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Hu J, Li Y, Dong C, Wei H, Liao K, Wei J, Zhao C, Chaudhary A, Chen J, Xu H, Zhong K, Liang SH, Wang L, Ye W. Discovery and evaluation of a novel 18F-labeled vasopressin 1a receptor PET ligand with peripheral binding specificity. Acta Pharm Sin B 2024; 14:4014-4027. [PMID: 39309503 PMCID: PMC11413668 DOI: 10.1016/j.apsb.2024.05.033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2024] [Revised: 05/06/2024] [Accepted: 05/13/2024] [Indexed: 09/25/2024] Open
Abstract
The arginine-vasopressin (AVP) hormone plays a pivotal role in regulating various physiological processes, such as hormone secretion, cardiovascular modulation, and social behavior. Recent studies have highlighted the V1a receptor as a promising therapeutic target. In-depth insights into V1a receptor-related pathologies, attained through in vivo imaging and quantification in both peripheral organs and the central nervous system (CNS), could significantly advance the development of effective V1a inhibitors. To address this need, we develop a novel V1a-targeted positron emission tomography (PET) ligand, [18F]V1A-2303 ([18F]8), which demonstrates favorable in vitro binding affinity and selectivity for the V1a receptor. Specific tracer binding in peripheral tissues was also confirmed through rigorous cell uptake studies, autoradiography, biodistribution assessments. Furthermore, [18F]8 was employed in PET imaging and arterial blood sampling studies in healthy rhesus monkeys to assess its brain permeability and specificity, whole-body distribution, and kinetic properties. Our research indicated [18F]8 as a valuable tool for noninvasively studying V1a receptors in peripheral organs, and as a foundational element for the development of next-generation, brain-penetrant ligands specifically designed for the CNS.
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Affiliation(s)
- Junqi Hu
- Center of Cyclotron and PET Radiopharmaceuticals, Department of Nuclear Medicine & Key Laboratory of Basic and Translational Research on Radiopharmaceuticals, the First Affiliated Hospital of Jinan University, Guangzhou 510630, China
| | - Yinlong Li
- Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA 30322, USA
| | - Chenchen Dong
- Center of Cyclotron and PET Radiopharmaceuticals, Department of Nuclear Medicine & Key Laboratory of Basic and Translational Research on Radiopharmaceuticals, the First Affiliated Hospital of Jinan University, Guangzhou 510630, China
| | - Huiyi Wei
- Center of Cyclotron and PET Radiopharmaceuticals, Department of Nuclear Medicine & Key Laboratory of Basic and Translational Research on Radiopharmaceuticals, the First Affiliated Hospital of Jinan University, Guangzhou 510630, China
| | - Kai Liao
- Center of Cyclotron and PET Radiopharmaceuticals, Department of Nuclear Medicine & Key Laboratory of Basic and Translational Research on Radiopharmaceuticals, the First Affiliated Hospital of Jinan University, Guangzhou 510630, China
| | - Junjie Wei
- Center of Cyclotron and PET Radiopharmaceuticals, Department of Nuclear Medicine & Key Laboratory of Basic and Translational Research on Radiopharmaceuticals, the First Affiliated Hospital of Jinan University, Guangzhou 510630, China
| | - Chunyu Zhao
- Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA 30322, USA
| | - Ahmad Chaudhary
- Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA 30322, USA
| | - Jiahui Chen
- Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA 30322, USA
| | - Hao Xu
- Center of Cyclotron and PET Radiopharmaceuticals, Department of Nuclear Medicine & Key Laboratory of Basic and Translational Research on Radiopharmaceuticals, the First Affiliated Hospital of Jinan University, Guangzhou 510630, China
| | - Ke Zhong
- Department of Pharmacy, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou 510120, China
| | - Steven H. Liang
- Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA 30322, USA
| | - Lu Wang
- Center of Cyclotron and PET Radiopharmaceuticals, Department of Nuclear Medicine & Key Laboratory of Basic and Translational Research on Radiopharmaceuticals, the First Affiliated Hospital of Jinan University, Guangzhou 510630, China
| | - Weijian Ye
- Center of Cyclotron and PET Radiopharmaceuticals, Department of Nuclear Medicine & Key Laboratory of Basic and Translational Research on Radiopharmaceuticals, the First Affiliated Hospital of Jinan University, Guangzhou 510630, China
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2
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Kim GH, Kim BR, Yoon HJ, Jeong JH. Elevated cerebral blood flow proxy with increased beta-amyloid burden in Alzheimer's disease preclinical phase evaluated by dual-phase 18F-florbetaben positron emission tomography. Sci Rep 2024; 14:18480. [PMID: 39122860 PMCID: PMC11315901 DOI: 10.1038/s41598-024-68916-4] [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: 03/11/2024] [Accepted: 07/30/2024] [Indexed: 08/12/2024] Open
Abstract
This study investigated the earliest change of cerebral blood flow (CBF) and its relationship with β-amyloid (Aβ) burden in preclinical Alzheimer's disease (AD) employing dual-phase 18F-florbetaben (FBB) PET. Seventy-one cognitively normal (NC) individuals were classified as Aβ negative (Aβ-NC) or positive (Aβ+NC) based on two different cutoff values: an SUVR of > 1.08 and a Centiloid scale of > 20. The PET scans were acquired in two phases: an early phase (0-10 min, eFBB) and a delayed phase (90-110 min, dFBB), which were averaged to generate single-frame images for each phase. Furthermore, an R1 parametric map was generated from the early phase data using a simplified reference tissue model. We conducted regional and voxel-based analyses to compare the eFBB, dFBB, and R1 images between the Aβ positive and negative groups. In addition, the correlations between the CBF proxy R1 and the dFBB SUVR were analyzed. The Aβ+NC group showed significantly higher dFBB SUVR in both the global cerebral cortex and target regions compared to the Aβ-NC group, while no significant differences were observed in eFBB SUVR between the two groups. Furthermore, the Aβ+NC group exhibited significantly higher R1 values, a proxy for cerebral perfusion, in both the global cerebral cortex and target regions compared to the Aβ-NC group. Significant positive correlations were observed between R1 and dFBB SUVR in both the global cerebral cortex and target regions, which remained significant after controlling for demographics and cognitive profiles, except for the medial temporal and occipital cortices. The findings reveal increased CBF in preclinical AD and a positive correlation between CBF and amyloid pathology. The positive correlation between R1 and amyloid burden may indicate a compensatory mechanism in the preclinical stage of Alzheimer's disease, but to elucidate this hypothesis, further longitudinal observational studies are necessary.
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Affiliation(s)
- Geon Ha Kim
- Department of Neurology, Ewha Womans University College of Medicine, Seoul, Republic of Korea
| | - Bori R Kim
- Department of Neurology, Ewha Womans University College of Medicine, Seoul, Republic of Korea
- Ewha Medical Research Institute, Ewha Womans University, Seoul, Republic of Korea
| | - Hai-Jeon Yoon
- Department of Nuclear Medicine, Ewha Womans University, College of Medicine, Seoul, Republic of Korea.
| | - Jee Hyang Jeong
- Department of Neurology, Ewha Womans University College of Medicine, Seoul, Republic of Korea.
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3
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Huang J, Wang J, Cui B, Yang H, Tian D, Ma J, Duan W, Chen Z, Lu J. The pons as an optimal background reference region for spinal 18F-FET PET/MRI evaluation. EJNMMI Res 2024; 14:69. [PMID: 39060564 PMCID: PMC11282009 DOI: 10.1186/s13550-024-01130-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2024] [Accepted: 07/12/2024] [Indexed: 07/28/2024] Open
Abstract
BACKGROUND This study aims to evaluate the effect of various background reference regions on spinal 18F-FET PET imaging, with a focus on distinguishing between spinal tumors and myelitis. To enhance diagnostic accuracy, we investigated the pons and several other spinal cord area as potential references, given the challenges in interpreting spinal PET results. RESULTS A retrospective analysis was conducted on 30 patients, 15 with cervical myelitis and 15 with cervical tumors, who underwent O-(2-[18F]-fluoroethyl)-L-tyrosine (FET) PET/MR imaging. The stability of uptake across four regions, including the pons, C2, C2-C7, and T1-T3, was compared. The standardized uptake value ratio (SUVR) was then evaluated using various background regions, and their effectiveness in differentiating between spinal tumors and myelitis was compared. Additionally, we correlated the SUVR values derived from these regions with the Ki-67 proliferation index in tumor patients. The study found no significant difference in SUVmax (U = 110, p = 0.93) and SUVmean (U = 89, p = 0.35) values at lesion sites between myelitis and tumor patients. The pons had the highest average uptake (p < 0.001) compared to the other three regions. However, its coefficient of variation (CV) was significantly lower than that of the C2-C7 (p < 0.0001) and T1-T3 segments (p < 0.05). The SUVRmax values, calculated using the regions of pons, C2-C7 and T1-T3, were found to significantly differentiate between tumors and myelitis (p < 0.05). However, only the pons-based SUVRmean was able to significantly distinguish between the two groups (p < 0.05). Additionally, the pons-based SUVRmax (r = 0.63, p = 0.013) and SUVRmean (r = 0.67, p = 0.007) demonstrated a significant positive correlation with the Ki-67 index. CONCLUSIONS This study suggests that the pons may be considered a suitable reference region for spinal 18F-FET PET imaging, which can improve the differentiation between spinal tumors and myelitis. The significant correlation between pons-based SUVR values and the Ki-67 index further highlights the potential of this approach in assessing tumor cell proliferation.
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Affiliation(s)
- Jing Huang
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, 45 Changchun Street, Xicheng District, Beijing, China
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Capital Medical University, Beijing, China
| | - Jiyuan Wang
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, 45 Changchun Street, Xicheng District, Beijing, China
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Capital Medical University, Beijing, China
| | - Bixiao Cui
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, 45 Changchun Street, Xicheng District, Beijing, China
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Capital Medical University, Beijing, China
| | - Hongwei Yang
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, 45 Changchun Street, Xicheng District, Beijing, China
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Capital Medical University, Beijing, China
| | - Defeng Tian
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, 45 Changchun Street, Xicheng District, Beijing, China
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Capital Medical University, Beijing, China
| | - Jie Ma
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, 45 Changchun Street, Xicheng District, Beijing, China
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Capital Medical University, Beijing, China
| | - Wanru Duan
- Department of Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Zan Chen
- Department of Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Jie Lu
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, 45 Changchun Street, Xicheng District, Beijing, China.
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Capital Medical University, Beijing, China.
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Fang J, Zeng F, Liu H. Signal separation of simultaneous dual-tracer PET imaging based on global spatial information and channel attention. EJNMMI Phys 2024; 11:47. [PMID: 38809438 PMCID: PMC11136940 DOI: 10.1186/s40658-024-00649-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2023] [Accepted: 05/15/2024] [Indexed: 05/30/2024] Open
Abstract
BACKGROUND Simultaneous dual-tracer positron emission tomography (PET) imaging efficiently provides more complete information for disease diagnosis. The signal separation has long been a challenge of dual-tracer PET imaging. To predict the single-tracer images, we proposed a separation network based on global spatial information and channel attention, and connected it to FBP-Net to form the FBPnet-Sep model. RESULTS Experiments using simulated dynamic PET data were conducted to: (1) compare the proposed FBPnet-Sep model to Sep-FBPnet model and currently existing Multi-task CNN, (2) verify the effectiveness of modules incorporated in FBPnet-Sep model, (3) investigate the generalization of FBPnet-Sep model to low-dose data, and (4) investigate the application of FBPnet-Sep model to multiple tracer combinations with decay corrections. Compared to the Sep-FBPnet model and Multi-task CNN, the FBPnet-Sep model reconstructed single-tracer images with higher structural similarity, peak signal-to-noise ratio and lower mean squared error, and reconstructed time-activity curves with lower bias and variation in most regions. Excluding the Inception or channel attention module resulted in degraded image qualities. The FBPnet-Sep model showed acceptable performance when applied to low-dose data. Additionally, it could deal with multiple tracer combinations. The qualities of predicted images, as well as the accuracy of derived time-activity curves and macro-parameters were slightly improved by incorporating a decay correction module. CONCLUSIONS The proposed FBPnet-Sep model was considered a potential method for the reconstruction and signal separation of simultaneous dual-tracer PET imaging.
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Affiliation(s)
- Jingwan Fang
- State Key Laboratory of Modern Optical Instrumentation, College of Optical Science and Engineering, Zhejiang University, Hangzhou, China
| | - Fuzhen Zeng
- State Key Laboratory of Modern Optical Instrumentation, College of Optical Science and Engineering, Zhejiang University, Hangzhou, China
| | - Huafeng Liu
- State Key Laboratory of Modern Optical Instrumentation, College of Optical Science and Engineering, Zhejiang University, Hangzhou, China.
