1
|
Iaccarino L, Llibre-Guerra JJ, McDade E, Edwards L, Gordon B, Benzinger T, Hassenstab J, Kramer JH, Li Y, Miller BL, Miller Z, Morris JC, Mundada N, Perrin RJ, Rosen HJ, Soleimani-Meigooni D, Strom A, Tsoy E, Wang G, Xiong C, Allegri R, Chrem P, Vazquez S, Berman SB, Chhatwal J, Masters CL, Farlow MR, Jucker M, Levin J, Salloway S, Fox NC, Day GS, Gorno-Tempini ML, Boxer AL, La Joie R, Bateman R, Rabinovici GD. Molecular neuroimaging in dominantly inherited versus sporadic early-onset Alzheimer's disease. Brain Commun 2024; 6:fcae159. [PMID: 38784820 PMCID: PMC11114609 DOI: 10.1093/braincomms/fcae159] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2023] [Revised: 03/14/2024] [Accepted: 05/01/2024] [Indexed: 05/25/2024] Open
Abstract
Approximately 5% of Alzheimer's disease patients develop symptoms before age 65 (early-onset Alzheimer's disease), with either sporadic (sporadic early-onset Alzheimer's disease) or dominantly inherited (dominantly inherited Alzheimer's disease) presentations. Both sporadic early-onset Alzheimer's disease and dominantly inherited Alzheimer's disease are characterized by brain amyloid-β accumulation, tau tangles, hypometabolism and neurodegeneration, but differences in topography and magnitude of these pathological changes are not fully elucidated. In this study, we directly compared patterns of amyloid-β plaque deposition and glucose hypometabolism in sporadic early-onset Alzheimer's disease and dominantly inherited Alzheimer's disease individuals. Our analysis included 134 symptomatic sporadic early-onset Alzheimer's disease amyloid-Positron Emission Tomography (PET)-positive cases from the University of California, San Francisco, Alzheimer's Disease Research Center (mean ± SD age 59.7 ± 5.6 years), 89 symptomatic dominantly inherited Alzheimer's disease cases (age 45.8 ± 9.3 years) and 102 cognitively unimpaired non-mutation carriers from the Dominantly Inherited Alzheimer Network study (age 44.9 ± 9.2). Each group underwent clinical and cognitive examinations, 11C-labelled Pittsburgh Compound B-PET and structural MRI. 18F-Fluorodeoxyglucose-PET was also available for most participants. Positron Emission Tomography scans from both studies were uniformly processed to obtain a standardized uptake value ratio (PIB50-70 cerebellar grey reference and FDG30-60 pons reference) images. Statistical analyses included pairwise global and voxelwise group comparisons and group-independent component analyses. Analyses were performed also adjusting for covariates including age, sex, Mini-Mental State Examination, apolipoprotein ε4 status and average composite cortical of standardized uptake value ratio. Compared with dominantly inherited Alzheimer's disease, sporadic early-onset Alzheimer's disease participants were older at age of onset (mean ± SD, 54.8 ± 8.2 versus 41.9 ± 8.2, Cohen's d = 1.91), with more years of education (16.4 ± 2.8 versus 13.5 ± 3.2, d = 1) and more likely to be apolipoprotein ε4 carriers (54.6% ε4 versus 28.1%, Cramer's V = 0.26), but similar Mini-Mental State Examination (20.6 ± 6.1 versus 21.2 ± 7.4, d = 0.08). Sporadic early-onset Alzheimer's disease had higher global cortical Pittsburgh Compound B-PET binding (mean ± SD standardized uptake value ratio, 1.92 ± 0.29 versus 1.58 ± 0.44, d = 0.96) and greater global cortical 18F-fluorodeoxyglucose-PET hypometabolism (mean ± SD standardized uptake value ratio, 1.32 ± 0.1 versus 1.39 ± 0.19, d = 0.48) compared with dominantly inherited Alzheimer's disease. Fully adjusted comparisons demonstrated relatively higher Pittsburgh Compound B-PET standardized uptake value ratio in the medial occipital, thalami, basal ganglia and medial/dorsal frontal regions in dominantly inherited Alzheimer's disease versus sporadic early-onset Alzheimer's disease. Sporadic early-onset Alzheimer's disease showed relatively greater 18F-fluorodeoxyglucose-PET hypometabolism in Alzheimer's disease signature temporoparietal regions and caudate nuclei, whereas dominantly inherited Alzheimer's disease showed relatively greater hypometabolism in frontal white matter and pericentral regions. Independent component analyses largely replicated these findings by highlighting common and unique Pittsburgh Compound B-PET and 18F-fluorodeoxyglucose-PET binding patterns. In summary, our findings suggest both common and distinct patterns of amyloid and glucose hypometabolism in sporadic and dominantly inherited early-onset Alzheimer's disease.
Collapse
Affiliation(s)
- Leonardo Iaccarino
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA 94158, USA
| | - Jorge J Llibre-Guerra
- The Dominantly Inherited Alzheimer Network (DIAN), St Louis, MO 63108, USA
- Department of Neurology, Washington University in St Louis, St Louis, MO 63108, USA
| | - Eric McDade
- The Dominantly Inherited Alzheimer Network (DIAN), St Louis, MO 63108, USA
- Department of Neurology, Washington University in St Louis, St Louis, MO 63108, USA
| | - Lauren Edwards
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA 94158, USA
| | - Brian Gordon
- Department of Radiology, Washington University in St Louis, St Louis, MO 63110, USA
| | - Tammie Benzinger
- Department of Radiology, Washington University in St Louis, St Louis, MO 63110, USA
| | - Jason Hassenstab
- The Dominantly Inherited Alzheimer Network (DIAN), St Louis, MO 63108, USA
- Department of Neurology, Washington University in St Louis, St Louis, MO 63108, USA
| | - Joel H Kramer
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA 94158, USA
| | - Yan Li
- Department of Biostatistics, Washington University in St Louis, St Louis, MO 63110, USA
| | - Bruce L Miller
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA 94158, USA
| | - Zachary Miller
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA 94158, USA
| | - John C Morris
- The Dominantly Inherited Alzheimer Network (DIAN), St Louis, MO 63108, USA
- Department of Neurology, Washington University in St Louis, St Louis, MO 63108, USA
| | - Nidhi Mundada
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA 94158, USA
| | - Richard J Perrin
- Department of Pathology and Immunology, Washington University in St Louis, St Louis, MO 63110, USA
| | - Howard J Rosen
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA 94158, USA
| | - David Soleimani-Meigooni
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA 94158, USA
| | - Amelia Strom
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA 94158, USA
| | - Elena Tsoy
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA 94158, USA
| | - Guoqiao Wang
- Department of Biostatistics, Washington University in St Louis, St Louis, MO 63110, USA
| | - Chengjie Xiong
- Department of Biostatistics, Washington University in St Louis, St Louis, MO 63110, USA
| | - Ricardo Allegri
- Department of Cognitive Neurology, Institute for Neurological Research Fleni, Buenos Aires 1428, Argentina
| | - Patricio Chrem
- Department of Cognitive Neurology, Institute for Neurological Research Fleni, Buenos Aires 1428, Argentina
| | - Silvia Vazquez
- Department of Cognitive Neurology, Institute for Neurological Research Fleni, Buenos Aires 1428, Argentina
| | - Sarah B Berman
- Department of Neurology, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - Jasmeer Chhatwal
- Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA
| | - Colin L Masters
- Department of Neuroscience, Florey Institute, The University of Melbourne, Melbourne 3052, Australia
| | - Martin R Farlow
- Neuroscience Center, Indiana University School of Medicine at Indianapolis, Indiana, IN 46202, USA
| | - Mathias Jucker
- DZNE-German Center for Neurodegenerative Diseases, Tübingen 72076, Germany
| | - Johannes Levin
- Department of Neurology, Ludwig-Maximilians-University, Munich 80539, Germany
- German Center for Neurodegenerative Diseases, Munich 81377, Germany
- Munich Cluster for Systems Neurology (SyNergy), Munich 81377, Germany
| | - Stephen Salloway
- Memory & Aging Program, Butler Hospital, Brown University in Providence, RI 02906, USA
| | - Nick C Fox
- Dementia Research Centre, Department of Neurodegenerative Disease, University College London Institute of Neurology, London WC1N 3BG, UK
| | - Gregory S Day
- Department of Neurology, Mayo Clinic Florida, Jacksonville, FL 33224, USA
| | - Maria Luisa Gorno-Tempini
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA 94158, USA
| | - Adam L Boxer
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA 94158, USA
| | - Renaud La Joie
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA 94158, USA
| | - Randall Bateman
- The Dominantly Inherited Alzheimer Network (DIAN), St Louis, MO 63108, USA
- Department of Neurology, Washington University in St Louis, St Louis, MO 63108, USA
| | - Gil D Rabinovici
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA 94158, USA
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA 94143, USA
| |
Collapse
|
2
|
Haghdel A, Smith N, Glodzik L, Li Y, Wang X, Crowder T, Zhu YS, Butler T, Blennow K, McIntire LB, Pahlajani S, Osborne J, Chiang G, de Leon M, Ivanidze J. Evidence of Pericyte Damage in a Cognitively Normal Cohort: Association With CSF and PET Biomarkers of Alzheimer Disease. Alzheimer Dis Assoc Disord 2024; 38:107-111. [PMID: 38752577 PMCID: PMC11132093 DOI: 10.1097/wad.0000000000000623] [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: 02/02/2024] [Accepted: 04/07/2024] [Indexed: 05/25/2024]
Abstract
BACKGROUND Blood-brain barrier (BBB) dysfunction is emerging as an important pathophysiologic factor in Alzheimer disease (AD). Cerebrospinal fluid (CSF) platelet-derived growth factor receptor-β (PDGFRβ) is a biomarker of BBB pericyte injury and has been implicated in cognitive impairment and AD. METHODS We aimed to study CSF PDGFRβ protein levels, along with CSF biomarkers of brain amyloidosis and tau pathology in a well-characterized population of cognitively unimpaired individuals and correlated CSF findings with amyloid-PET positivity. We performed an institutional review board (IRB)-approved cross-sectional analysis of a prospectively enrolled cohort of 36 cognitively normal volunteers with available CSF, Pittsburgh compound B PET/CT, Mini-Mental State Exam score, Global Deterioration Scale, and known apolipoprotein E ( APOE ) ε4 status. RESULTS Thirty-six subjects were included. Mean age was 63.3 years; 31 of 36 were female, 6 of 36 were amyloid-PET-positive and 12 of 36 were APOE ε4 carriers. We found a moderate positive correlation between CSF PDGFRβ and both total Tau (r=0.45, P =0.006) and phosphorylated Tau 181 (r=0.51, P =0.002). CSF PDGFRβ levels were not associated with either the CSF Aβ42 or the amyloid-PET. CONCLUSIONS We demonstrated a moderate positive correlation between PDGFRβ and both total Tau and phosphorylated Tau 181 in cognitively normal individuals. Our data support the hypothesis that BBB dysfunction represents an important early pathophysiologic step in AD, warranting larger prospective studies. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT00094939.
