBER BBN, Zaragoza, Spain; Department of Psychiatry, Mount Sinai School of Medicine, New York, NY; Department of Chemistry, State University of New York at Stony Brook, Stony Brook, NY; and Department of Neurology, Stony Brook University School of Medicine, Stony Brook, NY
| | - Joanna S. Fowler
- From the Biosciences Department, Brookhaven National Laboratory, Upton, NY; National Institute on Alcoholism and Alcohol Abuse, Bethesda, MD; Magnetic Resonance Unit Hospital Vall Hebron, Psg Vall Hebron 119–129, Barcelona, Spain; CIBER BBN, Zaragoza, Spain; Department of Psychiatry, Mount Sinai School of Medicine, New York, NY; Department of Chemistry, State University of New York at Stony Brook, Stony Brook, NY; and Department of Neurology, Stony Brook University School of Medicine, Stony Brook, NY
| | - Anat Biegon
- From the Biosciences Department, Brookhaven National Laboratory, Upton, NY; National Institute on Alcoholism and Alcohol Abuse, Bethesda, MD; Magnetic Resonance Unit Hospital Vall Hebron, Psg Vall Hebron 119–129, Barcelona, Spain; CIBER BBN, Zaragoza, Spain; Department of Psychiatry, Mount Sinai School of Medicine, New York, NY; Department of Chemistry, State University of New York at Stony Brook, Stony Brook, NY; and Department of Neurology, Stony Brook University School of Medicine, Stony Brook, NY
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11
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Hwang DR, Hu E, Rumfelt S, Easwaramoorthy B, Castrillon J, Davis C, Allen JR, Chen H, Treanor J, Abi-Dargham A, Slifstein M. Initial characterization of a PDE10A selective positron emission tomography tracer [11C]AMG 7980 in non-human primates. Nucl Med Biol 2014; 41:343-9. [PMID: 24607437 DOI: 10.1016/j.nucmedbio.2014.01.007] [Citation(s) in RCA: 21] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2013] [Revised: 12/19/2013] [Accepted: 01/07/2014] [Indexed: 10/25/2022]
Abstract
INTRODUCTION Phosphodiesterase 10A (PDE10A) is an intracellular enzyme responsible for the breakdown of cyclic nucleotides which are important secondary messengers in the central nervous system. Inhibition of PDE10A has been identified as a potential therapeutic target for treatment of various neuropsychiatric disorders. To assist the drug development program, we have identified a selective PDE10A PET tracer, [(11)C]AMG 7980, for imaging PDE10A distribution using positron emission tomography. METHODS [(11)C]AMG 7980 was prepared in a one-pot, two-step reaction. Dynamic PET scans were performed in non-human primates following a bolus or bolus plus constant infusion tracer injection paradigm. Regions-of-interest were defined on individuals' MRIs and transferred to the co-registered PET images. Data were analyzed using Logan graphical analysis with metabolite-corrected input function, the simplified reference tissue model (SRTM) method and occupancy plots. A benchmark PDE10A inhibitor was used to demonstrate PDE10A-specific binding. RESULTS [(11)C]AMG 7980 was prepared with a mean specific activity of 99 ± 74 GBq/μmol (n=10) and a synthesis time of 45 min. Specific binding of the tracer was localized to the striatum and globus pallidus (GP) and low in other brain regions. Thalamus was used as the reference tissue to derive binding potentials (BPND). The BPND for caudate, putamen, and GP were 0.23, 0.65, 0.51, respectively by the graphical method, and 0.42, 0.76, and 0.75 from the SRTM method. A dose dependent decrease of BPND was observed with the pre-treatment of a PDE10A inhibitor. A bolus plus infusion injection paradigm yielded similar results. CONCLUSION [(11)C]AMG 7980 has been successfully used for imaging PDE10A in non-human primate brain. Despite the fast brain kinetics it can be used to measure target occupancy of PDE10A inhibitors in non-human primates and potentially applicable to humans.
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Affiliation(s)
- Dah-Ren Hwang
- Department of Medical Sciences, Amgen Inc., 1 Amgen Center Drive, Thousand Oaks, California 91320-1799, United States.