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Wang H, Li B, Wang Z, Chen X, You Z, Ng YL, Ge Q, Yuan J, Zhou Y, Zhao J. Kinetic analysis of cardiac dynamic 18F-Florbetapir PET in healthy volunteers and amyloidosis patients: A pilot study. Heliyon 2024; 10:e26021. [PMID: 38375312 PMCID: PMC10875429 DOI: 10.1016/j.heliyon.2024.e26021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2023] [Revised: 02/01/2024] [Accepted: 02/06/2024] [Indexed: 02/21/2024] Open
Abstract
Objectives This study aimed to explore the potential of full dynamic PET kinetic analysis in assessing amyloid binding and perfusion in the cardiac region using 18F-Florbetapir PET, establishing a quantitative approach in the clinical assessment of cardiac amyloidosis disease. Materials & methods The distribution volume ratios (DVRs) and the relative transport rate constant (R1), were estimated by a pseudo-simplified reference tissue model (pSRTM2) and pseudo-Logan plot (pLogan plot) with kidney reference for the region of interest-based and voxel-wise-based analyses. The parametric images generated using the pSRTM2 and linear regression with spatially constrained (LRSC) algorithm were then evaluated. Semi-quantitative analyses include standardized uptake value ratios at the early phase (SUVREP, 0.5-5 min) and late phase (SUVRLP, 50-60 min) were also calculated. Results Ten participants [7 healthy controls (HC) and 3 cardiac amyloidosis (CA) subjects] underwent a 60-min dynamic 18F-Florbetapir PET scan. The DVRs estimated from pSRTM2 and Logan plot were significantly increased (HC vs CA; DVRpSRTM2: 0.95 ± 0.11 vs 2.77 ± 0.42, t'(2.13) = 7.39, P = 0.015; DVRLogan: 0.80 ± 0.12 vs 2.90 ± 0.55, t'(2.08) = 6.56, P = 0.020), and R1 were remarkably decreased in CA groups, as compared to HCs (HC vs CA; 1.08 ± 0.37 vs 0.56 ± 0.10, t'(7.63) = 3.38, P = 0.010). The SUVREP and SUVRLP were highly correlated to R1 (r = 0.97, P < 0.001) and DVR(r = 0.99, P < 0.001), respectively. The DVRs in the total myocardium region increased slightly as the size of FWHM increased and became stable at a Gaussian filter ≥6 mm. The secular equilibrium of SUVR was reached at around 50-min p.i. time. Conclusion The DVR and R1 estimated from cardiac dynamic 18F-Florbetapir PET using pSRTM with kidney pseudo-reference tissue are suggested to quantify cardiac amyloid deposition and relative perfusion, respectively, in amyloidosis patients and healthy controls. We recommend a dual-phase scan: 0.5-5 min and 50-60 min p.i. as the appropriate time window for clinically assessing cardiac amyloidosis and perfusion measurements using 18F-Florbetapir PET.
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Affiliation(s)
- Haiyan Wang
- Department of Nuclear Medicine, Shanghai East Hospital, School of Medicine, Tongji University, No. 150, Jimo Road, Shanghai, 200120, China
| | - Bolun Li
- Central Research Institute, United Imaging Healthcare Group Co., Ltd, Shanghai, 201807, China
| | - Zhe Wang
- Central Research Institute, United Imaging Healthcare Group Co., Ltd, Shanghai, 201807, China
| | - Xing Chen
- Department of Nuclear Medicine, Shanghai East Hospital, School of Medicine, Tongji University, No. 150, Jimo Road, Shanghai, 200120, China
| | - Zhiwen You
- Department of Nuclear Medicine, Shanghai East Hospital, School of Medicine, Tongji University, No. 150, Jimo Road, Shanghai, 200120, China
| | - Yee Ling Ng
- Central Research Institute, United Imaging Healthcare Group Co., Ltd, Shanghai, 201807, China
| | - Qi Ge
- Central Research Institute, United Imaging Healthcare Group Co., Ltd, Shanghai, 201807, China
| | - Jianmin Yuan
- Central Research Institute, United Imaging Healthcare Group Co., Ltd, Shanghai, 201807, China
| | - Yun Zhou
- Central Research Institute, United Imaging Healthcare Group Co., Ltd, Shanghai, 201807, China
| | - Jun Zhao
- Department of Nuclear Medicine, Shanghai East Hospital, School of Medicine, Tongji University, No. 150, Jimo Road, Shanghai, 200120, China
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6
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Yang Z, Kinney JW, Cordes D. Uptake of 18F-AV45 in the Putamen Provides Additional Insights into Alzheimer's Disease beyond the Cortex. Biomolecules 2024; 14:157. [PMID: 38397394 PMCID: PMC10886857 DOI: 10.3390/biom14020157] [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: 11/14/2023] [Revised: 01/09/2024] [Accepted: 01/17/2024] [Indexed: 02/25/2024] Open
Abstract
Cortical uptake in brain amyloid positron emission tomography (PET) is increasingly used for the biological diagnosis of Alzheimer's disease (AD); however, the clinical and biological relevance of the striatum beyond the cortex in amyloid PET scans remains unclear. A total of 513 amyloid-positive participants having 18F-AV45 amyloid PET scans available were included in the analysis. The associations between cognitive scores and striatal uptake were analyzed. The participants were categorized into three groups based on the residual from the linear fitting between 18F-AV45 uptake in the putamen and the cortex in the order of HighP > MidP > LowP group. We then examined the differences between these three groups in terms of clinical diagnosis, APOE genotype, CSF phosphorylated tau (ptau) concentration, hippocampal volume, entorhinal thickness, and cognitive decline rate to evaluate the additional insights provided by the putamen beyond the cortex. The 18F-AV45 uptake in the putamen was more strongly associated with ADAS-cog13 and MoCA scores (p < 0.001) compared to the uptake in the caudate nucleus. Despite comparable cortical uptakes, the HighP group had a two-fold higher risk of being ε4-homozygous or diagnosed with AD dementia compared to the LowP group. These three groups had significantly different CSF ptau concentration, hippocampal volume, entorhinal thickness, and cognitive decline rate. These findings suggest that the assessment of 18F-AV45 uptake in the putamen is of unique value for evaluating disease severity and predicting disease progression.
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Affiliation(s)
- Zhengshi Yang
- Cleveland Clinic Lou Ruvo Center for Brain Health, Las Vegas, NV 89106, USA;
- Department of Brain Health, University of Nevada Las Vegas (UNLV), Las Vegas, NV 89154, USA;
| | - Jefferson W. Kinney
- Department of Brain Health, University of Nevada Las Vegas (UNLV), Las Vegas, NV 89154, USA;
- Chambers-Grundy Center for Transformative Neuroscience, Pam Quirk Brain Health and Biomarker Laboratory, Department of Brain Health, School of Integrated Health Sciences, University of Nevada Las Vegas (UNLV), Las Vegas, NV 89154, USA
| | - Dietmar Cordes
- Cleveland Clinic Lou Ruvo Center for Brain Health, Las Vegas, NV 89106, USA;
- Department of Brain Health, University of Nevada Las Vegas (UNLV), Las Vegas, NV 89154, USA;
- Department of Psychology and Neuroscience, University of Colorado, Boulder, CO 80309, USA
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7
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Ottoy J, Ozzoude M, Zukotynski K, Kang MS, Adamo S, Scott C, Ramirez J, Swardfager W, Lam B, Bhan A, Mojiri P, Kiss A, Strother S, Bocti C, Borrie M, Chertkow H, Frayne R, Hsiung R, Laforce RJ, Noseworthy MD, Prato FS, Sahlas DJ, Smith EE, Kuo PH, Chad JA, Pasternak O, Sossi V, Thiel A, Soucy JP, Tardif JC, Black SE, Goubran M. Amyloid-PET of the white matter: Relationship to free water, fiber integrity, and cognition in patients with dementia and small vessel disease. J Cereb Blood Flow Metab 2023; 43:921-936. [PMID: 36695071 DOI: 10.1177/0271678x231152001] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Abstract
White matter (WM) injury is frequently observed along with dementia. Positron emission tomography with amyloid-ligands (Aβ-PET) recently gained interest for detecting WM injury. Yet, little is understood about the origin of the altered Aβ-PET signal in WM regions. Here, we investigated the relative contributions of diffusion MRI-based microstructural alterations, including free water and tissue-specific properties, to Aβ-PET in WM and to cognition. We included a unique cohort of 115 participants covering the spectrum of low-to-severe white matter hyperintensity (WMH) burden and cognitively normal to dementia. We applied a bi-tensor diffusion-MRI model that differentiates between (i) the extracellular WM compartment (represented via free water), and (ii) the fiber-specific compartment (via free water-adjusted fractional anisotropy [FA]). We observed that, in regions of WMH, a decrease in Aβ-PET related most closely to higher free water and higher WMH volume. In contrast, in normal-appearing WM, an increase in Aβ-PET related more closely to higher cortical Aβ (together with lower free water-adjusted FA). In relation to cognitive impairment, we observed a closer relationship with higher free water than with either free water-adjusted FA or WM PET. Our findings support free water and Aβ-PET as markers of WM abnormalities in patients with mixed dementia, and contribute to a better understanding of processes giving rise to the WM PET signal.
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Affiliation(s)
- Julie Ottoy
- LC Campbell Cognitive Neurology Unit, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
| | - Miracle Ozzoude
- LC Campbell Cognitive Neurology Unit, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
| | - Katherine Zukotynski
- LC Campbell Cognitive Neurology Unit, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada.,Departments of Medicine and Radiology, McMaster University, Hamilton, ON, Canada.,Department of Medical Imaging, Schulich School of Medicine & Dentistry, Western University, London, ON, Canada.,Department of Radiology, University of British Columbia, Vancouver, BC, Canada
| | - Min Su Kang
- LC Campbell Cognitive Neurology Unit, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada.,Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - Sabrina Adamo
- LC Campbell Cognitive Neurology Unit, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
| | - Christopher Scott
- LC Campbell Cognitive Neurology Unit, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
| | - Joel Ramirez
- LC Campbell Cognitive Neurology Unit, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
| | - Walter Swardfager
- Department of Pharmacology & Toxicology, University of Toronto, Toronto, ON, Canada
| | - Benjamin Lam
- Department of Medicine (Division of Neurology), Dr. Sandra Black Centre for Brain Resilience and Recovery, Hurvitz Brain Sciences Research Program, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada
| | - Aparna Bhan
- LC Campbell Cognitive Neurology Unit, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
| | - Parisa Mojiri
- LC Campbell Cognitive Neurology Unit, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
| | - Alex Kiss
- Department of Research Design and Biostatistics, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
| | - Stephen Strother
- Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada.,The Rotman Research Institute Baycrest, University of Toronto, Toronto, ON, Canada
| | - Christian Bocti
- Service de Neurologie, Département de Medicine, Université de Sherbrooke, Sherbrooke, QC, Canada
| | - Michael Borrie
- Lawson Health Research Institute, Western University, London, ON, Canada
| | - Howard Chertkow
- Jewish General Hospital and Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
| | - Richard Frayne
- Departments of Radiology and Clinical Neuroscience, Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
| | - Robin Hsiung
- Physics and Astronomy Department and DM Center for Brain Health, University of British Columbia, Vancouver, BC, Canada
| | - Robert Jr Laforce
- Clinique Interdisciplinaire de Mémoire, Département des Sciences Neurologiques, Université Laval, Québec, QC, Canada
| | - Michael D Noseworthy
- Departments of Medicine and Radiology, McMaster University, Hamilton, ON, Canada.,Department of Electrical and Computer Engineering, McMaster University, Hamilton, ON, Canada
| | - Frank S Prato
- Lawson Health Research Institute, Western University, London, ON, Canada
| | | | - Eric E Smith
- Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
| | - Phillip H Kuo
- Department of Medical Imaging, Medicine, and Biomedical Engineering, University of Arizona, Tucson, AZ, USA
| | - Jordan A Chad
- Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada.,The Rotman Research Institute Baycrest, University of Toronto, Toronto, ON, Canada
| | - Ofer Pasternak
- Departments of Psychiatry and Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, USA
| | - Vesna Sossi
- Physics and Astronomy Department and DM Center for Brain Health, University of British Columbia, Vancouver, BC, Canada
| | - Alexander Thiel
- Jewish General Hospital and Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
| | - Jean-Paul Soucy
- Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | | | - Sandra E Black
- LC Campbell Cognitive Neurology Unit, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada.,Department of Medicine (Division of Neurology), Dr. Sandra Black Centre for Brain Resilience and Recovery, Hurvitz Brain Sciences Research Program, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada
| | - Maged Goubran
- LC Campbell Cognitive Neurology Unit, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada.,Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada.,Physical Sciences Platform, Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
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8
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Kang K, Jeong SY, Park K, Hahm MH, Kim J, Lee H, Kim C, Yun E, Han J, Yoon U, Lee S. Distinct cerebral cortical perfusion patterns in idiopathic normal-pressure hydrocephalus. Hum Brain Mapp 2022; 44:269-279. [PMID: 36102811 PMCID: PMC9783416 DOI: 10.1002/hbm.25974] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2022] [Revised: 04/29/2022] [Accepted: 05/12/2022] [Indexed: 02/05/2023] Open
Abstract
The aims of the study are to evaluate idiopathic normal-pressure hydrocephalus (INPH)-related cerebral blood flow (CBF) abnormalities and to investigate their relation to cortical thickness in INPH patients. We investigated cortical CBF utilizing surface-based early-phase 18 F-florbetaben (E-FBB) PET analysis in two groups: INPH patients and healthy controls. All 39 INPH patients and 20 healthy controls were imaged with MRI, including three-dimensional volumetric images, for automated surface-based cortical thickness analysis across the entire brain. A subgroup with 37 participants (22 INPH patients and 15 healthy controls) that also underwent 18 F-fluorodeoxyglucose (FDG) PET imaging was further analyzed. Compared with age- and gender-matched healthy controls, INPH patients showed statistically significant hyperperfusion in the high convexity of the frontal and parietal cortical regions. Importantly, within the INPH group, increased perfusion correlated with cortical thickening in these regions. Additionally, significant hypoperfusion mainly in the ventrolateral frontal cortex, supramarginal gyrus, and temporal cortical regions was observed in the INPH group relative to the control group. However, this hypoperfusion was not associated with cortical thinning. A subgroup analysis of participants that also underwent FDG PET imaging showed that increased (or decreased) cerebral perfusion was associated with increased (or decreased) glucose metabolism in INPH. A distinctive regional relationship between cerebral cortical perfusion and cortical thickness was shown in INPH patients. Our findings suggest distinct pathophysiologic mechanisms of hyperperfusion and hypoperfusion in INPH patients.