Collapse
Affiliation(s)
| | | | | | - Yi Li
- Department of Radiology, Weill Cornell Medicine
| | | | - Tamara Crowder
- Clinical and Translational Science Center, Weill Cornell Medicine, New York, NY
| | - Yuan-Shan Zhu
- Clinical and Translational Science Center, Weill Cornell Medicine, New York, NY
| | | | - Kaj Blennow
- Institute of Neuroscience and Physiology, Sahlgrenska Academy, Department of Psychiatry and Neurochemistry, University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Department of Psychiatry and Neurochemistry, Sahlgrenska University Hospital, Mölndal, Sweden
| | | | | | | | | | | | | |
Collapse
|
3
|
Yue JH, Zhang QH, Yang X, Wang P, Sun XC, Yan SY, Li A, Zhao WW, Cao DN, Wang Y, Wei ZY, Li XL, Zhu LW, Yang G, Mah JZ. Magnetic resonance imaging of white matter in Alzheimer's disease: a global bibliometric analysis from 1990 to 2022. Front Neurosci 2023; 17:1163809. [PMID: 37304017 PMCID: PMC10248146 DOI: 10.3389/fnins.2023.1163809] [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: 02/11/2023] [Accepted: 04/26/2023] [Indexed: 06/13/2023] Open
Abstract
Background Alzheimer's disease (AD) is a common, progressive, irreversible, and fatal neurodegenerative disorder with rapidly increasing worldwide incidence. Although much research on magnetic resonance imaging (MRI) of the white matter (WM) in AD has been published, no bibliometric analysis study has investigated this issue. Thus, this study aimed to provide an overview of the current status, hotspots, and trends in MRI of WM in AD. Methods We searched for records related to MRI studies of WM in AD from 1990 to 2022 in the Web of Science Core Collection (WOSCC) database. CiteSpace (version 5.1.R8) and VOSviewer (version 1.6.19) software were used for bibliometric analyses. Results A total of 2,199 articles were obtained from this study. From 1990 to 2022, the number of published articles showed exponential growth of y = 4.1374e0.1294x, with an average of 17.9 articles per year. The top country and institutions were the United States and the University of California Davis, accounting for 44.52 and 5.32% of the total studies, respectively. The most productive journal was Neurology, and the most co-cited journal was Lancet Neurology. Decarli C was the most productive author. The current research frontier trend focuses on the association between small vessel disease and AD, the clinical application and exploration of diffusion MRI, and related markers. Conclusion This study provides an in-depth overview of publications on MRI of WM in AD, identifying the current research status, hotspots, and frontier trends in the field.
Collapse
Affiliation(s)
- Jin-huan Yue
- Department of Tuina, Acupuncture and Moxibustion, Shenzhen Jiuwei Chinese Medicine Clinic, Shenzhen, China
| | - Qin-hong Zhang
- Department of Tuina, Acupuncture and Moxibustion, Shenzhen Jiuwei Chinese Medicine Clinic, Shenzhen, China
| | - Xu Yang
- Graduate School of Heilongjiang University of Chinese Medicine, Harbin, China
| | - Peng Wang
- Department of Oncology, First Affiliated Hospital of Heilongjiang University of Chinese Medicine, Harbin, China
| | - Xu-Chen Sun
- Graduate School of Heilongjiang University of Chinese Medicine, Harbin, China
| | - Shi-Yan Yan
- International Acupuncture and Moxibustion Innovation Institute, School of Acupuncture-Moxibustion and Tuina, Beijing University of Chinese Medicine, Beijing, China
| | - Ang Li
- Sanofifi-Aventis China Investment Co., Ltd, Beijing, China
| | | | - Dan-Na Cao
- Division of CT and MRI, First Affiliated Hospital of Heilongjiang University of Chinese Medicine, Harbin, China
| | - Yang Wang
- Division of CT and MRI, First Affiliated Hospital of Heilongjiang University of Chinese Medicine, Harbin, China
| | - Ze-Yi Wei
- Graduate School of Heilongjiang University of Chinese Medicine, Harbin, China
| | - Xiao-Ling Li
- Division of CT and MRI, First Affiliated Hospital of Heilongjiang University of Chinese Medicine, Harbin, China
| | - Lu-Wen Zhu
- Department of Rehabilitation, Second Affiliated Hospital of Heilongjiang University of Chinese Medicine, Harbin, China
| | - Guanhu Yang
- Department of Specialty Medicine, Ohio University, Athens, OH, United States
| | | |
Collapse
|
4
|
Woldstad C, Rusinek H, Sweeney E, Butler T, Li Y, Tanzi E, Mardy C, Harvey P, de Leon MJ, Glodzik L. Quadratic relationship between systolic blood pressure and white matter lesions in individuals with hypertension. J Hypertens 2023; 41:35-43. [PMID: 36204999 PMCID: PMC9794123 DOI: 10.1097/hjh.0000000000003292] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2022] [Revised: 07/07/2022] [Accepted: 07/12/2022] [Indexed: 02/01/2023]
Abstract
BACKGROUND There is a well documented relationship between cardiovascular risk factors and the development of brain injury, which can lead to cognitive dysfunction. Hypertension (HTN) is a condition increasing the risk of silent and symptomatic ischemic brain lesions. Although benefits of hypertension treatment are indisputable, the target blood pressure value where the possibility of tissue damage is most reduced remains under debate. METHOD Our group performed a cross-sectional ( n = 376) and longitudinal ( n = 188) study of individuals without dementia or stroke (60% women n = 228, age 68.5 ± 7.4 years; men n = 148, age 70.7 ± 6.9 years). Participants were split into hypertensive ( n = 169) and normotensive ( n = 207) groups. MR images were obtained on a 3T system. Linear modeling was performed in hypertensive and normotensive cohorts to investigate the relationship between systolic (SBP) and diastolic (DBP) blood pressure, white matter lesion (WML), and brain volumes. RESULTS Participants in the hypertensive cohort showed a quadratic relationship between SBP and WML, with the lowest amounts of WML being measured in participants with readings at approximately 124 mmHg. Additionally, the hypertensive cohort also exhibited a quadratic relationship between DBP and mean hippocampal volume; participants with readings at approximately 77 mmHg showing the largest volumes. Longitudinally, all groups experienced WML growth, despite different BP trajectories, further suggesting that WML expansion may occur despite or because of BP reduction in individuals with compromised vascular system. CONCLUSION Overall, our study suggests that in the hypertensive group there is a valley of mid-range blood pressures displaying less pathology in the brain.