| | - Essa Hu
- Department of Small Molecule Chemistry, Amgen Inc., 1 Amgen Center Drive, Thousand Oaks, California 91320-1799, United States
| | - Shannon Rumfelt
- Department of Small Molecule Chemistry, Amgen Inc., 1 Amgen Center Drive, Thousand Oaks, California 91320-1799, United States
| | - Balu Easwaramoorthy
- Department of Psychiatry, Columbia University, New York, NY, USA; New York State Psychiatric Institute, NY, USA
| | | | - Carl Davis
- Department of Pharmacokinetics and Drug Metabolism, Amgen Inc., 1 Amgen Center Drive, Thousand Oaks, California 91320-1799, United States
| | - Jennifer R Allen
- Department of Small Molecule Chemistry, Amgen Inc., 1 Amgen Center Drive, Thousand Oaks, California 91320-1799, United States
| | - Hang Chen
- Department of Neuroscience, Amgen Inc., South San Francisco, CA
| | - James Treanor
- Department of Neuroscience, Amgen Inc., 1 Amgen Center Drive, Thousand Oaks, California 91320-1799, United States
| | - Anissa Abi-Dargham
- Department of Psychiatry, Columbia University, New York, NY, USA; Department of Radiology, Columbia University, New York, NY, USA; New York State Psychiatric Institute, NY, USA
| | - Mark Slifstein
- Department of Psychiatry, Columbia University, New York, NY, USA; New York State Psychiatric Institute, NY, USA
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Zheng P, Lieberman BP, Ploessl K, Lemoine L, Miller S, Kung HF. A new single-photon emission computed tomography (SPECT) imaging agent for serotonin transporters: [(125)I]Flip-IDAM, (2-((2-((dimethylamino)methyl)-4-iodophenyl)thio)phenyl)methanol. Bioorg Med Chem Lett 2013; 23:869-72. [PMID: 23265880 DOI: 10.1016/j.bmcl.2012.11.043] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2012] [Revised: 11/07/2012] [Accepted: 11/12/2012] [Indexed: 11/18/2022]
Abstract
New ligands for in vivo brain imaging of serotonin transporter (SERT) with single photon emission tomography (SPECT) were prepared and evaluated. An efficient synthesis and radiolabeling of a biphenylthiol, FLIP-IDAM, 4, was accomplished. The affinity of FLIP-IDAM was evaluated by an in vitro inhibitory binding assay using [(125)I]-IDAM as radioligand in rat brain tissue homogenates (K(i) = 0.03 nM). New [(125)I]Flip-IDAM exhibited excellent binding affinity to SERT binding sites with a high hypothalamus to cerebellum ratio of 4 at 30 min post iv injection. The faster in vivo kinetics for brain uptake and a rapid washout from non-specific regions provide excellent signal to noise ratio. This new agent, when labeled with (123)I, may be a useful imaging agent for mapping SERT binding sites in the human brain.
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Affiliation(s)
- Pinguan Zheng
- Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104, USA
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13
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Zhou Y, Sojkova J, Resnick SM, Wong DF. Relative equilibrium plot improves graphical analysis and allows bias correction of standardized uptake value ratio in quantitative 11C-PiB PET studies. J Nucl Med 2012; 53:622-8. [PMID: 22414634 PMCID: PMC3449083 DOI: 10.2967/jnumed.111.095927] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
UNLABELLED Both the standardized uptake value ratio (SUVR) and the Logan plot result in biased distribution volume ratios (DVRs) in ligand-receptor dynamic PET studies. The objective of this study was to use a recently developed relative equilibrium-based graphical (RE) plot method to improve and simplify the 2 commonly used methods for quantification of (11)C-Pittsburgh compound B ((11)C-PiB) PET. METHODS The overestimation of DVR in SUVR was analyzed theoretically using the Logan and the RE plots. A bias-corrected SUVR (bcSUVR) was derived from the RE plot. Seventy-eight (11)C-PiB dynamic PET scans (66 from controls and 12 from participants with mild cognitive impaired [MCI] from the Baltimore Longitudinal Study of Aging) were acquired over 90 min. Regions of interest (ROIs) were defined on coregistered MR images. Both the ROI and the pixelwise time-activity curves were used to evaluate the estimates of DVR. DVRs obtained using the Logan plot applied to ROI time-activity curves were used as a reference for comparison of DVR estimates. RESULTS Results from the theoretic analysis were confirmed by human studies. ROI estimates from the RE plot and the bcSUVR were nearly identical to those from the Logan plot with ROI time-activity curves. In contrast, ROI estimates from DVR images in frontal, temporal, parietal, and cingulate regions and the striatum were underestimated by the Logan plot (controls, 4%-12%; MCI, 9%-16%) and overestimated by the SUVR (controls, 8%-16%; MCI, 16%-24%). This bias was higher in the MCI group than in controls (P < 0.01) but was not present when data were analyzed using either the RE plot or the bcSUVR. CONCLUSION The RE plot improves pixelwise quantification of (11)C-PiB dynamic PET, compared with the conventional Logan plot. The bcSUVR results in lower bias and higher consistency of DVR estimates than of SUVR. The RE plot and the bcSUVR are practical quantitative approaches that improve the analysis of (11)C-PiB studies.
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Affiliation(s)
- Yun Zhou
- Russell H. Morgan Department of Radiology and Radiological Science, School of Medicine, Johns Hopkins University, Baltimore, MD 21287-0807, USA.