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Affiliation(s)
- Kyunghun Kang
- Department of Neurology, School of MedicineKyungpook National UniversityDaeguSouth Korea
| | - Shin Young Jeong
- Department of Nuclear Medicine, School of MedicineKyungpook National UniversityDaeguSouth Korea
| | - Ki‐Su Park
- Department of Neurosurgery, School of MedicineKyungpook National UniversityDaeguSouth Korea
| | - Myong Hun Hahm
- Department of Radiology, School of MedicineKyungpook National UniversityDaeguSouth Korea
| | - Jaeil Kim
- School of Computer Science and EngineeringKyungpook National UniversityDaeguSouth Korea
| | - Ho‐Won Lee
- Department of Neurology, School of MedicineKyungpook National UniversityDaeguSouth Korea,Brain Science and Engineering InstituteKyungpook National UniversityDaeguSouth Korea
| | - Chi‐Hun Kim
- Department of NeurologyHallym University Sacred Heart HospitalAnyangSouth Korea
| | - Eunkyeong Yun
- Department of Biomedical EngineeringDaegu Catholic UniversityGyeongsan‐siSouth Korea
| | - Jaehwan Han
- Department of Biomedical EngineeringDaegu Catholic UniversityGyeongsan‐siSouth Korea
| | - Uicheul Yoon
- Department of Biomedical EngineeringDaegu Catholic UniversityGyeongsan‐siSouth Korea
| | - Sang‐Woo Lee
- Department of Nuclear Medicine, School of MedicineKyungpook National UniversityDaeguSouth Korea
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9
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Seixas AA, Rajabli F, Pericak-Vance MA, Jean-Louis G, Harms RL, Tarnanas I. Associations of digital neuro-signatures with molecular and neuroimaging measures of brain resilience: The altoida large cohort study. Front Psychiatry 2022; 13:899080. [PMID: 36061297 PMCID: PMC9435312 DOI: 10.3389/fpsyt.2022.899080] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/18/2022] [Accepted: 07/06/2022] [Indexed: 01/08/2023] Open
Abstract
Background Mixed results in the predictive ability of traditional biomarkers to determine cognitive functioning and changes in older adults have led to misdiagnosis and inappropriate treatment plans to address mild cognitive impairment and dementia among older adults. To address this critical gap, the primary goal of the current study is to investigate whether a digital neuro signature (DNS-br) biomarker predicted global cognitive functioning and change over time relative among cognitively impaired and cognitive healthy older adults. The secondary goal is to compare the effect size of the DNS-br biomarker on global cognitive functioning compared to traditional imaging and genomic biomarkers. The tertiary goal is to investigate which demographic and clinical factors predicted DNS-br in cognitively impaired and cognitively healthy older adults. Methods We conducted two experiments (Study A and Study B) to assess DNS for brain resilience (DNS-br) against the established FDG-PET brain imaging signature for brain resilience, based on a 10 min digital cognitive assessment tool. Study A was a semi-naturalistic observational study that included 29 participants, age 65+, with mild to moderate mild cognitive impairment and AD diagnosis. Study B was also a semi-naturalistic observational multicenter study which included 496 participants (213 mild cognitive impairment (MCI) and 283 cognitively healthy controls (HC), a total of 525 participants-cognitively healthy (n = 283) or diagnosed with MCI (n = 213) or AD (n = 29). Results DNS-br total score and majority of the 11 DNS-br neurocognitive subdomain scores were significantly associated with FDG-PET resilience signature, PIB ratio, cerebral gray matter and white matter volume after adjusting for multiple testing. DNS-br total score predicts cognitive impairment for the 80+ individuals in the Altoida large cohort study. We identified a significant interaction between the DNS-br total score and time, indicating that participants with higher DNS-br total score or FDG-PET in the resilience signature would show less cognitive decline over time. Conclusion Our findings highlight that a digital biomarker predicted cognitive functioning and change, which established biomarkers are unable to reliably do. Our findings also offer possible etiologies of MCI and AD, where education did not protect against cognitive decline.
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Affiliation(s)
- Azizi A. Seixas
- Department of Psychiatry and Behavioral Sciences, University of Miami Miller School of Medicine, Miami, FL, United States
| | - Farid Rajabli
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, United States
| | - Margaret A. Pericak-Vance
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, United States
| | - Girardin Jean-Louis
- Department of Psychiatry and Behavioral Sciences, University of Miami Miller School of Medicine, Miami, FL, United States
| | | | - Ioannis Tarnanas
- Altoida Inc., Washington, DC, United States
- Global Brain Health Institute, Trinity College Dublin, Dublin, Ireland
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10
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Heeman F, Hendriks J, Lopes Alves I, Tolboom N, van Berckel BNM, Yaqub M, Lammertsma AA. Test-Retest Variability of Relative Tracer Delivery Rate as Measured by [ 11C]PiB. Mol Imaging Biol 2021; 23:335-339. [PMID: 33884565 PMCID: PMC8099850 DOI: 10.1007/s11307-021-01606-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2020] [Revised: 02/23/2021] [Accepted: 04/06/2021] [Indexed: 11/30/2022]
Abstract
Purpose Moderate-to-high correlations have been reported between the [11C]PiB PET-derived relative tracer delivery rate R1 and relative CBF as measured using [15O]H2O PET, supporting its use as a proxy of relative CBF. As longitudinal PET studies become more common for measuring treatment efficacy or disease progression, it is important to know the intrinsic variability of R1. The purpose of the present study was to determine this through a retrospective data analysis. Procedures Test-retest data belonging to twelve participants, who underwent two 90 min [11C]PiB PET scans, were retrospectively included. The voxel-based implementation of the two-step simplified reference tissue model with cerebellar grey matter as reference tissue was used to compute R1 images. Next, test-retest variability was calculated, and test and retest R1 measures were compared using linear mixed effect models and a Bland-Altman analysis. Results Test-retest variability was low across regions (max. 5.8 %), and test and retest measures showed high, significant correlations (R2=0.92, slope=0.98) and a negligible bias (0.69±3.07 %). Conclusions In conclusion, the high precision of [11C]PiB R1 suggests suitable applicability for cross-sectional and longitudinal studies.
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Affiliation(s)
- Fiona Heeman
- Amsterdam UMC, Vrije Universiteit Amsterdam, Radiology and Nuclear Medicine, Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, The Netherlands.
| | - Janine Hendriks
- Amsterdam UMC, Vrije Universiteit Amsterdam, Radiology and Nuclear Medicine, Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, The Netherlands
| | - Isadora Lopes Alves
- Amsterdam UMC, Vrije Universiteit Amsterdam, Radiology and Nuclear Medicine, Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, The Netherlands
| | - Nelleke Tolboom
- Imaging Division, Department of Radiology, University Medical Center Utrecht, Utrecht, Netherlands
| | - Bart N M van Berckel
- Amsterdam UMC, Vrije Universiteit Amsterdam, Radiology and Nuclear Medicine, Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, The Netherlands
| | - Maqsood Yaqub
- Amsterdam UMC, Vrije Universiteit Amsterdam, Radiology and Nuclear Medicine, Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, The Netherlands
| | - Adriaan A Lammertsma
- Amsterdam UMC, Vrije Universiteit Amsterdam, Radiology and Nuclear Medicine, Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, The Netherlands
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11
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Schwarz CG. Uses of Human MR and PET Imaging in Research of Neurodegenerative Brain Diseases. Neurotherapeutics 2021; 18:661-672. [PMID: 33723751 PMCID: PMC8423895 DOI: 10.1007/s13311-021-01030-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/15/2021] [Indexed: 01/18/2023] Open
Abstract
In the past decades, many neuroimaging studies have aimed to improve the scientific understanding of human neurodegenerative diseases using MRI and PET. This article is designed to provide an overview of the major classes of brain imaging and how/why they are used in this line of research. It is intended as a primer for individuals who are relatively unfamiliar with the methods of neuroimaging research to gain a better understanding of the vocabulary and overall methodologies. It is not intended to describe or review any research findings for any disease or biology, but rather to broadly describe the imaging methodologies that are used in conducting this neurodegeneration research. We will also review challenges and strategies for analyzing neuroimaging data across multiple sites and studies, i.e., harmonization and standardization of imaging data for multi-site and meta-analyses.
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12
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Heeman F, Yaqub M, Hendriks J, Bader I, Barkhof F, Gispert JD, van Berckel BNM, Lopes Alves I, Lammertsma AA. Parametric imaging of dual-time window [ 18F]flutemetamol and [ 18F]florbetaben studies. Neuroimage 2021; 234:117953. [PMID: 33762215 DOI: 10.1016/j.neuroimage.2021.117953] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2020] [Revised: 01/12/2021] [Accepted: 03/05/2021] [Indexed: 11/15/2022] Open
Abstract
Optimal pharmacokinetic models for quantifying amyloid beta (Aβ) burden using both [18F]flutemetamol and [18F]florbetaben scans have previously been identified at a region of interest (ROI) level. The purpose of this study was to determine optimal quantitative methods for parametric analyses of [18F]flutemetamol and [18F]florbetaben scans. Forty-six participants were scanned on a PET/MR scanner using a dual-time window protocol and either [18F]flutemetamol (N=24) or [18F]florbetaben (N=22). The following parametric approaches were used to derive DVR estimates: reference Logan (RLogan), receptor parametric mapping (RPM), two-step simplified reference tissue model (SRTM2) and multilinear reference tissue models (MRTM0, MRTM1, MRTM2), all with cerebellar grey matter as reference tissue. In addition, a standardized uptake value ratio (SUVR) was calculated for the 90-110 min post injection interval. All parametric images were assessed visually. Regional outcome measures were compared with those from a validated ROI method, i.e. DVR derived using RLogan. Visually, RPM, and SRTM2 performed best across tracers and, in addition to SUVR, provided highest AUC values for differentiating between Aβ-positive vs Aβ-negative scans ([18F]flutemetamol: range AUC=0.96-0.97 [18F]florbetaben: range AUC=0.83-0.85). Outcome parameters of most methods were highly correlated with the reference method (R2≥0.87), while lowest correlation were observed for MRTM2 (R2=0.71-0.80). Furthermore, bias was low (≤5%) and independent of underlying amyloid burden for MRTM0 and MRTM1. The optimal parametric method differed per evaluated aspect; however, the best compromise across aspects was found for MRTM0 followed by SRTM2, for both tracers. SRTM2 is the preferred method for parametric imaging because, in addition to its good performance, it has the advantage of providing a measure of relative perfusion (R1), which is useful for measuring disease progression.