Collapse
Affiliation(s)
| | | | - Elizabeth Sweeney
- Division of Biostatistics, Department of Population Health Sciences, Weill Cornell Medicine
| | - Tracy Butler
- Brain Health Imaging Institute, Department of Radiology, Weill Cornell Medicine
| | - Yi Li
- Brain Health Imaging Institute, Department of Radiology, Weill Cornell Medicine
| | - Emily Tanzi
- Brain Health Imaging Institute, Department of Radiology, Weill Cornell Medicine
| | - Christopher Mardy
- Brain Health Imaging Institute, Department of Radiology, Weill Cornell Medicine
| | - Patrick Harvey
- Brain Health Imaging Institute, Department of Radiology, Weill Cornell Medicine
| | - Mony J. de Leon
- Brain Health Imaging Institute, Department of Radiology, Weill Cornell Medicine
| | - Lidia Glodzik
- Brain Health Imaging Institute, Department of Radiology, Weill Cornell Medicine
- Department of Psychiatry, NYU School of Medicine, New York, NY, USA
| |
Collapse
|
5
|
Keuss SE, Coath W, Nicholas JM, Poole T, Barnes J, Cash DM, Lane CA, Parker TD, Keshavan A, Buchanan SM, Wagen AZ, Storey M, Harris M, Malone IB, Sudre CH, Lu K, James SN, Street R, Thomas DL, Dickson JC, Murray-Smith H, Wong A, Freiberger T, Crutch S, Richards M, Fox NC, Schott JM. Associations of β-Amyloid and Vascular Burden With Rates of Neurodegeneration in Cognitively Normal Members of the 1946 British Birth Cohort. Neurology 2022; 99:e129-e141. [PMID: 35410910 PMCID: PMC9280996 DOI: 10.1212/wnl.0000000000200524] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2021] [Accepted: 03/01/2022] [Indexed: 11/28/2022] Open
Abstract
BACKGROUND AND OBJECTIVES The goals of this work were to quantify the independent and interactive associations of β-amyloid (Aβ) and white matter hyperintensity volume (WMHV), a marker of presumed cerebrovascular disease (CVD), with rates of neurodegeneration and to examine the contributions of APOE ε4 and vascular risk measured at different stages of adulthood in cognitively normal members of the 1946 British Birth Cohort. METHODS Participants underwent brain MRI and florbetapir-Aβ PET as part of Insight 46, an observational population-based study. Changes in whole-brain, ventricular, and hippocampal volume were directly measured from baseline and repeat volumetric T1 MRI with the boundary shift integral. Linear regression was used to test associations with baseline Aβ deposition, baseline WMHV, APOE ε4, and office-based Framingham Heart Study Cardiovascular Risk Score (FHS-CVS) and systolic blood pressure (BP) at ages 36, 53, and 69 years. RESULTS Three hundred forty-six cognitively normal participants (mean [SD] age at baseline scan 70.5 [0.6] years; 48% female) had high-quality T1 MRI data from both time points (mean [SD] scan interval 2.4 [0.2] years). Being Aβ positive at baseline was associated with 0.87-mL/y faster whole-brain atrophy (95% CI 0.03, 1.72), 0.39-mL/y greater ventricular expansion (95% CI 0.16, 0.64), and 0.016-mL/y faster hippocampal atrophy (95% CI 0.004, 0.027), while each 10-mL additional WMHV at baseline was associated with 1.07-mL/y faster whole-brain atrophy (95% CI 0.47, 1.67), 0.31-mL/y greater ventricular expansion (95% CI 0.13, 0.60), and 0.014-mL/y faster hippocampal atrophy (95% CI 0.006, 0.022). These contributions were independent, and there was no evidence that Aβ and WMHV interacted in their effects. There were no independent associations of APOE ε4 with rates of neurodegeneration after adjustment for Aβ status and WMHV, no clear relationships between FHS-CVS or systolic BP and rates of neurodegeneration when assessed across the whole sample, and no evidence that FHS-CVS or systolic BP acted synergistically with Aβ. DISCUSSION Aβ and presumed CVD have distinct and additive effects on rates of neurodegeneration in cognitively normal elderly. These findings have implications for the use of MRI measures as biomarkers of neurodegeneration and emphasize the importance of risk management and early intervention targeting both pathways.
Collapse
Affiliation(s)
- Sarah E Keuss
- From the Dementia Research Centre (S.E.K., W.C., J.M.N., T.P., J.B., D.M.C., C.A.L., A.K. S.M.B., A.Z.W., M.S., M.H., I.B.M., C.H.S., K.L., R.S., H.M.-S, T.F., S.C., N.C.F., J.M.S.), Dementia Research Institute (D.M.C., N.C.F.), Leonard Wolfson Experimental Neurology Centre (D.L.T.), and Department of Brain Repair and Neurorehabilitation (D.L.T.), UCL Queen Square Institute of Neurology; Department of Medical Statistics (J.M.N., T.P.), London School of Hygiene and Tropical Medicine; 4. Department of Medicine (T.D.P.), Division of Brain Sciences, Imperial College London; MRC Unit for Lifelong Health and Ageing at UCL (C.H.S., S.-N.J., A.W., M.R.); Centre for Medical Image Computing (C.H.S.), University College London; School of Biomedical Engineering & Imaging Sciences (C.H.S.), King's College London; and Institute of Nuclear Medicine (J.C.D.), University College London Hospitals, UK
| | - William Coath
- From the Dementia Research Centre (S.E.K., W.C., J.M.N., T.P., J.B., D.M.C., C.A.L., A.K. S.M.B., A.Z.W., M.S., M.H., I.B.M., C.H.S., K.L., R.S., H.M.-S, T.F., S.C., N.C.F., J.M.S.), Dementia Research Institute (D.M.C., N.C.F.), Leonard Wolfson Experimental Neurology Centre (D.L.T.), and Department of Brain Repair and Neurorehabilitation (D.L.T.), UCL Queen Square Institute of Neurology; Department of Medical Statistics (J.M.N., T.P.), London School of Hygiene and Tropical Medicine; 4. Department of Medicine (T.D.P.), Division of Brain Sciences, Imperial College London; MRC Unit for Lifelong Health and Ageing at UCL (C.H.S., S.-N.J., A.W., M.R.); Centre for Medical Image Computing (C.H.S.), University College London; School of Biomedical Engineering & Imaging Sciences (C.H.S.), King's College London; and Institute of Nuclear Medicine (J.C.D.), University College London Hospitals, UK
| | - Jennifer M Nicholas
- From the Dementia Research Centre (S.E.K., W.C., J.M.N., T.P., J.B., D.M.C., C.A.L., A.K. S.M.B., A.Z.W., M.S., M.H., I.B.M., C.H.S., K.L., R.S., H.M.-S, T.F., S.C., N.C.F., J.M.S.), Dementia Research Institute (D.M.C., N.C.F.), Leonard Wolfson Experimental Neurology Centre (D.L.T.), and Department of Brain Repair and Neurorehabilitation (D.L.T.), UCL Queen Square Institute of Neurology; Department of Medical Statistics (J.M.N., T.P.), London School of Hygiene and Tropical Medicine; 4. Department of Medicine (T.D.P.), Division of Brain Sciences, Imperial College London; MRC Unit for Lifelong Health and Ageing at UCL (C.H.S., S.-N.J., A.W., M.R.); Centre for Medical Image Computing (C.H.S.), University College London; School of Biomedical Engineering & Imaging Sciences (C.H.S.), King's College London; and Institute of Nuclear Medicine (J.C.D.), University College London Hospitals, UK
| | - Teresa Poole