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Constantinescu CC, Coleman RA, Pan ML, Mukherjee J. Striatal and extrastriatal microPET imaging of D2/D3 dopamine receptors in rat brain with [¹⁸F]fallypride and [¹⁸F]desmethoxyfallypride. Synapse 2011; 65:778-87. [PMID: 21218455 DOI: 10.1002/syn.20904] [Citation(s) in RCA: 30] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2010] [Accepted: 12/23/2010] [Indexed: 11/07/2022]
Abstract
In this study, we compared two different D(2/3) receptor ligands, [¹⁸F]fallypride and [¹⁸F]desmethoxyfallypride ([¹⁸F]DMFP) with respect to the duration of the scan, visualization of extrastriatal receptors, and binding potentials (BP(ND) ) in the rat brain. In addition, we studied the feasibility of using these tracers following a period of awake tracer uptake, during which the animal may perform a behavioral task. Male Sprague-Dawley rats were imaged with [¹⁸F]fallypride and with [¹⁸F]DMFP in four different studies using microPET. All scans were performed under isoflurane anesthesia. The first (test) and second (retest) study were 150-min baseline scans. No retest scans were performed with [¹⁸F]DMFP. A third study was a 60-min awake uptake of radiotracer followed by a 90-min scan. A fourth study was a 150-min competition scan with haloperidol (0.2 mg/kg) administered via tail vein at 90-min post-[¹⁸F]fallypride injection and 60-min post-[¹⁸F]DMFP. For the test-retest studies, BP(ND) was measured using both Logan noninvasive (LNI) method and the interval ratios (ITR) method. Cerebellum was used as a reference region. For the third study, the binding was measured only with the ITR method, and the results were compared to the baseline results. Studies showed that the average transient equilibrium time in the dorsal striatum (DSTR) was at 90 min for [¹⁸F]fallypride and 30 min for [¹⁸F]DMFP. The average BP(ND) for [¹⁸F]fallypride was 14.4 in DSTR, 6.8 in ventral striatum (VSTR), 1.3 in substantia nigra/ventral tegmental area (SN/VTA), 1.4 in colliculi (COL), and 1.5 in central gray area. In the case of [¹⁸F]DMFP, the average BP(ND) values were 2.2 in DSTR, 2.7 in VSTR, and 0.8 in SN/VTA. The haloperidol blockade showed detectable decrease in binding of both tracers in striatal regions with a faster displacement of [¹⁸F]DMFP. No significant changes in BP(ND) of [¹⁸F]fallypride due to the initial awake state of the animal were found, whereas BP(ND) of [¹⁸F]DMFP was significantly higher in the awake state compared to baseline. We were able to demonstrate that dynamic PET using MicroPET Inveon allows quantification of both striatal and extrastriatal [¹⁸F]fallypride binding in rats in vivo. Quantification of the striatal regions could be achieved with [¹⁸F]DMFP.
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Affiliation(s)
- Cristian C Constantinescu
- Preclinical Imaging, Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, California 92697, USA.
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Differences in the dynamics of serotonin reuptake transporter occupancy may explain superior clinical efficacy of escitalopram versus citalopram. Int Clin Psychopharmacol 2009; 24:119-25. [PMID: 19367152 DOI: 10.1097/yic.0b013e32832a8ec8] [Citation(s) in RCA: 47] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
Escitalopram the S-enantiomer of the racemate citalopram, is clinically more effective than citalopram in the treatment of major depressive disorder. However, the precise mechanism by which escitalopram achieves superiority over citalopram is yet to be determined. It has been hypothesized that the therapeutically inactive R-enantiomer competes with the serotonin-enhancing S-enantiomer at a low-affinity allosteric site on serotonin reuptake transporters (SERTs), and reduces the effectiveness of the S-enantiomer at the primary, high-affinity serotonin-binding site. This study summarizes the results of two recent single-photon emission computerized tomography studies measuring SERT occupancy in citalopram-treated and escitalopram-treated healthy volunteers, after a single dose and multiple doses (i.e. under steady-state conditions). The single-dose study showed no attenuating effect of R-citalopram. After multiple dosing, however, SERT occupancy was significantly reduced in the presence of R-citalopram. Under steady-state conditions, R-enantiomer concentrations were greater than for the S-enantiomer because of slower clearance of R-citalopram. A pooled analysis suggests that build-up of the R-enantiomer after repeated citalopram dosing may lead to increased inhibition of S-enantiomer occupancy of SERT. This review adds to the growing body of evidence regarding differences in the dynamics of SERT occupancy, that is, molecular mechanisms underlying the often-observed superior clinical efficacy of escitalopram compared with citalopram in major depressive disorder.
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