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Affiliation(s)
- Fiona Heeman
- Amsterdam UMC, Vrije Universiteit Amsterdam, Radiology and Nuclear Medicine, Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, the Netherlands.
| | - Maqsood Yaqub
- Amsterdam UMC, Vrije Universiteit Amsterdam, Radiology and Nuclear Medicine, Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, the Netherlands
| | - Janine Hendriks
- Amsterdam UMC, Vrije Universiteit Amsterdam, Radiology and Nuclear Medicine, Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, the Netherlands
| | - Ilona Bader
- Amsterdam UMC, Vrije Universiteit Amsterdam, Radiology and Nuclear Medicine, Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, the Netherlands
| | - Frederik Barkhof
- Amsterdam UMC, Vrije Universiteit Amsterdam, Radiology and Nuclear Medicine, Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, the Netherlands; UCL, Institutes of Neurology and Healthcare Engineering, London, United Kingdom
| | - Juan Domingo Gispert
- Barcelonaβeta Brain Research Centre, Pasqual Maragall Foundation, Barcelona, Spain; Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Madrid, Spain; Department of Experimental and Health Sciences, Universitat Pompeu Fabra, Barcelona, Spain; IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain
| | - Bart N M van Berckel
- Amsterdam UMC, Vrije Universiteit Amsterdam, Radiology and Nuclear Medicine, Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, the Netherlands
| | - Isadora Lopes Alves
- Amsterdam UMC, Vrije Universiteit Amsterdam, Radiology and Nuclear Medicine, Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, the Netherlands
| | - Adriaan A Lammertsma
- Amsterdam UMC, Vrije Universiteit Amsterdam, Radiology and Nuclear Medicine, Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, the Netherlands
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13
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Verfaillie SC, Golla SS, Timmers T, Tuncel H, van der Weijden CW, Schober P, Schuit RC, van der Flier WM, Windhorst AD, Lammertsma AA, van Berckel BN, Boellaard R. Repeatability of parametric methods for [ 18F]florbetapir imaging in Alzheimer's disease and healthy controls: A test-retest study. J Cereb Blood Flow Metab 2021; 41:569-578. [PMID: 32321347 PMCID: PMC7907981 DOI: 10.1177/0271678x20915403] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Abstract
Accumulation of amyloid beta (Aβ) is one of the pathological hallmarks of Alzheimer's disease (AD), which can be visualized using [18F]florbetapir positron emission tomography (PET). The aim of this study was to evaluate various parametric methods and to assess their test-retest (TRT) reliability. Two 90 min dynamic [18F]florbetapir PET scans, including arterial sampling, were acquired (n = 8 AD patient, n = 8 controls). The following parametric methods were used; (reference:cerebellum); Logan and spectral analysis (SA), receptor parametric mapping (RPM), simplified reference tissue model2 (SRTM2), reference Logan (rLogan) and standardized uptake value ratios (SUVr(50-70)). BPND+1, DVR, VT and SUVr were compared with corresponding estimates (VT or DVR) from the plasma input reversible two tissue compartmental (2T4k_VB) model with corresponding TRT values for 90-scan duration. RPM (r2 = 0.92; slope = 0.91), Logan (r2 = 0.95; slope = 0.84) and rLogan (r2 = 0.94; slope = 0.88), and SRTM2 (r2 = 0.91; slope = 0.83), SA (r2 = 0.91; slope = 0.88), SUVr (r2 = 0.84; slope = 1.16) correlated well with their 2T4k_VB counterparts. RPM (controls: 1%, AD: 3%), rLogan (controls: 1%, AD: 3%) and SUVr(50-70) (controls: 3%, AD: 8%) showed an excellent TRT reliability. In conclusion, most parametric methods showed excellent performance for [18F]florbetapir, but RPM and rLogan seem the methods of choice, combining the highest accuracy and best TRT reliability.
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Affiliation(s)
- Sander Cj Verfaillie
- Department of Radiology & Nuclear Medicine, Amsterdam University Medical center location VUmc, The Netherlands
| | - Sandeep Sv Golla
- Department of Radiology & Nuclear Medicine, Amsterdam University Medical center location VUmc, The Netherlands
| | - Tessa Timmers
- Department of Radiology & Nuclear Medicine, Amsterdam University Medical center location VUmc, The Netherlands.,Neurology & Alzheimer Center, Amsterdam Neuroscience, Amsterdam University Medical center location VUmc, The Netherlands
| | - Hayel Tuncel
- Department of Radiology & Nuclear Medicine, Amsterdam University Medical center location VUmc, The Netherlands
| | - Chris Wj van der Weijden
- Department of Nuclear Medicine & Molecular Imaging, University Medical Center Groningen, Groningen, The Netherlands
| | - Patrick Schober
- Department of Anaesthesiology, Amsterdam University Medical center location VUmc, Amsterdam, The Netherlands
| | - Robert C Schuit
- Department of Radiology & Nuclear Medicine, Amsterdam University Medical center location VUmc, The Netherlands
| | - Wiesje M van der Flier
- Neurology & Alzheimer Center, Amsterdam Neuroscience, Amsterdam University Medical center location VUmc, The Netherlands.,Epidemiology & Biostatistics, Amsterdam Neuroscience, Amsterdam University Medical center location VUmc, Amsterdam, The Netherlands
| | - Albert D Windhorst
- Department of Radiology & Nuclear Medicine, Amsterdam University Medical center location VUmc, The Netherlands
| | - Adriaan A Lammertsma
- Department of Radiology & Nuclear Medicine, Amsterdam University Medical center location VUmc, The Netherlands
| | - Bart Nm van Berckel
- Department of Radiology & Nuclear Medicine, Amsterdam University Medical center location VUmc, The Netherlands
| | - Ronald Boellaard
- Department of Radiology & Nuclear Medicine, Amsterdam University Medical center location VUmc, The Netherlands.,Department of Nuclear Medicine & Molecular Imaging, University Medical Center Groningen, Groningen, The Netherlands
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14
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Wang M, Yan Z, Zhang H, Lu J, Li L, Yu J, Wang J, Matsuda H, Zuo C, Jiang J. Parametric estimation of reference signal intensity in the quantification of amyloid-beta deposition: an 18F-AV-45 study. Quant Imaging Med Surg 2021; 11:249-263. [PMID: 33392026 PMCID: PMC7719939 DOI: 10.21037/qims-20-110] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2020] [Accepted: 09/07/2020] [Indexed: 12/23/2022]
Abstract
BACKGROUND Positron emission tomography (PET) with the radiotracer florbetapir (18F-AV-45) allows the pathophysiology of Alzheimer's disease (AD) to be tracked in vivo. The semi-quantification of amyloid-beta (Aβ) has been extensively evaluated with the standardized uptake value ratio (SUVR) but is susceptible to disturbance from the candidate reference region and the partial volume effect (PVE). In the present study, we applied the parametric estimation of reference signal intensity (PERSI) method to 18F-AV-45 PET images for intensity normalization. METHODS We enrolled 479 people with 18F-AV-45 images from the Alzheimer's Disease Neuroimaging Initiative database: 261 healthy controls (HCs), 102 patients with mild cognitive impairment (MCI), and 116 AD patients. We used white matter post-processed by PERSI (PERSI-WM) as the reference region and compared our proposed method with the traditional method for semi-quantification. SUVRs were calculated for eight regions of interest: the frontal lobe, the parietal lobe, the temporal lobe, the occipital lobe, the anterior cingulate cortex, the posterior cingulate cortex, the precuneus, and the global cortex. The SUVRs derived from PERSI-WM and other reference regions were evaluated by effect size and receiver-operator characteristic curve analyses. RESULTS The SUVRs derived from PERSI-WM showed significantly higher trace retention in the frontal, parietal, temporal, and occipital lobes, as well as in the anterior cingulate, posterior cingulate, precuneus, and global cortex in the AD Aβ-positive (+) group (mean: +43.3%±5.4%, P<0.01) and MCI Aβ+ group (mean: +29.6%±5.3%, P<0.01). For the global cortex, PERSI-WM had the greatest Cohen's d effect size compared with the HC Aβ-negative (-) group (AD Aβ+ and MCI Aβ+: 3.02, AD Aβ+: 3.56, MCI Aβ+: 2.34), and the highest area under the curve (AUC) between the HC Aβ- and AD Aβ+ groups (AUC: 0.983, 95% confidence interval: 0.978-0.998). CONCLUSIONS PERSI-WM could mitigate the influence of PVE and improve the semi-quantification of 18F-AV-45 images; therefore, it could be used for large-scale clinical application in the nuclear medicine domain.
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Affiliation(s)
- Min Wang
- Shanghai Institute for Advanced Communication and Data Science, School of Communication and Information Engineering, Shanghai University, Shanghai, China
- Institute of Biomedical Engineering, School of Communication and Information Engineering, Shanghai University, Shanghai, China
| | - Zhuangzhi Yan
- Institute of Biomedical Engineering, School of Communication and Information Engineering, Shanghai University, Shanghai, China
| | - Huiwei Zhang
- PET Center, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
| | - Jiaying Lu
- PET Center, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
| | - Ling Li
- PET Center, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
| | - Jintai Yu
- Department of Neurology and Institute of Neurology, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
| | - Jian Wang
- Department of Neurology and Institute of Neurology, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
| | - Hiroshi Matsuda
- Integrative Brain Imaging Center, National Center of Neurology and Psychiatry, Kodaira, Tokyo, Japan
| | - Chuantao Zuo
- PET Center, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
| | - Jiehui Jiang
- Shanghai Institute for Advanced Communication and Data Science, School of Communication and Information Engineering, Shanghai University, Shanghai, China
- Institute of Biomedical Engineering, School of Communication and Information Engineering, Shanghai University, Shanghai, China
| | - the Alzheimer’s Disease Neuroimaging Initiative
- Shanghai Institute for Advanced Communication and Data Science, School of Communication and Information Engineering, Shanghai University, Shanghai, China
- Institute of Biomedical Engineering, School of Communication and Information Engineering, Shanghai University, Shanghai, China
- PET Center, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
- Department of Neurology and Institute of Neurology, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
- Integrative Brain Imaging Center, National Center of Neurology and Psychiatry, Kodaira, Tokyo, Japan
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15
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Heeman F, Hendriks J, Lopes Alves I, Ossenkoppele R, Tolboom N, van Berckel BNM, Lammertsma AA, Yaqub M. [ 11C]PIB amyloid quantification: effect of reference region selection. EJNMMI Res 2020; 10:123. [PMID: 33074395 PMCID: PMC7572969 DOI: 10.1186/s13550-020-00714-1] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2020] [Accepted: 09/24/2020] [Indexed: 11/24/2022] Open
Abstract
Background The standard reference region (RR) for amyloid-beta (Aβ) PET studies is the cerebellar grey matter (GMCB), while alternative RRs have mostly been utilized without prior validation against the gold standard. This study compared five commonly used RRs to gold standard plasma input-based quantification using the GMCB. Methods Thirteen subjects from a test–retest (TRT) study and 30 from a longitudinal study were retrospectively included (total: 17 Alzheimer’s disease, 13 mild cognitive impairment, 13 controls). Dynamic [11C]PiB PET (90 min) and T1-weighted MR scans were co-registered and time–activity curves were extracted for cortical target regions and the following RRs: GMCB, whole cerebellum (WCB), white matter brainstem/pons (WMBS), whole brainstem (WBS) and eroded subcortical white matter (WMES). A two-tissue reversible plasma input model (2T4k_Vb) with GMCB as RR, reference Logan and the simplified reference tissue model were used to derive distribution volume ratios (DVRs), and standardized uptake value (SUV) ratios were calculated for 40–60 min and 60–90 min intervals. Parameter variability was evaluated using TRT scans, and correlations and agreements with the gold standard (DVR from 2T4k_Vb with GMCB RR) were also assessed. Next, longitudinal changes in SUVs (both intervals) were assessed for each RR. Finally, the ability to discriminate between visually Aβ positive and Aβ negative scans was assessed. Results All RRs yielded stable TRT performance (max 5.1% variability), with WCB consistently showing lower variability. All approaches were able to discriminate between Aβ positive and Aβ negative scans, with highest effect sizes obtained for GMCB (range − 0.9 to − 0.7), followed by WCB (range − 0.8 to − 0.6). Furthermore, all approaches provided good correlations with the gold standard (r ≥ 0.78), while the highest bias (as assessed by the regression slope) was observed using WMES (range slope 0.52–0.67), followed by WBS (range slope 0.58–0.92) and WMBS (range slope 0.62–0.91). Finally, RR SUVs were stable across a period of 2.6 years for all except WBS and WMBS RRs (60–90 min interval). Conclusions GMCB and WCB are considered the best RRs for quantifying amyloid burden using [11C]PiB PET.