- From the Dementia Research Centre (S.E.K., W.C., J.M.N., T.P., J.B., D.M.C., C.A.L., A.K. S.M.B., A.Z.W., M.S., M.H., I.B.M., C.H.S., K.L., R.S., H.M.-S, T.F., S.C., N.C.F., J.M.S.), Dementia Research Institute (D.M.C., N.C.F.), Leonard Wolfson Experimental Neurology Centre (D.L.T.), and Department of Brain Repair and Neurorehabilitation (D.L.T.), UCL Queen Square Institute of Neurology; Department of Medical Statistics (J.M.N., T.P.), London School of Hygiene and Tropical Medicine; 4. Department of Medicine (T.D.P.), Division of Brain Sciences, Imperial College London; MRC Unit for Lifelong Health and Ageing at UCL (C.H.S., S.-N.J., A.W., M.R.); Centre for Medical Image Computing (C.H.S.), University College London; School of Biomedical Engineering & Imaging Sciences (C.H.S.), King's College London; and Institute of Nuclear Medicine (J.C.D.), University College London Hospitals, UK
| | - Josephine Barnes
- From the Dementia Research Centre (S.E.K., W.C., J.M.N., T.P., J.B., D.M.C., C.A.L., A.K. S.M.B., A.Z.W., M.S., M.H., I.B.M., C.H.S., K.L., R.S., H.M.-S, T.F., S.C., N.C.F., J.M.S.), Dementia Research Institute (D.M.C., N.C.F.), Leonard Wolfson Experimental Neurology Centre (D.L.T.), and Department of Brain Repair and Neurorehabilitation (D.L.T.), UCL Queen Square Institute of Neurology; Department of Medical Statistics (J.M.N., T.P.), London School of Hygiene and Tropical Medicine; 4. Department of Medicine (T.D.P.), Division of Brain Sciences, Imperial College London; MRC Unit for Lifelong Health and Ageing at UCL (C.H.S., S.-N.J., A.W., M.R.); Centre for Medical Image Computing (C.H.S.), University College London; School of Biomedical Engineering & Imaging Sciences (C.H.S.), King's College London; and Institute of Nuclear Medicine (J.C.D.), University College London Hospitals, UK
| | - David M Cash
- From the Dementia Research Centre (S.E.K., W.C., J.M.N., T.P., J.B., D.M.C., C.A.L., A.K. S.M.B., A.Z.W., M.S., M.H., I.B.M., C.H.S., K.L., R.S., H.M.-S, T.F., S.C., N.C.F., J.M.S.), Dementia Research Institute (D.M.C., N.C.F.), Leonard Wolfson Experimental Neurology Centre (D.L.T.), and Department of Brain Repair and Neurorehabilitation (D.L.T.), UCL Queen Square Institute of Neurology; Department of Medical Statistics (J.M.N., T.P.), London School of Hygiene and Tropical Medicine; 4. Department of Medicine (T.D.P.), Division of Brain Sciences, Imperial College London; MRC Unit for Lifelong Health and Ageing at UCL (C.H.S., S.-N.J., A.W., M.R.); Centre for Medical Image Computing (C.H.S.), University College London; School of Biomedical Engineering & Imaging Sciences (C.H.S.), King's College London; and Institute of Nuclear Medicine (J.C.D.), University College London Hospitals, UK
| | - Christopher A Lane
- From the Dementia Research Centre (S.E.K., W.C., J.M.N., T.P., J.B., D.M.C., C.A.L., A.K. S.M.B., A.Z.W., M.S., M.H., I.B.M., C.H.S., K.L., R.S., H.M.-S, T.F., S.C., N.C.F., J.M.S.), Dementia Research Institute (D.M.C., N.C.F.), Leonard Wolfson Experimental Neurology Centre (D.L.T.), and Department of Brain Repair and Neurorehabilitation (D.L.T.), UCL Queen Square Institute of Neurology; Department of Medical Statistics (J.M.N., T.P.), London School of Hygiene and Tropical Medicine; 4. Department of Medicine (T.D.P.), Division of Brain Sciences, Imperial College London; MRC Unit for Lifelong Health and Ageing at UCL (C.H.S., S.-N.J., A.W., M.R.); Centre for Medical Image Computing (C.H.S.), University College London; School of Biomedical Engineering & Imaging Sciences (C.H.S.), King's College London; and Institute of Nuclear Medicine (J.C.D.), University College London Hospitals, UK
| | - Thomas D Parker
- From the Dementia Research Centre (S.E.K., W.C., J.M.N., T.P., J.B., D.M.C., C.A.L., A.K. S.M.B., A.Z.W., M.S., M.H., I.B.M., C.H.S., K.L., R.S., H.M.-S, T.F., S.C., N.C.F., J.M.S.), Dementia Research Institute (D.M.C., N.C.F.), Leonard Wolfson Experimental Neurology Centre (D.L.T.), and Department of Brain Repair and Neurorehabilitation (D.L.T.), UCL Queen Square Institute of Neurology; Department of Medical Statistics (J.M.N., T.P.), London School of Hygiene and Tropical Medicine; 4. Department of Medicine (T.D.P.), Division of Brain Sciences, Imperial College London; MRC Unit for Lifelong Health and Ageing at UCL (C.H.S., S.-N.J., A.W., M.R.); Centre for Medical Image Computing (C.H.S.), University College London; School of Biomedical Engineering & Imaging Sciences (C.H.S.), King's College London; and Institute of Nuclear Medicine (J.C.D.), University College London Hospitals, UK
| | - Ashvini Keshavan
- From the Dementia Research Centre (S.E.K., W.C., J.M.N., T.P., J.B., D.M.C., C.A.L., A.K. S.M.B., A.Z.W., M.S., M.H., I.B.M., C.H.S., K.L., R.S., H.M.-S, T.F., S.C., N.C.F., J.M.S.), Dementia Research Institute (D.M.C., N.C.F.), Leonard Wolfson Experimental Neurology Centre (D.L.T.), and Department of Brain Repair and Neurorehabilitation (D.L.T.), UCL Queen Square Institute of Neurology; Department of Medical Statistics (J.M.N., T.P.), London School of Hygiene and Tropical Medicine; 4. Department of Medicine (T.D.P.), Division of Brain Sciences, Imperial College London; MRC Unit for Lifelong Health and Ageing at UCL (C.H.S., S.-N.J., A.W., M.R.); Centre for Medical Image Computing (C.H.S.), University College London; School of Biomedical Engineering & Imaging Sciences (C.H.S.), King's College London; and Institute of Nuclear Medicine (J.C.D.), University College London Hospitals, UK
| | - Sarah M Buchanan
- From the Dementia Research Centre (S.E.K., W.C., J.M.N., T.P., J.B., D.M.C., C.A.L., A.K. S.M.B., A.Z.W., M.S., M.H., I.B.M., C.H.S., K.L., R.S., H.M.-S, T.F., S.C., N.C.F., J.M.S.), Dementia Research Institute (D.M.C., N.C.F.), Leonard Wolfson Experimental Neurology Centre (D.L.T.), and Department of Brain Repair and Neurorehabilitation (D.L.T.), UCL Queen Square Institute of Neurology; Department of Medical Statistics (J.M.N., T.P.), London School of Hygiene and Tropical Medicine; 4. Department of Medicine (T.D.P.), Division of Brain Sciences, Imperial College London; MRC Unit for Lifelong Health and Ageing at UCL (C.H.S., S.-N.J., A.W., M.R.); Centre for Medical Image Computing (C.H.S.), University College London; School of Biomedical Engineering & Imaging Sciences (C.H.S.), King's College London; and Institute of Nuclear Medicine (J.C.D.), University College London Hospitals, UK
| | - Aaron Z Wagen
- From the Dementia Research Centre (S.E.K., W.C., J.M.N., T.P., J.B., D.M.C., C.A.L., A.K. S.M.B., A.Z.W., M.S., M.H., I.B.M., C.H.S., K.L., R.S., H.M.-S, T.F., S.C., N.C.F., J.M.S.), Dementia Research Institute (D.M.C., N.C.F.), Leonard Wolfson Experimental Neurology Centre (D.L.T.), and Department of Brain Repair and Neurorehabilitation (D.L.T.), UCL Queen Square Institute of Neurology; Department of Medical Statistics (J.M.N., T.P.), London School of Hygiene and Tropical Medicine; 4. Department of Medicine (T.D.P.), Division of Brain Sciences, Imperial College London; MRC Unit for Lifelong Health and Ageing at UCL (C.H.S., S.-N.J., A.W., M.R.); Centre for Medical Image Computing (C.H.S.), University College London; School of Biomedical Engineering & Imaging Sciences (C.H.S.), King's College London; and Institute of Nuclear Medicine (J.C.D.), University College London Hospitals, UK
| | - Mathew Storey
- From the Dementia Research Centre (S.E.K., W.C., J.M.N., T.P., J.B., D.M.C., C.A.L., A.K. S.M.B., A.Z.W., M.S., M.H., I.B.M., C.H.S., K.L., R.S., H.M.-S, T.F., S.C., N.C.F., J.M.S.), Dementia Research Institute (D.M.C., N.C.F.), Leonard Wolfson Experimental Neurology Centre (D.L.T.), and Department of Brain Repair and Neurorehabilitation (D.L.T.), UCL Queen Square Institute of Neurology; Department of Medical Statistics (J.M.N., T.P.), London School of Hygiene and Tropical Medicine; 4. Department of Medicine (T.D.P.), Division of Brain Sciences, Imperial College London; MRC Unit for Lifelong Health and Ageing at UCL (C.H.S., S.-N.J., A.W., M.R.); Centre for Medical Image Computing (C.H.S.), University College London; School of Biomedical Engineering & Imaging Sciences (C.H.S.), King's College London; and Institute of Nuclear Medicine (J.C.D.), University College London Hospitals, UK
| | - Matthew Harris
- From the Dementia Research Centre (S.E.K., W.C., J.M.N., T.P., J.B., D.M.C., C.A.L., A.K. S.M.B., A.Z.W., M.S., M.H., I.B.M., C.H.S., K.L., R.S., H.M.-S, T.F., S.C., N.C.F., J.M.S.), Dementia Research Institute (D.M.C., N.C.F.), Leonard Wolfson Experimental Neurology Centre (D.L.T.), and Department of Brain Repair and Neurorehabilitation (D.L.T.), UCL Queen Square Institute of Neurology; Department of Medical Statistics (J.M.N., T.P.), London School of Hygiene and Tropical Medicine; 4. Department of Medicine (T.D.P.), Division of Brain Sciences, Imperial College London; MRC Unit for Lifelong Health and Ageing at UCL (C.H.S., S.-N.J., A.W., M.R.); Centre for Medical Image Computing (C.H.S.), University College London; School of Biomedical Engineering & Imaging Sciences (C.H.S.), King's College London; and Institute of Nuclear Medicine (J.C.D.), University College London Hospitals, UK
| | - Ian B Malone
- From the Dementia Research Centre (S.E.K., W.C., J.M.N., T.P., J.B., D.M.C., C.A.L., A.K. S.M.B., A.Z.W., M.S., M.H., I.B.M., C.H.S., K.L., R.S., H.M.-S, T.F., S.C., N.C.F., J.M.S.), Dementia Research Institute (D.M.C., N.C.F.), Leonard Wolfson Experimental Neurology Centre (D.L.T.), and Department of Brain Repair and Neurorehabilitation (D.L.T.), UCL Queen Square Institute of Neurology; Department of Medical Statistics (J.M.N., T.P.), London School of Hygiene and Tropical Medicine; 4. Department of Medicine (T.D.P.), Division of Brain Sciences, Imperial College London; MRC Unit for Lifelong Health and Ageing at UCL (C.H.S., S.-N.J., A.W., M.R.); Centre for Medical Image Computing (C.H.S.), University College London; School of Biomedical Engineering & Imaging Sciences (C.H.S.), King's College London; and Institute of Nuclear Medicine (J.C.D.), University College London Hospitals, UK
| | - Carole H Sudre
- From the Dementia Research Centre (S.E.K., W.C., J.M.N., T.P., J.B., D.M.C., C.A.L., A.K. S.M.B., A.Z.W., M.S., M.H., I.B.M., C.H.S., K.L., R.S., H.M.-S, T.F., S.C., N.C.F., J.M.S.), Dementia Research Institute (D.M.C., N.C.F.), Leonard Wolfson Experimental Neurology Centre (D.L.T.), and Department of Brain Repair and Neurorehabilitation (D.L.T.), UCL Queen Square Institute of Neurology; Department of Medical Statistics (J.M.N., T.P.), London School of Hygiene and Tropical Medicine; 4. Department of Medicine (T.D.P.), Division of Brain Sciences, Imperial College London; MRC Unit for Lifelong Health and Ageing at UCL (C.H.S., S.-N.J., A.W., M.R.); Centre for Medical Image Computing (C.H.S.), University College London; School of Biomedical Engineering & Imaging Sciences (C.H.S.), King's College London; and Institute of Nuclear Medicine (J.C.D.), University College London Hospitals, UK
| | - Kirsty Lu
- From the Dementia Research Centre (S.E.K., W.C., J.M.N., T.P., J.B., D.M.C., C.A.L., A.K. S.M.B., A.Z.W., M.S., M.H., I.B.M., C.H.S., K.L., R.S., H.M.-S, T.F., S.C., N.C.F., J.M.S.), Dementia Research Institute (D.M.C., N.C.F.), Leonard Wolfson Experimental Neurology Centre (D.L.T.), and Department of Brain Repair and Neurorehabilitation (D.L.T.), UCL Queen Square Institute of Neurology; Department of Medical Statistics (J.M.N., T.P.), London School of Hygiene and Tropical Medicine; 4. Department of Medicine (T.D.P.), Division of Brain Sciences, Imperial College London; MRC Unit for Lifelong Health and Ageing at UCL (C.H.S., S.-N.J., A.W., M.R.); Centre for Medical Image Computing (C.H.S.), University College London; School of Biomedical Engineering & Imaging Sciences (C.H.S.), King's College London; and Institute of Nuclear Medicine (J.C.D.), University College London Hospitals, UK
| | - Sarah-Naomi James
- From the Dementia Research Centre (S.E.K., W.C., J.M.N., T.P., J.B., D.M.C., C.A.L., A.K. S.M.B., A.Z.W., M.S., M.H., I.B.M., C.H.S., K.L., R.S., H.M.-S, T.F., S.C., N.C.F., J.M.S.), Dementia Research Institute (D.M.C., N.C.F.), Leonard Wolfson Experimental Neurology Centre (D.L.T.), and Department of Brain Repair and Neurorehabilitation (D.L.T.), UCL Queen Square Institute of Neurology; Department of Medical Statistics (J.M.N., T.P.), London School of Hygiene and Tropical Medicine; 4. Department of Medicine (T.D.P.), Division of Brain Sciences, Imperial College London; MRC Unit for Lifelong Health and Ageing at UCL (C.H.S., S.-N.J., A.W., M.R.); Centre for Medical Image Computing (C.H.S.), University College London; School of Biomedical Engineering & Imaging Sciences (C.H.S.), King's College London; and Institute of Nuclear Medicine (J.C.D.), University College London Hospitals, UK
| | - Rebecca Street
- From the Dementia Research Centre (S.E.K., W.C., J.M.N., T.P., J.B., D.M.C., C.A.L., A.K. S.M.B., A.Z.W., M.S., M.H., I.B.M., C.H.S., K.L., R.S., H.M.-S, T.F., S.C., N.C.F., J.M.S.), Dementia Research Institute (D.M.C., N.C.F.), Leonard Wolfson Experimental Neurology Centre (D.L.T.), and Department of Brain Repair and Neurorehabilitation (D.L.T.), UCL Queen Square Institute of Neurology; Department of Medical Statistics (J.M.N., T.P.), London School of Hygiene and Tropical Medicine; 4. Department of Medicine (T.D.P.), Division of Brain Sciences, Imperial College London; MRC Unit for Lifelong Health and Ageing at UCL (C.H.S., S.-N.J., A.W., M.R.); Centre for Medical Image Computing (C.H.S.), University College London; School of Biomedical Engineering & Imaging Sciences (C.H.S.), King's College London; and Institute of Nuclear Medicine (J.C.D.), University College London Hospitals, UK
| | - David L Thomas
- From the Dementia Research Centre (S.E.K., W.C., J.M.N., T.P., J.B., D.M.C., C.A.L., A.K. S.M.B., A.Z.W., M.S., M.H., I.B.M., C.H.S., K.L., R.S., H.M.-S, T.F., S.C., N.C.F., J.M.S.), Dementia Research Institute (D.M.C., N.C.F.), Leonard Wolfson Experimental Neurology Centre (D.L.T.), and Department of Brain Repair and Neurorehabilitation (D.L.T.), UCL Queen Square Institute of Neurology; Department of Medical Statistics (J.M.N., T.P.), London School of Hygiene and Tropical Medicine; 4. Department of Medicine (T.D.P.), Division of Brain Sciences, Imperial College London; MRC Unit for Lifelong Health and Ageing at UCL (C.H.S., S.-N.J., A.W., M.R.); Centre for Medical Image Computing (C.H.S.), University College London; School of Biomedical Engineering & Imaging Sciences (C.H.S.), King's College London; and Institute of Nuclear Medicine (J.C.D.), University College London Hospitals, UK
| | - John C Dickson