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Affiliation(s)
- Fiona Heeman
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands.
| | - Janine Hendriks
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands
| | - Isadora Lopes Alves
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands
| | - Rik Ossenkoppele
- Neurology and Alzheimer Center, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan 1117, Amsterdam, The Netherlands.,Clinical Memory Research Unit, Lund University, Malmö, Sweden
| | - Nelleke Tolboom
- Imaging Division, Department of Radiology, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Bart N M van Berckel
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands
| | - Adriaan A Lammertsma
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands
| | - Maqsood Yaqub
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands
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16
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Jelistratova I, Teipel SJ, Grothe MJ. Longitudinal validity of PET-based staging of regional amyloid deposition. Hum Brain Mapp 2020; 41:4219-4231. [PMID: 32648624 PMCID: PMC7502828 DOI: 10.1002/hbm.25121] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2019] [Revised: 05/29/2020] [Accepted: 06/22/2020] [Indexed: 12/12/2022] Open
Abstract
Positron emission tomography (PET)-based staging of regional amyloid deposition has recently emerged as a promising tool for sensitive detection and stratification of pathology progression in Alzheimer's Disease (AD). Here we present an updated methodological framework for PET-based amyloid staging using region-specific amyloid-positivity thresholds and assess its longitudinal validity using serial PET acquisitions. We defined region-specific thresholds of amyloid-positivity based on Florbetapir-PET data of 13 young healthy individuals (age ≤ 45y), applied these thresholds to Florbetapir-PET data of 179 cognitively normal older individuals to estimate a regional amyloid staging model, and tested this model in a larger sample of patients with mild cognitive impairment (N = 403) and AD dementia (N = 85). 2-year follow-up Florbetapir-PET scans from a subset of this sample (N = 436) were used to assess the longitudinal validity of the cross-sectional model based on individual stage transitions and data-driven longitudinal trajectory modeling. Results show a remarkable congruence between cross-sectionally estimated and longitudinally modeled trajectories of amyloid accumulation, beginning in anterior temporal areas, followed by frontal and medial parietal areas, the remaining associative neocortex, and finally primary sensory-motor areas and subcortical regions. Over 98% of individual amyloid deposition profiles and longitudinal stage transitions adhered to this staging scheme of regional pathology progression, which was further supported by corresponding changes in cerebrospinal fluid biomarkers. In conclusion, we provide a methodological refinement and longitudinal validation of PET-based staging of regional amyloid accumulation, which may help improving early detection and in-vivo stratification of pathologic disease progression in AD.
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Affiliation(s)
| | - Stefan J. Teipel
- German Center for Neurodegenerative Diseases (DZNE)RostockGermany
- Department of Psychosomatic MedicineUniversity of RostockRostockGermany
| | - Michel J. Grothe
- German Center for Neurodegenerative Diseases (DZNE)RostockGermany
- Unidad de Trastornos del Movimiento, Servicio de Neurología y Neurofisiología Clínica, Instituto de Biomedicina de SevillaHospital Universitario Virgen del Rocío/CSIC/Universidad de SevillaSevilleSpain
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17
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Golla SS, Verfaillie SC, Boellaard R, Adriaanse SM, Zwan MD, Schuit RC, Timmers T, Groot C, Schober P, Scheltens P, van der Flier WM, Windhorst AD, van Berckel BN, Lammertsma AA. Quantification of [ 18F]florbetapir: A test-retest tracer kinetic modelling study. J Cereb Blood Flow Metab 2019; 39:2172-2180. [PMID: 29897009 PMCID: PMC6826855 DOI: 10.1177/0271678x18783628] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Accumulation of amyloid beta can be visualized using [18F]florbetapir positron emission tomography. The aim of this study was to identify the optimal model for quantifying [18F]florbetapir uptake and to assess test-retest reliability of corresponding outcome measures. Eight Alzheimer's disease patients (age: 67 ± 6 years, Mini-Mental State Examination (MMSE): 23 ± 3) and eight controls (age: 63 ± 4 years, MMSE: 30 ± 0) were included. Ninety-minute dynamic positron emission tomography scans, together with arterial blood sampling, were acquired immediately following a bolus injection of 294 ± 32 MBq [18F]florbetapir. Several plasma input models and the simplified reference tissue model (SRTM) were evaluated. The Akaike information criterion was used to identify the preferred kinetic model. Compared to controls, Alzheimer's disease patients had lower MMSE scores and evidence for cortical Aβ pathology. A reversible two-tissue compartment model with fitted blood volume fraction (2T4k_VB) was the preferred model for describing [18F]florbetapir kinetics. SRTM-derived non-displaceable binding potential (BPND) correlated well (r2 = 0.83, slope = 0.86) with plasma input-derived distribution volume ratio. Test-retest reliability for plasma input-derived distribution volume ratio, SRTM-derived BPND and SUVr(50-70) were r = 0.88, r = 0.91 and r = 0.86, respectively. In vivo kinetics of [18F]florbetapir could best be described by a reversible two-tissue compartmental model and [18F]florbetapir BPND can be reliably estimated using an SRTM.
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Affiliation(s)
- Sandeep Sv Golla
- Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, VU University Medical Center, Amsterdam, the Netherlands
| | - Sander Cj Verfaillie
- Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, VU University Medical Center, Amsterdam, the Netherlands.,Department of Neurology & Alzheimer Center, Amsterdam Neuroscience, VU University Medical Center, Amsterdam, the Netherlands
| | - Ronald Boellaard
- Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, VU University Medical Center, Amsterdam, the Netherlands.,Department of Nuclear Medicine & Molecular Imaging, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Sofie M Adriaanse
- Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, VU University Medical Center, Amsterdam, the Netherlands
| | - Marissa D Zwan
- Department of Neurology & Alzheimer Center, Amsterdam Neuroscience, VU University Medical Center, Amsterdam, the Netherlands
| | - Robert C Schuit
- Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, VU University Medical Center, Amsterdam, the Netherlands
| | - Tessa Timmers
- Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, VU University Medical Center, Amsterdam, the Netherlands.,Department of Neurology & Alzheimer Center, Amsterdam Neuroscience, VU University Medical Center, Amsterdam, the Netherlands
| | - Colin Groot
- Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, VU University Medical Center, Amsterdam, the Netherlands
| | - Patrick Schober
- Department of Anaesthesiology, Amsterdam Neuroscience, VU University Medical Center, Amsterdam, the Netherlands
| | - Philip Scheltens
- Department of Neurology & Alzheimer Center, Amsterdam Neuroscience, VU University Medical Center, Amsterdam, the Netherlands
| | - Wiesje M van der Flier
- Department of Neurology & Alzheimer Center, Amsterdam Neuroscience, VU University Medical Center, Amsterdam, the Netherlands.,Department of Epidemiology & Biostatistics, Amsterdam Neuroscience, VU University Medical Center, Amsterdam, the Netherlands
| | - Albert D Windhorst
- Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, VU University Medical Center, Amsterdam, the Netherlands
| | - Bart Nm van Berckel
- Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, VU University Medical Center, Amsterdam, the Netherlands
| | - Adriaan A Lammertsma
- Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, VU University Medical Center, Amsterdam, the Netherlands
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18
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Parker TD, Cash DM, Lane CAS, Lu K, Malone IB, Nicholas JM, James SN, Keshavan A, Murray-Smith H, Wong A, Buchanan SM, Keuss SE, Sudre CH, Modat M, Thomas DL, Crutch SJ, Richards M, Fox NC, Schott JM. Hippocampal subfield volumes and pre-clinical Alzheimer's disease in 408 cognitively normal adults born in 1946. PLoS One 2019; 14:e0224030. [PMID: 31622410 PMCID: PMC6797197 DOI: 10.1371/journal.pone.0224030] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2019] [Accepted: 10/03/2019] [Indexed: 12/17/2022] Open
Abstract
BACKGROUND The human hippocampus comprises a number of interconnected histologically and functionally distinct subfields, which may be differentially influenced by cerebral pathology. Automated techniques are now available that estimate hippocampal subfield volumes using in vivo structural MRI data. To date, research investigating the influence of cerebral β-amyloid deposition-one of the earliest hypothesised changes in the pathophysiological continuum of Alzheimer's disease-on hippocampal subfield volumes in cognitively normal older individuals, has been limited. METHODS Using cross-sectional data from 408 cognitively normal individuals born in mainland Britain (age range at time of assessment = 69.2-71.9 years) who underwent cognitive assessment, 18F-Florbetapir PET and structural MRI on the same 3 Tesla PET/MR unit (spatial resolution 1.1 x 1.1 x 1.1. mm), we investigated the influences of β-amyloid status, age at scan, and global white matter hyperintensity volume on: CA1, CA2/3, CA4, dentate gyrus, presubiculum and subiculum volumes, adjusting for sex and total intracranial volume. RESULTS Compared to β-amyloid negative participants (n = 334), β-amyloid positive participants (n = 74) had lower volume of the presubiculum (3.4% smaller, p = 0.012). Despite an age range at scanning of just 2.7 years, older age at time of scanning was associated with lower CA1 (p = 0.007), CA4 (p = 0.004), dentate gyrus (p = 0.002), and subiculum (p = 0.035) volumes. There was no evidence that white matter hyperintensity volume was associated with any subfield volumes. CONCLUSION These data provide evidence of differential associations in cognitively normal older adults between hippocampal subfield volumes and β-amyloid deposition and, increasing age at time of scan. The relatively selective effect of lower presubiculum volume in the β-amyloid positive group potentially suggest that the presubiculum may be an area of early and relatively specific volume loss in the pathophysiological continuum of Alzheimer's disease. Future work using higher resolution imaging will be key to exploring these findings further.
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Affiliation(s)
- Thomas D. Parker
- The Dementia Research Centre, Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - David M. Cash
- The Dementia Research Centre, Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Christopher A. S. Lane
- The Dementia Research Centre, Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Kirsty Lu
- The Dementia Research Centre, Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Ian B. Malone
- The Dementia Research Centre, Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Jennifer M. Nicholas
- The Dementia Research Centre, Queen Square Institute of Neurology, University College London, London, United Kingdom
- Department of Medical Statistics, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Sarah-Naomi James
- MRC Unit for Lifelong Health and Ageing at University College London, London, United Kingdom
| | - Ashvini Keshavan
- The Dementia Research Centre, Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Heidi Murray-Smith
- The Dementia Research Centre, Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Andrew Wong
- MRC Unit for Lifelong Health and Ageing at University College London, London, United Kingdom
| | - Sarah M. Buchanan
- The Dementia Research Centre, Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Sarah E. Keuss
- The Dementia Research Centre, Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Carole H. Sudre
- The Dementia Research Centre, Queen Square Institute of Neurology, University College London, London, United Kingdom
- School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
- Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom
| | - Marc Modat
- The Dementia Research Centre, Queen Square Institute of Neurology, University College London, London, United Kingdom
- School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom
- Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom
| | - David L. Thomas
- Leonard Wolfson Experimental Neurology Centre, Queen Square Institute of Neurology, University College London, London, United Kingdom
- Neuroradiological Academic Unit, Department of Brain Repair and Rehabilitation, Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Sebastian J. Crutch
- The Dementia Research Centre, Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Marcus Richards
- MRC Unit for Lifelong Health and Ageing at University College London, London, United Kingdom
| | - Nick C. Fox
- The Dementia Research Centre, Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Jonathan M. Schott
- The Dementia Research Centre, Queen Square Institute of Neurology, University College London, London, United Kingdom
- * E-mail:
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19
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Kameyama M, Ishibash K, Wagatsuma K, Toyohara J, Ishii K. A pitfall of white matter reference regions used in [18F] florbetapir PET: a consideration of kinetics. Ann Nucl Med 2019; 33:848-854. [DOI: 10.1007/s12149-019-01397-y] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2019] [Accepted: 08/17/2019] [Indexed: 12/16/2022]
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20
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18F-FDG PET, the early phases and the delivery rate of 18F-AV45 PET as proxies of cerebral blood flow in Alzheimer's disease: Validation against 15O-H 2O PET. Alzheimers Dement 2019; 15:1172-1182. [PMID: 31405824 DOI: 10.1016/j.jalz.2019.05.010] [Citation(s) in RCA: 32] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2019] [Revised: 04/27/2019] [Accepted: 05/21/2019] [Indexed: 11/22/2022]
Abstract
INTRODUCTION Dual-biomarker positron emission tomography (PET), providing complementary information on cerebral blood flow and amyloid-β deposition, is of clinical interest for Alzheimer's disease (AD). The purpose of this study was to validate the perfusion components of early-phase 18F-florbetapir (eAV45), the 18F-AV45 delivery rate (R1), and 18F-FDG against 15O-H2O PET and assess how they change with disease severity. METHODS This study included ten controls, 19 amnestic mild cognitive impairment, and 10 AD dementia subjects. Within-subject regional correlations between modalities, between-group regional and voxel-wise analyses of covariance per modality, and receiver operating characteristic analyses for discrimination between groups were performed. RESULTS FDG standardized uptake value ratio, eAV45 (0-2 min) standardized uptake value ratio, and AV45-R1 were significantly associated with H2O PET (regional Pearson r = 0.54-0.82, 0.70-0.94, and 0.65-0.92, respectively; P < .001). All modalities confirmed reduced cerebral blood flow in the posterior cingulate of patients with amnestic mild cognitive impairment and AD dementia, which was associated with lower cognition (r = 0.36-0.65, P < .025) and could discriminate between patient and control groups (area under the curve > 0.80). However, eAV45 was less sensitive to reflect the disease severity than AV45-R1 or FDG. DISCUSSION R1 is preferable over eAV45 for accurate representation of brain perfusion in dual-biomarker PET for AD.