- From the Dementia Research Centre (S.E.K., W.C., J.M.N., T.P., J.B., D.M.C., C.A.L., A.K. S.M.B., A.Z.W., M.S., M.H., I.B.M., C.H.S., K.L., R.S., H.M.-S, T.F., S.C., N.C.F., J.M.S.), Dementia Research Institute (D.M.C., N.C.F.), Leonard Wolfson Experimental Neurology Centre (D.L.T.), and Department of Brain Repair and Neurorehabilitation (D.L.T.), UCL Queen Square Institute of Neurology; Department of Medical Statistics (J.M.N., T.P.), London School of Hygiene and Tropical Medicine; 4. Department of Medicine (T.D.P.), Division of Brain Sciences, Imperial College London; MRC Unit for Lifelong Health and Ageing at UCL (C.H.S., S.-N.J., A.W., M.R.); Centre for Medical Image Computing (C.H.S.), University College London; School of Biomedical Engineering & Imaging Sciences (C.H.S.), King's College London; and Institute of Nuclear Medicine (J.C.D.), University College London Hospitals, UK
| | - Heidi Murray-Smith
- From the Dementia Research Centre (S.E.K., W.C., J.M.N., T.P., J.B., D.M.C., C.A.L., A.K. S.M.B., A.Z.W., M.S., M.H., I.B.M., C.H.S., K.L., R.S., H.M.-S, T.F., S.C., N.C.F., J.M.S.), Dementia Research Institute (D.M.C., N.C.F.), Leonard Wolfson Experimental Neurology Centre (D.L.T.), and Department of Brain Repair and Neurorehabilitation (D.L.T.), UCL Queen Square Institute of Neurology; Department of Medical Statistics (J.M.N., T.P.), London School of Hygiene and Tropical Medicine; 4. Department of Medicine (T.D.P.), Division of Brain Sciences, Imperial College London; MRC Unit for Lifelong Health and Ageing at UCL (C.H.S., S.-N.J., A.W., M.R.); Centre for Medical Image Computing (C.H.S.), University College London; School of Biomedical Engineering & Imaging Sciences (C.H.S.), King's College London; and Institute of Nuclear Medicine (J.C.D.), University College London Hospitals, UK
| | - Andrew Wong
- From the Dementia Research Centre (S.E.K., W.C., J.M.N., T.P., J.B., D.M.C., C.A.L., A.K. S.M.B., A.Z.W., M.S., M.H., I.B.M., C.H.S., K.L., R.S., H.M.-S, T.F., S.C., N.C.F., J.M.S.), Dementia Research Institute (D.M.C., N.C.F.), Leonard Wolfson Experimental Neurology Centre (D.L.T.), and Department of Brain Repair and Neurorehabilitation (D.L.T.), UCL Queen Square Institute of Neurology; Department of Medical Statistics (J.M.N., T.P.), London School of Hygiene and Tropical Medicine; 4. Department of Medicine (T.D.P.), Division of Brain Sciences, Imperial College London; MRC Unit for Lifelong Health and Ageing at UCL (C.H.S., S.-N.J., A.W., M.R.); Centre for Medical Image Computing (C.H.S.), University College London; School of Biomedical Engineering & Imaging Sciences (C.H.S.), King's College London; and Institute of Nuclear Medicine (J.C.D.), University College London Hospitals, UK
| | - Tamar Freiberger
- From the Dementia Research Centre (S.E.K., W.C., J.M.N., T.P., J.B., D.M.C., C.A.L., A.K. S.M.B., A.Z.W., M.S., M.H., I.B.M., C.H.S., K.L., R.S., H.M.-S, T.F., S.C., N.C.F., J.M.S.), Dementia Research Institute (D.M.C., N.C.F.), Leonard Wolfson Experimental Neurology Centre (D.L.T.), and Department of Brain Repair and Neurorehabilitation (D.L.T.), UCL Queen Square Institute of Neurology; Department of Medical Statistics (J.M.N., T.P.), London School of Hygiene and Tropical Medicine; 4. Department of Medicine (T.D.P.), Division of Brain Sciences, Imperial College London; MRC Unit for Lifelong Health and Ageing at UCL (C.H.S., S.-N.J., A.W., M.R.); Centre for Medical Image Computing (C.H.S.), University College London; School of Biomedical Engineering & Imaging Sciences (C.H.S.), King's College London; and Institute of Nuclear Medicine (J.C.D.), University College London Hospitals, UK
| | - Sebastian Crutch
- From the Dementia Research Centre (S.E.K., W.C., J.M.N., T.P., J.B., D.M.C., C.A.L., A.K. S.M.B., A.Z.W., M.S., M.H., I.B.M., C.H.S., K.L., R.S., H.M.-S, T.F., S.C., N.C.F., J.M.S.), Dementia Research Institute (D.M.C., N.C.F.), Leonard Wolfson Experimental Neurology Centre (D.L.T.), and Department of Brain Repair and Neurorehabilitation (D.L.T.), UCL Queen Square Institute of Neurology; Department of Medical Statistics (J.M.N., T.P.), London School of Hygiene and Tropical Medicine; 4. Department of Medicine (T.D.P.), Division of Brain Sciences, Imperial College London; MRC Unit for Lifelong Health and Ageing at UCL (C.H.S., S.-N.J., A.W., M.R.); Centre for Medical Image Computing (C.H.S.), University College London; School of Biomedical Engineering & Imaging Sciences (C.H.S.), King's College London; and Institute of Nuclear Medicine (J.C.D.), University College London Hospitals, UK
| | - Marcus Richards
- From the Dementia Research Centre (S.E.K., W.C., J.M.N., T.P., J.B., D.M.C., C.A.L., A.K. S.M.B., A.Z.W., M.S., M.H., I.B.M., C.H.S., K.L., R.S., H.M.-S, T.F., S.C., N.C.F., J.M.S.), Dementia Research Institute (D.M.C., N.C.F.), Leonard Wolfson Experimental Neurology Centre (D.L.T.), and Department of Brain Repair and Neurorehabilitation (D.L.T.), UCL Queen Square Institute of Neurology; Department of Medical Statistics (J.M.N., T.P.), London School of Hygiene and Tropical Medicine; 4. Department of Medicine (T.D.P.), Division of Brain Sciences, Imperial College London; MRC Unit for Lifelong Health and Ageing at UCL (C.H.S., S.-N.J., A.W., M.R.); Centre for Medical Image Computing (C.H.S.), University College London; School of Biomedical Engineering & Imaging Sciences (C.H.S.), King's College London; and Institute of Nuclear Medicine (J.C.D.), University College London Hospitals, UK
| | - Nick C Fox
- From the Dementia Research Centre (S.E.K., W.C., J.M.N., T.P., J.B., D.M.C., C.A.L., A.K. S.M.B., A.Z.W., M.S., M.H., I.B.M., C.H.S., K.L., R.S., H.M.-S, T.F., S.C., N.C.F., J.M.S.), Dementia Research Institute (D.M.C., N.C.F.), Leonard Wolfson Experimental Neurology Centre (D.L.T.), and Department of Brain Repair and Neurorehabilitation (D.L.T.), UCL Queen Square Institute of Neurology; Department of Medical Statistics (J.M.N., T.P.), London School of Hygiene and Tropical Medicine; 4. Department of Medicine (T.D.P.), Division of Brain Sciences, Imperial College London; MRC Unit for Lifelong Health and Ageing at UCL (C.H.S., S.-N.J., A.W., M.R.); Centre for Medical Image Computing (C.H.S.), University College London; School of Biomedical Engineering & Imaging Sciences (C.H.S.), King's College London; and Institute of Nuclear Medicine (J.C.D.), University College London Hospitals, UK
| | - Jonathan M Schott
- From the Dementia Research Centre (S.E.K., W.C., J.M.N., T.P., J.B., D.M.C., C.A.L., A.K. S.M.B., A.Z.W., M.S., M.H., I.B.M., C.H.S., K.L., R.S., H.M.-S, T.F., S.C., N.C.F., J.M.S.), Dementia Research Institute (D.M.C., N.C.F.), Leonard Wolfson Experimental Neurology Centre (D.L.T.), and Department of Brain Repair and Neurorehabilitation (D.L.T.), UCL Queen Square Institute of Neurology; Department of Medical Statistics (J.M.N., T.P.), London School of Hygiene and Tropical Medicine; 4. Department of Medicine (T.D.P.), Division of Brain Sciences, Imperial College London; MRC Unit for Lifelong Health and Ageing at UCL (C.H.S., S.-N.J., A.W., M.R.); Centre for Medical Image Computing (C.H.S.), University College London; School of Biomedical Engineering & Imaging Sciences (C.H.S.), King's College London; and Institute of Nuclear Medicine (J.C.D.), University College London Hospitals, UK.