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21
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Lane NE, Nyman JS, Uppuganti S, Chaudhari AJ, Aguirre JI, Shidara K, Liu XP, Yao W, Kimmel DB. Inhibition of vascular endothelial growth factor in young adult mice causes low bone blood flow and bone strength with no effect on bone mass in trabecular regions. Bone Rep 2019; 10:100210. [PMID: 31193542 PMCID: PMC6535464 DOI: 10.1016/j.bonr.2019.100210] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/18/2019] [Accepted: 05/03/2019] [Indexed: 12/15/2022] Open
Abstract
Objective To determine the effect of an antibody to vascular endothelial growth factor (VEGF) on bone blood flow, bone strength, and bone mass in the young adult mouse. Methods Ten-week-old male BALB/cJ mice were body weight-randomized into either a rodent anti-VEGF monoclonal antibody (anti-VEGF, B20-4.1.1; 5 mg/kg 2×/wk.; n = 12) group or a vehicle (VEH; n = 12) group. After 42 days, mice were evaluated for bone blood flow at the distal femur by 18F-NaF-PET/CT and then necropsied. Samples from trabecular and cortical bone regions were evaluated for bone strength by mechanical testing, bone mass by peripheral quantitative computed tomography (pQCT), and micoarchitecture (MicroCT). Hydration of the whole femur was studied by proton nuclear magnetic resonance relaxometry (1H NMR). Results Distal femur blood flow was 43% lower in anti-VEGF mice than in VEH mice (p = 0.009). Ultimate load in the lumbar vertebral body was 25% lower in anti-VEGF than in VEH mice (p = 0.013). Bone mineral density (BMD) in the trabecular region of the proximal humeral metaphysis by pQCT, and bone volume fraction and volumetric BMD by MicroCT were the same in the two groups. Volume fraction of bound water (BW) of the whole femur was 14% lower in anti-VEGF than in VEH mice (p = 0.003). Finally, BW, but not cortical tissue mineral density, helped section modulus explain the variance in the ultimate moment experienced by the femur in three-point bending. Conclusion Anti-VEGF caused low bone blood flow and bone strength in trabecular bone regions without influencing BMD and microarchitecture. Low bone strength was also associated with low bone hydration. These data suggest that bone blood flow is a novel bone property that affects bone quality. An antibody to vascular endothelial growth factor (anti-VEGF) caused low bone blood flow in a trabecular bone rich region. Anti-VEGF did not affect trabecular bone region and bone hydration of the whole femur were also low, trabecular bone mass was not affected by anti-VEGF. Bone blood flow may be a bone property that affects bone quality through bone hydration. Anti-VEGF caused low trabecular bone strength in the vertebral body and low bone hydration of the whole femur.
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Affiliation(s)
- N E Lane
- Center for Musculoskeletal Health, University of California at Davis Medical Center, Sacramento, CA 95817, USA
| | - J S Nyman
- Department of Orthopaedic Surgery and Rehabilitation, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - S Uppuganti
- Department of Orthopaedic Surgery and Rehabilitation, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - A J Chaudhari
- Center for Molecular and Genomic Imaging, Department of Radiology, University of California at Davis, Davis, CA 95616, USA
| | - J I Aguirre
- Department of Physiological Sciences, University of Florida, Gainesville, FL 32610, USA
| | - K Shidara
- Center for Musculoskeletal Health, University of California at Davis Medical Center, Sacramento, CA 95817, USA
| | - X P Liu
- Center for Musculoskeletal Health, University of California at Davis Medical Center, Sacramento, CA 95817, USA
| | - W Yao
- Center for Musculoskeletal Health, University of California at Davis Medical Center, Sacramento, CA 95817, USA
| | - D B Kimmel
- Department of Physiological Sciences, University of Florida, Gainesville, FL 32610, USA
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22
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Ottoy J, Niemantsverdriet E, Verhaeghe J, De Roeck E, Struyfs H, Somers C, Wyffels L, Ceyssens S, Van Mossevelde S, Van den Bossche T, Van Broeckhoven C, Ribbens A, Bjerke M, Stroobants S, Engelborghs S, Staelens S. Association of short-term cognitive decline and MCI-to-AD dementia conversion with CSF, MRI, amyloid- and 18F-FDG-PET imaging. NEUROIMAGE-CLINICAL 2019; 22:101771. [PMID: 30927601 PMCID: PMC6444289 DOI: 10.1016/j.nicl.2019.101771] [Citation(s) in RCA: 95] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/13/2018] [Revised: 01/08/2019] [Accepted: 03/10/2019] [Indexed: 12/31/2022]
Abstract
Disease-modifying treatment trials are increasingly advanced to the prodromal or preclinical phase of Alzheimer's disease (AD), and inclusion criteria are based on biomarkers rather than clinical symptoms. Therefore, it is of great interest to determine which biomarkers should be combined to accurately predict conversion from mild cognitive impairment (MCI) to AD dementia. However, up to date, only few studies performed a complete A/T/N subject characterization using each of the CSF and imaging markers, or they only investigated long-term (≥ 2 years) prognosis. This study aimed to investigate the association between cerebrospinal fluid (CSF), magnetic resonance imaging (MRI), amyloid- and 18F-FDG positron emission tomography (PET) measures at baseline, in relation to cognitive changes and conversion to AD dementia over a short-term (12-month) period. We included 13 healthy controls, 49 MCI and 16 AD dementia patients with a clinical-based diagnosis and a complete A/T/N characterization at baseline. Global cortical amyloid-β (Aβ) burden was quantified using the 18F-AV45 standardized uptake value ratio (SUVR) with two different reference regions (cerebellar grey and subcortical white matter), whereas metabolism was assessed based on 18F-FDG SUVR. CSF measures included Aβ1–42, Aβ1–40, T-tau, P-tau181, and their ratios, and MRI markers included hippocampal volumes (HV), white matter hyperintensities, and cortical grey matter volumes. Cognitive functioning was measured by MMSE and RBANS index scores. All statistical analyses were corrected for age, sex, education, and APOE ε4 genotype. As a result, faster cognitive decline was most strongly associated with hypometabolism (posterior cingulate) and smaller hippocampal volume (e.g., Δstory recall: β = +0.43 [p < 0.001] and + 0.37 [p = 0.005], resp.) at baseline. In addition, faster cognitive decline was significantly associated with higher baseline Aβ burden only if SUVR was referenced to the subcortical white matter (e.g., Δstory recall: β = −0.28 [p = 0.020]). Patients with MCI converted to AD dementia at an annual rate of 31%, which could be best predicted by combining neuropsychological testing (visuospatial construction skills) with either MRI-based HV or 18F-FDG-PET. Combining all three markers resulted in 96% specificity and 92% sensitivity. Neither amyloid-PET nor CSF biomarkers could discriminate short-term converters from non-converters. FDG-PET and MRI HV are the strongest predictors of cognitive decline and conversion to AD. Combination of visuospatial construction testing with FDG-PET or MRI HV present high predicting power of conversion. CSF and amyloid-PET seem less suitable markers of disease progression. Increased AV45-PET predicts short-term cognitive decline if SUVR is referenced to WM instead of CB.
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Affiliation(s)
- Julie Ottoy
- Molecular Imaging Center Antwerp, University of Antwerp, Antwerp, Belgium
| | - Ellis Niemantsverdriet
- Reference Center for Biological Markers of Dementia (BIODEM), Laboratory of Neurochemistry and Behavior, Institute Born-Bunge, University of Antwerp, Antwerp, Belgium
| | - Jeroen Verhaeghe
- Molecular Imaging Center Antwerp, University of Antwerp, Antwerp, Belgium
| | - Ellen De Roeck
- Reference Center for Biological Markers of Dementia (BIODEM), Laboratory of Neurochemistry and Behavior, Institute Born-Bunge, University of Antwerp, Antwerp, Belgium
| | - Hanne Struyfs
- Reference Center for Biological Markers of Dementia (BIODEM), Laboratory of Neurochemistry and Behavior, Institute Born-Bunge, University of Antwerp, Antwerp, Belgium
| | - Charisse Somers
- Reference Center for Biological Markers of Dementia (BIODEM), Laboratory of Neurochemistry and Behavior, Institute Born-Bunge, University of Antwerp, Antwerp, Belgium
| | - Leonie Wyffels
- Department of Nuclear Medicine, Antwerp University Hospital, Edegem, Belgium
| | - Sarah Ceyssens
- Department of Nuclear Medicine, Antwerp University Hospital, Edegem, Belgium
| | - Sara Van Mossevelde
- Neurodegenerative Brain Diseases Group, Center for Molecular Neurology, VIB, Antwerp, Belgium; Laboratory of Neurogenetics, Institute Born-Bunge, University of Antwerp, Antwerp, Belgium
| | - Tobi Van den Bossche
- Neurodegenerative Brain Diseases Group, Center for Molecular Neurology, VIB, Antwerp, Belgium
| | - Christine Van Broeckhoven
- Neurodegenerative Brain Diseases Group, Center for Molecular Neurology, VIB, Antwerp, Belgium; Laboratory of Neurogenetics, Institute Born-Bunge, University of Antwerp, Antwerp, Belgium
| | | | - Maria Bjerke
- Reference Center for Biological Markers of Dementia (BIODEM), Laboratory of Neurochemistry and Behavior, Institute Born-Bunge, University of Antwerp, Antwerp, Belgium
| | - Sigrid Stroobants
- Department of Nuclear Medicine, Antwerp University Hospital, Edegem, Belgium
| | - Sebastiaan Engelborghs
- Reference Center for Biological Markers of Dementia (BIODEM), Laboratory of Neurochemistry and Behavior, Institute Born-Bunge, University of Antwerp, Antwerp, Belgium
| | - Steven Staelens
- Molecular Imaging Center Antwerp, University of Antwerp, Antwerp, Belgium.
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23
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Sakr FA, Grothe MJ, Cavedo E, Jelistratova I, Habert MO, Dyrba M, Gonzalez-Escamilla G, Bertin H, Locatelli M, Lehericy S, Teipel S, Dubois B, Hampel H. Applicability of in vivo staging of regional amyloid burden in a cognitively normal cohort with subjective memory complaints: the INSIGHT-preAD study. ALZHEIMERS RESEARCH & THERAPY 2019; 11:15. [PMID: 30704537 PMCID: PMC6357385 DOI: 10.1186/s13195-019-0466-3] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/21/2018] [Accepted: 01/07/2019] [Indexed: 01/12/2023]
Abstract
BACKGROUND Current methods of amyloid PET interpretation based on the binary classification of global amyloid signal fail to identify early phases of amyloid deposition. A recent analysis of 18F-florbetapir PET data from the Alzheimer's disease Neuroimaging Initiative cohort suggested a hierarchical four-stage model of regional amyloid deposition that resembles neuropathologic estimates and can be used to stage an individual's amyloid burden in vivo. Here, we evaluated the validity of this in vivo amyloid staging model in an independent cohort of older people with subjective memory complaints (SMC). We further examined its potential association with subtle cognitive impairments in this population at elevated risk for Alzheimer's disease (AD). METHODS The monocentric INSIGHT-preAD cohort includes 318 cognitively intact older individuals with SMC. All individuals underwent 18F-florbetapir PET scanning and extensive neuropsychological testing. We projected the regional amyloid uptake signal into the previously proposed hierarchical staging model of in vivo amyloid progression. We determined the adherence to this model across all cases and tested the association between increasing in vivo amyloid stage and cognitive performance using ANCOVA models. RESULTS In total, 156 participants (49%) showed evidence of regional amyloid deposition, and all but 2 of these (99%) adhered to the hierarchical regional pattern implied by the in vivo amyloid progression model. According to a conventional binary classification based on global signal (SUVRCereb = 1.10), individuals in stages III and IV were classified as amyloid-positive (except one in stage III), but 99% of individuals in stage I and even 28% of individuals in stage II were classified as amyloid-negative. Neither in vivo amyloid stage nor conventional binary amyloid status was significantly associated with cognitive performance in this preclinical cohort. CONCLUSIONS The proposed hierarchical staging scheme of PET-evidenced amyloid deposition generalizes well to data from an independent cohort of older people at elevated risk for AD. Future studies will determine the prognostic value of the staging approach for predicting longitudinal cognitive decline in older individuals at increased risk for AD.