| |
Collapse
|
6
|
Smith NM, Ford JN, Haghdel A, Glodzik L, Li Y, D’Angelo D, RoyChoudhury A, Wang X, Blennow K, de Leon MJ, Ivanidze J. Statistical Parametric Mapping in Amyloid Positron Emission Tomography. Front Aging Neurosci 2022; 14:849932. [PMID: 35547630 PMCID: PMC9083453 DOI: 10.3389/fnagi.2022.849932] [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] [Subscribe] [Scholar Register] [Received: 01/06/2022] [Accepted: 03/21/2022] [Indexed: 12/03/2022] Open
Abstract
Alzheimer's disease (AD), the most common cause of dementia, has limited treatment options. Emerging disease modifying therapies are targeted at clearing amyloid-β (Aβ) aggregates and slowing the rate of amyloid deposition. However, amyloid burden is not routinely evaluated quantitatively for purposes of disease progression and treatment response assessment. Statistical Parametric Mapping (SPM) is a technique comparing single-subject Positron Emission Tomography (PET) to a healthy cohort that may improve quantification of amyloid burden and diagnostic performance. While primarily used in 2-[18F]-fluoro-2-deoxy-D-glucose (FDG)-PET, SPM's utility in amyloid PET for AD diagnosis is less established and uncertainty remains regarding optimal normal database construction. Using commercially available SPM software, we created a database of 34 non-APOE ε4 carriers with normal cognitive testing (MMSE > 25) and negative cerebrospinal fluid (CSF) AD biomarkers. We compared this database to 115 cognitively normal subjects with variable AD risk factors. We hypothesized that SPM based on our database would identify more positive scans in the test cohort than the qualitatively rated [11C]-PiB PET (QR-PiB), that SPM-based interpretation would correlate better with CSF Aβ42 levels than QR-PiB, and that regional z-scores of specific brain regions known to be involved early in AD would be predictive of CSF Aβ42 levels. Fisher's exact test and the kappa coefficient assessed the agreement between SPM, QR-PiB PET, and CSF biomarkers. Logistic regression determined if the regional z-scores predicted CSF Aβ42 levels. An optimal z-score cutoff was calculated using Youden's index. We found SPM identified more positive scans than QR-PiB PET (19.1 vs. 9.6%) and that SPM correlated more closely with CSF Aβ42 levels than QR-PiB PET (kappa 0.13 vs. 0.06) indicating that SPM may have higher sensitivity than standard QR-PiB PET images. Regional analysis demonstrated the z-scores of the precuneus, anterior cingulate and posterior cingulate were predictive of CSF Aβ42 levels [OR (95% CI) 2.4 (1.1, 5.1) p = 0.024; 1.8 (1.1, 2.8) p = 0.020; 1.6 (1.1, 2.5) p = 0.026]. This study demonstrates the utility of using SPM with a "true normal" database and suggests that SPM enhances diagnostic performance in AD in the clinical setting through its quantitative approach, which will be increasingly important with future disease-modifying therapies.
Collapse
Affiliation(s)
- Natasha M. Smith
- Department of Radiology and MD Program, Weill Cornell Medicine, New York City, NY, United States
| | - Jeremy N. Ford
- Department of Radiology, Weill Cornell Medicine, New York City, NY, United States
- Department of Radiology, Massachusetts General Hospital, Boston, MA, United States
| | - Arsalan Haghdel
- Department of Radiology and MD Program, Weill Cornell Medicine, New York City, NY, United States
| | - Lidia Glodzik
- Department of Radiology, Weill Cornell Medicine, New York City, NY, United States
| | - Yi Li
- Department of Radiology, Weill Cornell Medicine, New York City, NY, United States
| | - Debra D’Angelo
- Department of Population Health Sciences, Weill Cornell Medicine, New York City, NY, United States
| | - Arindam RoyChoudhury
- Department of Population Health Sciences, Weill Cornell Medicine, New York City, NY, United States
| | - Xiuyuan Wang
- Department of Radiology, Weill Cornell Medicine, New York City, NY, United States
| | - Kaj Blennow
- Department of Neuroscience and Physiology, University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Mony J. de Leon
- Department of Radiology, Weill Cornell Medicine, New York City, NY, United States
| | - Jana Ivanidze
- Department of Radiology, Weill Cornell Medicine, New York City, NY, United States
| |
Collapse
|
7
|
The Role of Molecular Imaging as a Marker of Remyelination and Repair in Multiple Sclerosis. Int J Mol Sci 2021; 23:ijms23010474. [PMID: 35008899 PMCID: PMC8745199 DOI: 10.3390/ijms23010474] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Revised: 12/26/2021] [Accepted: 12/29/2021] [Indexed: 12/14/2022] Open
Abstract
The appearance of new disease-modifying therapies in multiple sclerosis (MS) has revolutionized our ability to fight inflammatory relapses and has immensely improved patients’ quality of life. Although remarkable, this achievement has not carried over into reducing long-term disability. In MS, clinical disability progression can continue relentlessly irrespective of acute inflammation. This “silent” disease progression is the main contributor to long-term clinical disability in MS and results from chronic inflammation, neurodegeneration, and repair failure. Investigating silent disease progression and its underlying mechanisms is a challenge. Standard MRI excels in depicting acute inflammation but lacks the pathophysiological lens required for a more targeted exploration of molecular-based processes. Novel modalities that utilize nuclear magnetic resonance’s ability to display in vivo information on imaging look to bridge this gap. Displaying the CNS through a molecular prism is becoming an undeniable reality. This review will focus on “molecular imaging biomarkers” of disease progression, modalities that can harmoniously depict anatomy and pathophysiology, making them attractive candidates to become the first valid biomarkers of neuroprotection and remyelination.
Collapse
|
8
|
Seixas AA, Turner AD, Bubu OM, Jean-Louis G, de Leon MJ, Osorio RS, Glodzik L. Obesity and Race May Explain Differential Burden of White Matter Hyperintensity Load. Clin Interv Aging 2021; 16:1563-1571. [PMID: 34465985 PMCID: PMC8402977 DOI: 10.2147/cia.s316064] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2021] [Accepted: 06/10/2021] [Indexed: 11/23/2022] Open
Abstract
OBJECTIVE Compared to European Americans, research indicates that African Americans have higher white matter hyperintensity (WMH) load; however, the clinical and biological bases underlying this higher burden are poorly understood. We hypothesize that obesity may explain differences in WMH between African and European Americans. METHODS Participants enrolled in longitudinal brain aging studies (n=292; 61% Female; 92% European American; mean age=69.6±7.7) completed evaluations including medical exams, neuroimaging, and sociodemographic surveys. Overweight/obese status defined as body mass index ≥30 kg/m2, and WMH load, captured by FLAIR images, as sum of deep and periventricular volumes, scored using the Fazekas scale (0-6), WMH≥4 considered high. RESULTS Logistic regression analyses, adjusted for age, sex, hypertension, and smoking history, indicated that age and interaction between race and obesity were significant predictors of WMH, demonstrating that obesity significantly moderated the relationship between race and WMH. Age independently increased the odds of high WMH by 16% (OR=1.16, 95% CI=1.09-1.23, p<0.001). Stratified analysis indicates that older European Americans had increased WMH (OR=1.17, 95% CI=1.09-1.23, p<0.001), while obese African Americans had increased WMH (OR=27.65, 95% CI=1.47-519.13, p<0.05). In a case controlled subgroup matched by age, sex, and education (n=48), African Americans had significantly higher WMH load (27% vs 4%, Χ 2=5.3, p=0.02). CONCLUSION Results denote that age predicted WMH among European Americans, while obesity predicted WMH among African Americans. Matched sample analyses indicate that obesity increases the odds of WMH, though more pronounced in African Americans. These findings suggest that obesity may explain the differential burden of white matter hyperintensity load, signifying public health and clinical importance.