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Affiliation(s)
- Fatemah A Sakr
- Department of Psychosomatic Medicine, Clinical Dementia Research, Faculty of Medicine, Rostock University, Rostock, Germany. .,German Center for Neurodegenerative Diseases (DZNE), Rostock, Germany.
| | - Michel J Grothe
- German Center for Neurodegenerative Diseases (DZNE), Rostock, Germany
| | - Enrica Cavedo
- AXA Research Fund and Sorbonne University Chair, Paris, France.,Sorbonne University, GRC n° 21, Alzheimer Precision Medicine (APM), AP-HP, Pitié-Salpêtrière Hospital, Boulevard de l'hôpital, F-75013, Paris, France.,Brain and Spine Institute (ICM), INSERM U 1127, CNRS UMR 7225, Boulevard de l'hôpital, F-75013, Paris, France.,Department of Neurology, Institute of Memory and Alzheimer's Disease (IM2A), Pitié-Salpêtrière Hospital, AP-HP, Boulevard de l'hôpital, F-75013, Paris, France.,Qynapse, Paris, France
| | | | - Marie-Odile Habert
- Sorbonne University, UPMC University Paris 06, CNRS, INSERM, Laboratoire d'Imagerie Biomédicale, F-75013, Paris, France.,Multi-center Neuroimaging Platform.,Department of Nuclear Medicine, Pitié-Salpêtrière Hospital, AP-HP, F-75013, Paris, France
| | - Martin Dyrba
- German Center for Neurodegenerative Diseases (DZNE), Rostock, Germany
| | - Gabriel Gonzalez-Escamilla
- Department of Neurology, University Medical Center of the Johannes-Gutenberg-University Mainz, Langenbeck str, 155131, Mainz, Germany
| | | | - Maxime Locatelli
- Sorbonne University, UPMC University Paris 06, CNRS, INSERM, Laboratoire d'Imagerie Biomédicale, F-75013, Paris, France.,Multi-center Neuroimaging Platform.,Department of Nuclear Medicine, Pitié-Salpêtrière Hospital, AP-HP, F-75013, Paris, France
| | - Stephane Lehericy
- Brain and Spine Institute (ICM), INSERM U 1127, CNRS UMR 7225, Boulevard de l'hôpital, F-75013, Paris, France.,Multi-center Neuroimaging Platform.,Centre de NeuroImagerie de Recherche (CENIR), Institut du Cerveau et de la Moelle Epiniere (ICM), Paris, France.,Department of Neuroradiology, Salpêtriere Hospital, Paris, France
| | - Stefan Teipel
- Department of Psychosomatic Medicine, Clinical Dementia Research, Faculty of Medicine, Rostock University, Rostock, Germany.,German Center for Neurodegenerative Diseases (DZNE), Rostock, Germany
| | - Bruno Dubois
- Sorbonne University, GRC n° 21, Alzheimer Precision Medicine (APM), AP-HP, Pitié-Salpêtrière Hospital, Boulevard de l'hôpital, F-75013, Paris, France.,Brain and Spine Institute (ICM), INSERM U 1127, CNRS UMR 7225, Boulevard de l'hôpital, F-75013, Paris, France.,Department of Neurology, Institute of Memory and Alzheimer's Disease (IM2A), Pitié-Salpêtrière Hospital, AP-HP, Boulevard de l'hôpital, F-75013, Paris, France
| | - Harald Hampel
- AXA Research Fund and Sorbonne University Chair, Paris, France.,Sorbonne University, GRC n° 21, Alzheimer Precision Medicine (APM), AP-HP, Pitié-Salpêtrière Hospital, Boulevard de l'hôpital, F-75013, Paris, France.,Brain and Spine Institute (ICM), INSERM U 1127, CNRS UMR 7225, Boulevard de l'hôpital, F-75013, Paris, France.,Department of Neurology, Institute of Memory and Alzheimer's Disease (IM2A), Pitié-Salpêtrière Hospital, AP-HP, Boulevard de l'hôpital, F-75013, Paris, France
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24
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Lowe VJ, Lundt ES, Senjem ML, Schwarz CG, Min HK, Przybelski SA, Kantarci K, Knopman D, Petersen RC, Jack CR. White Matter Reference Region in PET Studies of 11C-Pittsburgh Compound B Uptake: Effects of Age and Amyloid-β Deposition. J Nucl Med 2018; 59:1583-1589. [PMID: 29674420 PMCID: PMC6167534 DOI: 10.2967/jnumed.117.204271] [Citation(s) in RCA: 31] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2017] [Accepted: 04/04/2018] [Indexed: 02/06/2023] Open
Abstract
Amyloid-β (Aβ) deposition as seen on PET using an Aβ-binding agent is a critical diagnostic biomarker for Alzheimer disease (AD). Some reports suggest using white matter (WM) as a reference region for quantification of serial Aβ PET studies; however, nonspecific WM retention in Aβ PET in people with dementia or cognitively unimpaired (CU) has been widely reported and is poorly understood. Methods: To investigate the suitability of WM as a reference region and the factors affecting WM 11C-Pittsburgh compound B (11C-PiB) uptake variability, we conducted a retrospective study on 2 large datasets: a longitudinal study of participants (n = 577) who were CU, had mild cognitive impairment, or had dementia likely due to AD; and a cross-sectional study of single-scan PET imaging in CU subjects (n = 1,349). In the longitudinal study, annual changes in WM 11C-PiB uptake were assessed, and in the cross-sectional study, WM 11C-PiB uptake was assessed relative to subject age. Results: Overall, we found that WM 11C-PiB uptake showed age-related increases, which varied with the WM regions selected. Further, variable annual WM 11C-PiB uptake changes were seen with different gray matter (GM) 11C-PiB baseline uptake levels. Conclusion: WM binding increases with age and varies with GM 11C-PiB. These correlations should be considered when using WM for normalization in 11C-PiB PET studies. The cerebellar crus1+crus2 showed no increase with age and cerebellar GM+WM showed minimal increase, supporting their use as reference regions for cross-sectional studies comparing wide age spans. In longitudinal studies, the increase in WM uptake may be minimal in the short-term and thus using WM as a reference region in these studies seems reasonable. However, as participants age, the findings may be affected by changes in WM uptake. Changes in WM 11C-PiB uptake may relate to disease progression, warranting examination of the causes of WM 11C-PiB uptake.
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Affiliation(s)
- Val J Lowe
- Department of Radiology, Mayo Clinic, Rochester, Minnesota
| | - Emily S Lundt
- Division of Biostatistics, Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota
| | - Matthew L Senjem
- Department of Radiology, Mayo Clinic, Rochester, Minnesota
- Department of Information Technology, Mayo Clinic, Rochester, Minnesota; and
| | | | - Hoon-Ki Min
- Department of Radiology, Mayo Clinic, Rochester, Minnesota
| | - Scott A Przybelski
- Division of Biostatistics, Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota
| | - Kejal Kantarci
- Department of Radiology, Mayo Clinic, Rochester, Minnesota
| | - David Knopman
- Department of Neurology, Mayo Clinic, Rochester, Minnesota
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25
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Meyer MA, Caccia A, Martinez D, Mingos MA. PET imaging of 18F-florbetapir in cognitively impaired individuals: Lack of activity within the cerebellar cortex. Neurol Int 2018; 10:7666. [PMID: 30344964 PMCID: PMC6176476 DOI: 10.4081/ni.2018.7666] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2018] [Accepted: 06/18/2018] [Indexed: 11/23/2022] Open
Abstract
Ten individuals suspected of having possible Alzheimer disease underwent PET imaging using 18F-Flubetapir. Only one of ten individuals had a pattern typical for normal elderly control subjects with 9 of the 10 showing a Alzheimer type pattern for the cerebral cortex yet all 10 subjects had uniformly low to absent tracer localization to the cerebellar cortex; significantly high tracer activity was noted within the subcortical white matter of the cerebellum in a symmetric manner in all cases. In consideration of studies that have shown amyloid deposits within the cerebellar cortex in 90% of pathologically proven cases of Alzheimer's disease, these findings raise questions about the actual clinical value of florbetapir PET imaging in evaluating cerebellar involvement and raises questions whether PET imaging of this tracer accurately portrays patterns of amyloid deposition, as there is rapid hepatic metabolism of the parent compound after intravenous injection. Possible links to Alzheimer's disease related alterations in blood-brain barrier permeability to the parent compound and subsequent radiolabelled metabolites are discussed as potential mechanisms that could explain the associated localization of the tracer to the brainstem and subcortical white matter within the cerebrum and cerebellum of Alzheimer's disease patients.
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Affiliation(s)
- Michael A Meyer
- Departments of Neurology and Nuclear Medicine, Guthrie Clinic, Sayre PA, USA
| | - Allison Caccia
- Departments of Neurology and Nuclear Medicine, Guthrie Clinic, Sayre PA, USA
| | - Danielle Martinez
- Departments of Neurology and Nuclear Medicine, Guthrie Clinic, Sayre PA, USA
| | - Mark A Mingos
- Departments of Neurology and Nuclear Medicine, Guthrie Clinic, Sayre PA, USA
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26
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Niemantsverdriet E, Ottoy J, Somers C, De Roeck E, Struyfs H, Soetewey F, Verhaeghe J, Van den Bossche T, Van Mossevelde S, Goeman J, De Deyn PP, Mariën P, Versijpt J, Sleegers K, Van Broeckhoven C, Wyffels L, Albert A, Ceyssens S, Stroobants S, Staelens S, Bjerke M, Engelborghs S. The Cerebrospinal Fluid Aβ1-42/Aβ1-40 Ratio Improves Concordance with Amyloid-PET for Diagnosing Alzheimer's Disease in a Clinical Setting. J Alzheimers Dis 2018; 60:561-576. [PMID: 28869470 PMCID: PMC5611891 DOI: 10.3233/jad-170327] [Citation(s) in RCA: 65] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
Background: Evidence suggests that the concordance between amyloid-PET and cerebrospinal fluid (CSF) amyloid-β (Aβ) increases when the CSF Aβ1–42/Aβ1–40 ratio is used as compared to CSF Aβ1–42 levels alone. Objective: In order to test this hypothesis, we set up a prospective longitudinal study comparing the concordance between different amyloid biomarkers for Alzheimer’s disease (AD) in a clinical setting. Methods: Seventy-eight subjects (AD dementia (n = 17), mild cognitive impairment (MCI, n = 48), and cognitively healthy controls (n = 13)) underwent a [18F]Florbetapir ([18F]AV45) PET scan, [18F]FDG PET scan, MRI scan, and an extensive neuropsychological examination. In a large subset (n = 67), a lumbar puncture was performed and AD biomarkers were analyzed (Aβ1–42, Aβ1–40, T-tau, P-tau181). Results: We detected an increased concordance in the visual and quantitative (standardized uptake value ratio (SUVR) and total volume of distribution (VT)) [18F]AV45 PET measures when the CSF Aβ1–42/Aβ1–40 was applied compared to Aβ1–42 alone. CSF biomarkers were stronger associated to [18F]AV45 PET for SUVR values when considering the total brain white matter as reference region instead of cerebellar grey matter Conclusions: The concordance between CSF Aβ and [18F]AV45 PET increases when the CSF Aβ1–42/Aβ1–40 ratio is applied. This finding is of most importance for the biomarker-based diagnosis of AD as well as for selection of subjects for clinical trials with potential disease-modifying therapies for AD.
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Affiliation(s)
- Ellis Niemantsverdriet
- Reference Center for Biological Markers of Dementia (BIODEM), Laboratory of Neurochemistry and Behavior, Institute Born-Bunge, UAntwerp, Antwerp, Belgium
| | - Julie Ottoy
- Molecular Imaging Center Antwerp (MICA), UAntwerp, Antwerp, Belgium
| | - Charisse Somers
- Reference Center for Biological Markers of Dementia (BIODEM), Laboratory of Neurochemistry and Behavior, Institute Born-Bunge, UAntwerp, Antwerp, Belgium
| | - Ellen De Roeck
- Reference Center for Biological Markers of Dementia (BIODEM), Laboratory of Neurochemistry and Behavior, Institute Born-Bunge, UAntwerp, Antwerp, Belgium.,Faculty of Psychology and Educational Sciences, Vrije Universiteit Brussels, Brussels, Belgium
| | - Hanne Struyfs
- Reference Center for Biological Markers of Dementia (BIODEM), Laboratory of Neurochemistry and Behavior, Institute Born-Bunge, UAntwerp, Antwerp, Belgium
| | - Femke Soetewey
- Reference Center for Biological Markers of Dementia (BIODEM), Laboratory of Neurochemistry and Behavior, Institute Born-Bunge, UAntwerp, Antwerp, Belgium
| | - Jeroen Verhaeghe
- Molecular Imaging Center Antwerp (MICA), UAntwerp, Antwerp, Belgium
| | - Tobi Van den Bossche
- VIB-UAntwerp Center for Molecular Neurology, Antwerp, Belgium.,Laboratory of Neurogenetics, Institute Born-Bunge, UAntwerp, Antwerp, Belgium.,Department of Neurology and Memory Clinic, Hospital Network Antwerp (ZNA) Middelheim and Hoge Beuken, Antwerp, Belgium
| | - Sara Van Mossevelde
- VIB-UAntwerp Center for Molecular Neurology, Antwerp, Belgium.,Laboratory of Neurogenetics, Institute Born-Bunge, UAntwerp, Antwerp, Belgium.,Department of Neurology and Memory Clinic, Hospital Network Antwerp (ZNA) Middelheim and Hoge Beuken, Antwerp, Belgium
| | - Johan Goeman
- Department of Neurology and Memory Clinic, Hospital Network Antwerp (ZNA) Middelheim and Hoge Beuken, Antwerp, Belgium
| | - Peter Paul De Deyn
- Reference Center for Biological Markers of Dementia (BIODEM), Laboratory of Neurochemistry and Behavior, Institute Born-Bunge, UAntwerp, Antwerp, Belgium.,Department of Neurology and Memory Clinic, Hospital Network Antwerp (ZNA) Middelheim and Hoge Beuken, Antwerp, Belgium
| | - Peter Mariën
- Department of Neurology and Memory Clinic, Hospital Network Antwerp (ZNA) Middelheim and Hoge Beuken, Antwerp, Belgium.,Clinical and Experimental Neurolinguistics, CLIN, Vrije Universiteit Brussel (VUB), Brussels, Belgium
| | - Jan Versijpt
- Vrije Universiteit Brussel(VUB), University Hospital Brussels (UZ Brussel), Department of Neurology, Brussels, Belgium
| | - Kristel Sleegers
- VIB-UAntwerp Center for Molecular Neurology, Antwerp, Belgium.,Laboratory of Neurogenetics, Institute Born-Bunge, UAntwerp, Antwerp, Belgium
| | - Christine Van Broeckhoven
- VIB-UAntwerp Center for Molecular Neurology, Antwerp, Belgium.,Laboratory of Neurogenetics, Institute Born-Bunge, UAntwerp, Antwerp, Belgium
| | - Leonie Wyffels
- Molecular Imaging Center Antwerp (MICA), UAntwerp, Antwerp, Belgium.,Departmentof Nuclear Medicine, Antwerp University Hospital, Antwerp, Belgium
| | - Adrien Albert
- Departmentof Nuclear Medicine, Antwerp University Hospital, Antwerp, Belgium
| | - Sarah Ceyssens
- Departmentof Nuclear Medicine, Antwerp University Hospital, Antwerp, Belgium
| | - Sigrid Stroobants
- Molecular Imaging Center Antwerp (MICA), UAntwerp, Antwerp, Belgium.,Departmentof Nuclear Medicine, Antwerp University Hospital, Antwerp, Belgium
| | - Steven Staelens
- Molecular Imaging Center Antwerp (MICA), UAntwerp, Antwerp, Belgium
| | - Maria Bjerke
- Reference Center for Biological Markers of Dementia (BIODEM), Laboratory of Neurochemistry and Behavior, Institute Born-Bunge, UAntwerp, Antwerp, Belgium
| | - Sebastiaan Engelborghs
- Reference Center for Biological Markers of Dementia (BIODEM), Laboratory of Neurochemistry and Behavior, Institute Born-Bunge, UAntwerp, Antwerp, Belgium.,Department of Neurology and Memory Clinic, Hospital Network Antwerp (ZNA) Middelheim and Hoge Beuken, Antwerp, Belgium
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27
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Ottoy J, Verhaeghe J, Niemantsverdriet E, Engelborghs S, Stroobants S, Staelens S. A simulation study on the impact of the blood flow-dependent component in [18F]AV45 SUVR in Alzheimer's disease. PLoS One 2017; 12:e0189155. [PMID: 29211812 PMCID: PMC5718604 DOI: 10.1371/journal.pone.0189155] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2017] [Accepted: 11/20/2017] [Indexed: 01/04/2023] Open
Abstract
Background Increased brain uptake on [18F]AV45 PET is a biomarker for Alzheimer’s disease (AD). The standardised uptake value ratio (SUVR) is widely used for quantification but is subject to variability. Here we evaluate how SUVR of a cortical target region is affected by blood flow changes in the target and two frequently used reference regions. Methods Regional baseline time-activity curves (TACs) were simulated based on metabolite-corrected plasma input functions and pharmacokinetic parameters obtained from our previously acquired data in healthy control (HC; n = 10), amnestic mild cognitive impairment (aMCI; n = 15) and AD cohorts (n = 9). Blood flow changes were simulated by altering the regional tracer delivery rate K1 (and clearance rate k2) between -40% and +40% from its regional baseline value in the target region and/or cerebellar grey (CB) or subcortical white matter (WM) reference regions. The corresponding change in SUVR was calculated at 50–60 min post-injection. Results A -40% blood flow reduction in the target resulted in an increased SUVRtarget (e.g. SUVRprecuneus: +10.0±5% in HC, +2.5±2% in AD), irrespective of the used reference region. A -40% blood flow reduction in the WM reference region increased SUVRWM (+11.5±4% in HC, +13.5±3% in AD) while a blood flow reduction in CB decreased SUVRCB (-9.5±6% in HC, -5.5±2% in AD), irrespective of the used target region. A -40% flow reduction in both the precuneus and reference WM (i.e., global flow change) induced an increased SUVR (+22.5±8% in HC, +16.0±4% in AD). When considering reference CB instead, SUVR was decreased by less than -5% (both in HC and AD). Conclusion Blood flow changes introduce alterations in [18F]AV45 PET SUVR. Flow reductions in the CB and WM reference regions resulted in a decreased and increased SUVR of the target, respectively. SUVR was more affected by global blood flow changes when considering WM instead of CB normalization.
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Affiliation(s)
- Julie Ottoy
- Molecular Imaging Center Antwerp, University of Antwerp, Antwerp, Belgium
| | - Jeroen Verhaeghe
- Molecular Imaging Center Antwerp, University of Antwerp, Antwerp, Belgium
| | - Ellis Niemantsverdriet
- Reference Center for Biological Markers of Dementia (BIODEM), University of Antwerp, Antwerp, Belgium
| | - Sebastiaan Engelborghs
- Reference Center for Biological Markers of Dementia (BIODEM), University of Antwerp, Antwerp, Belgium
- Department of Neurology and Memory Clinic, Hospital Network Antwerp (ZNA) Hoge Beuken en Middelheim, Antwerp, Belgium
| | - Sigrid Stroobants
- Department of Nuclear Medicine, Antwerp University Hospital, Edegem, Belgium
| | - Steven Staelens
- Molecular Imaging Center Antwerp, University of Antwerp, Antwerp, Belgium
- * E-mail:
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28
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Bullich S, Barthel H, Koglin N, Becker GA, De Santi S, Jovalekic A, Stephens AW, Sabri O. Validation of Noninvasive Tracer Kinetic Analysis of 18F-Florbetaben PET Using a Dual-Time-Window Acquisition Protocol. J Nucl Med 2017; 59:1104-1110. [PMID: 29175981 DOI: 10.2967/jnumed.117.200964] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2017] [Accepted: 11/10/2017] [Indexed: 11/16/2022] Open
Abstract
Accurate amyloid PET quantification is necessary for monitoring amyloid-β accumulation and response to therapy. Currently, most of the studies are analyzed using the static SUV ratio (SUVR) approach because of its simplicity. However, this approach may be influenced by changes in cerebral blood flow (CBF) or radiotracer clearance. Full tracer kinetic models require arterial blood sampling and dynamic image acquisition. The objectives of this work were, first, to validate a noninvasive kinetic modeling approach for 18F-florbetaben PET using an acquisition protocol with the best compromise between quantification accuracy and simplicity and, second, to assess the impact of CBF changes and radiotracer clearance on SUVRs and noninvasive kinetic modeling data in 18F-florbetaben PET. Methods: Using data from 20 subjects (10 patients with probable Alzheimer dementia and 10 healthy volunteers), the nondisplaceable binding potential (BPND) obtained from the full kinetic analysis was compared with the SUVR and with noninvasive tracer kinetic methods (simplified reference tissue model and multilinear reference tissue model 2). Various approaches using shortened or interrupted acquisitions were compared with the results of the full acquisition (0-140 min). Simulations were performed to assess the effect of CBF and radiotracer clearance changes on SUVRs and noninvasive kinetic modeling outputs. Results: An acquisition protocol using time windows of 0-30 and 120-140 min with appropriate interpolation of the missing time points provided the best compromise between patient comfort and quantification accuracy. Excellent agreement was found between BPND obtained using the full protocol and BPND obtained using the dual-window protocol (for multilinear reference tissue model 2, BPND [dual-window] = 0.01 + 1.00·BPND [full], R2 = 0.97; for simplified reference tissue model, BPND [dual-window] = 0.05 + 0.92·BPND [full], R2 = 0.93). Simulations showed a limited impact of CBF and radiotracer clearance changes on multilinear reference tissue model parameters and SUVR. Conclusion: This study demonstrated accurate noninvasive kinetic modeling of 18F-florbetaben PET data using a dual-window acquisition, thus providing a good compromise between quantification accuracy, scan duration, and patient burden. The influence of CBF and radiotracer clearance changes on amyloid-β load estimates was small. For most clinical research applications, the SUVR approach is appropriate. However, for longitudinal studies in which maximum quantification accuracy is desired, this noninvasive dual-window acquisition with kinetic analysis is recommended.
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Affiliation(s)
| | - Henryk Barthel
- Department of Nuclear Medicine, University Hospital Leipzig, Leipzig, Germany; and
| | | | - Georg A Becker
- Department of Nuclear Medicine, University Hospital Leipzig, Leipzig, Germany; and
| | | | | | | | - Osama Sabri
- Department of Nuclear Medicine, University Hospital Leipzig, Leipzig, Germany; and
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29
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Niemantsverdriet E, Valckx S, Bjerke M, Engelborghs S. Alzheimer's disease CSF biomarkers: clinical indications and rational use. Acta Neurol Belg 2017; 117:591-602. [PMID: 28752420 PMCID: PMC5565643 DOI: 10.1007/s13760-017-0816-5] [Citation(s) in RCA: 76] [Impact Index Per Article: 10.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2017] [Accepted: 07/12/2017] [Indexed: 11/29/2022]
Abstract
This review focusses on the validation and standardization of Alzheimer's disease (AD) cerebrospinal fluid (CSF) biomarkers, as well as on the current clinical indications and rational use of CSF biomarkers in daily clinical practice. The validated AD CSF biomarkers, Aβ1-42, T-tau, and P-tau181, have an added value in the (differential) diagnosis of AD and related disorders, including mixed pathologies, atypical presentations, and in case of ambiguous clinical dementia diagnosis. CSF biomarkers should not be routinely used in the diagnostic work-up of dementia and cannot be used to diagnose non-AD dementias. In cognitively healthy subjects, CSF biomarkers can only be applied for research purposes, e.g., to identify pre-clinical AD in the context of clinical trials with potentially disease-modifying drugs. Therefore, biomarker-based early diagnosis of AD offers great opportunities for preventive treatment development in the near future.
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Affiliation(s)
- Ellis Niemantsverdriet
- Reference Center for Biological Markers of Dementia (BIODEM), Laboratory of Neurochemistry and Behavior, Institute Born-Bunge, University of Antwerp (UAntwerp), Antwerp, Belgium
| | - Sara Valckx
- Reference Center for Biological Markers of Dementia (BIODEM), Laboratory of Neurochemistry and Behavior, Institute Born-Bunge, University of Antwerp (UAntwerp), Antwerp, Belgium
| | - Maria Bjerke
- Reference Center for Biological Markers of Dementia (BIODEM), Laboratory of Neurochemistry and Behavior, Institute Born-Bunge, University of Antwerp (UAntwerp), Antwerp, Belgium
| | - Sebastiaan Engelborghs
- Reference Center for Biological Markers of Dementia (BIODEM), Laboratory of Neurochemistry and Behavior, Institute Born-Bunge, University of Antwerp (UAntwerp), Antwerp, Belgium.
- Department of Neurology and Memory Clinic, Hospital Network Antwerp (ZNA) Middelheim and Hoge Beuken, Antwerp, Belgium.
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