Collapse
Grants
- R01 AG013616 NIA NIH HHS
- RF1 AG057570 NIA NIH HHS
- K23 AG068534 NIA NIH HHS
- L30 AG064670 NIA NIH HHS
- R01 HL142066 NHLBI NIH HHS
- R01 AG022374 NIA NIH HHS
- R01 HL111724 NHLBI NIH HHS
- R56 AG058913 NIA NIH HHS
- R01 NS104364 NINDS NIH HHS
- R01 AG067523 NIA NIH HHS
- R25 HL105444 NHLBI NIH HHS
- P30 AG066512 NIA NIH HHS
- K01 HL135452 NHLBI NIH HHS
- R01 HL152453 NHLBI NIH HHS
- R01 MD007716 NIMHD NIH HHS
- R01 AG012101 NIA NIH HHS
- R01 AG056031 NIA NIH HHS
- K07 AG052685 NIA NIH HHS
- the National Institutes of Health: K01HL135452, K07AG052685, R01HL152453, R01MD007716, R01HL142066, R01AG067523, R01AG056031, R01NS104364, MdeL (RF1AG057570, R56 AG058913, R01 AG012101, R01 AG022374, R01 AG013616), R01 HL111724, R01AG05653, R01AG056031, and R25HL105444
Collapse
Affiliation(s)
- Azizi A Seixas
- New York University Grossman School of Medicine, Department of Population Health, New York, NY, 10016, USA
- New York University Grossman School of Medicine, Department of Psychiatry, New York, NY, 10016, USA
| | - Arlener D Turner
- New York University Grossman School of Medicine, Department of Psychiatry, New York, NY, 10016, USA
| | - Omonigho Michael Bubu
- New York University Grossman School of Medicine, Department of Population Health, New York, NY, 10016, USA
- New York University Grossman School of Medicine, Department of Psychiatry, New York, NY, 10016, USA
| | - Girardin Jean-Louis
- New York University Grossman School of Medicine, Department of Population Health, New York, NY, 10016, USA
- New York University Grossman School of Medicine, Department of Psychiatry, New York, NY, 10016, USA
| | - Mony J de Leon
- Weill Cornell Medicine, Department of Radiology, New York, NY, 10021, USA
| | - Ricardo S Osorio
- New York University Grossman School of Medicine, Department of Psychiatry, New York, NY, 10016, USA
| | - Lidia Glodzik
- Weill Cornell Medicine, Department of Radiology, New York, NY, 10021, USA
| |
Collapse
|
9
|
Zhang M, Ni Y, Zhou Q, He L, Meng H, Gao Y, Huang X, Meng H, Li P, Chen M, Wang D, Hu J, Huang Q, Li Y, Chauveau F, Li B, Chen S. 18F-florbetapir PET/MRI for quantitatively monitoring myelin loss and recovery in patients with multiple sclerosis: A longitudinal study. EClinicalMedicine 2021; 37:100982. [PMID: 34195586 PMCID: PMC8234356 DOI: 10.1016/j.eclinm.2021.100982] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/26/2020] [Revised: 05/19/2021] [Accepted: 06/02/2021] [Indexed: 11/29/2022] Open
Abstract
BACKGROUND Amyloid positron emission tomography (PET) can measure in-vivo demyelination in patients with multiple sclerosis (MS). However, the value of 18F-labeled amyloid PET tracer, 18F-florbetapir in the longitudinal study for monitoring myelin loss and recovery has not been confirmed. METHODS From March 2019 to September 2020, twenty-three patients with MS and nine healthy controls (HCs) underwent a hybrid PET/MRI at baseline and expanded disability status scale (EDSS) assessment, and eight of 23 patients further underwent follow-up PET/MRI. The distribution volume ratio (DVR) and standard uptake value ratio (SUVR) of 18F-florbetapir in damaged white matter (DWM) and normal-appearance white matter (NAWM) were obtained from dynamic and static PET acquisition. Diffusion tensor imaging-derived parameters were also calculated. Data were expressed as mean ± standard deviation with 99% confidence interval (99%CI). FINDING The mean DVR (1.08 ± 0.12, 99%CI [1.02 ~ 1.14]) but not the mean SUVR of DWM lesions was lower than that of NAWM in patients with MS (1.25 ± 0.10, 99%CI [1.20 ~ 1.31]) and HCs (1.29 ± 0.08, 99%CI [1.23 ~ 1.36]). A trend toward lower mean fractional anisotropy (374.95 ± 45.30 vs. 419.07 ± 4.83) and higher mean radial diffusivity (0.45 ± 0.05 vs. 0.40 ± 0.01) of NAWM in patients with MS than those in HCs was found. DVR decreased in DWM lesions with higher MD (rho = -0.261, 99%CI [-0.362 ~ -0.144]), higher AD (rho = -0.200, 99%CI [-0.318 ~ -0.070]) and higher RD (rho = -0.198, 99%CI [-0.313 ~ -0.075]). Patients' EDSS scores were reduced (B = 0.04, 99%CI [-0.005 ~ 0.084]) with decreased index of global demyelination in the longitudinal study. INTERPRETATION Our exploratory study suggests that dynamic 18F-florbetapir PET/MRI may be a very promising tool for quantitatively monitoring myelin loss and recovery in patients with MS. FUNDING Shanghai Pujiang Program, Shanghai Municipal Key Clinical Specialty, Shanghai Shuguang Plan Project, Shanghai Health and Family Planning Commission Research Project, Clinical Research Plan of SHDC, French-Chinese program "Xu Guangqi".
Collapse
Affiliation(s)
- Min Zhang
- Department of Nuclear Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - You Ni
- Department of Neurology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 197 Ruijin 2nd Road, Shanghai 200025, China
| | - Qinming Zhou
- Department of Neurology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 197 Ruijin 2nd Road, Shanghai 200025, China
| | - Lu He
- Department of Neurology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 197 Ruijin 2nd Road, Shanghai 200025, China
| | - Huanyu Meng
- Department of Neurology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 197 Ruijin 2nd Road, Shanghai 200025, China
| | - Yining Gao
- Department of Neurology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 197 Ruijin 2nd Road, Shanghai 200025, China
| | - Xinyun Huang
- Department of Nuclear Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Hongping Meng
- Department of Nuclear Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Peihan Li
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Meidi Chen
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Danni Wang
- Institute for Medical Imaging Technology, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Jingyi Hu
- Institute for Medical Imaging Technology, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Qiu Huang
- Department of Nuclear Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Yao Li
- Department of Nuclear Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Institute for Medical Imaging Technology, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Fabien Chauveau
- Univ Lyon, Lyon Neuroscience research Center, CNRS UMR5292, INSERM U1028, Univ Lyon 1, Lyon, France
| | - Biao Li
- Department of Nuclear Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Sheng Chen
- Department of Neurology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 197 Ruijin 2nd Road, Shanghai 200025, China
| |
Collapse
|
10
|
Reduced [ 18F]flortaucipir retention in white matter hyperintensities compared to normal-appearing white matter. Eur J Nucl Med Mol Imaging 2021; 48:2283-2294. [PMID: 33475761 DOI: 10.1007/s00259-021-05195-5] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2020] [Accepted: 01/04/2021] [Indexed: 01/18/2023]
Abstract
PURPOSE Recent research has suggested the use of white matter (WM) reference regions for longitudinal tau-PET imaging. However, tau tracers display affinity for the β-sheet structure formed by myelin, and thus WM lesions might influence tracer retention. Here, we explored whether the tau-sensitive tracer [18F]flortaucipir shows reduced retention in WM hyperintensities (WMH) and how this retention changes over time. METHODS We included 707 participants from the Alzheimer's Disease Neuroimaging Initiative with available [18F]flortaucipir-PET and structural and FLAIR MRI scans. WM segments and WMH were automatically delineated in the structural MRI and FLAIR scans, respectively. [18F]flortaucipir standardized uptake value ratios (SUVR) of WMH and normal-appearing WM (NAWM) were calculated using the inferior cerebellar grey matter as reference region, and a 3-mm erosion was applied to the combined NAWM and WMH masks to avoid partial volume effects. Longitudinal [18F]flortaucipir SUVR changes in NAWM and WMH were estimated using linear mixed models. The percent variance of WM-referenced cortical [18F]flortaucipir SUVRs explained by longitudinal changes in the WM reference region was estimated with the R2 coefficient. RESULTS Compared to NAWM, WMH areas displayed significantly reduced [18F]flortaucipir SUVR, independent of cognitive impairment or Aβ status (mean difference = 0.14 SUVR, p < 0.001). Older age was associated with lower [18F]flortaucipir SUVR in both NAWM (- 0.002 SUVR/year, p = 0.005) and WMH (- 0.004 SUVR/year, p < 0.001). Longitudinally, [18F]flortaucipir SUVR decreased in NAWM (- 0.008 SUVR/year, p = 0.03) and even more so in WMH (- 0.02 SUVR/year, p < 0.001). Between 17% and 66% of the variance of longitudinal changes in cortical WM-referenced [18F]flortaucipir SUVRs were explained by longitudinal changes in the reference region. CONCLUSIONS [18F]flortaucipir retention in the WM decreases over time and is influenced by the presence of WMH, supporting the hypothesis that [18F]flortaucipir retention in the WM is partially myelin-dependent. These findings have implications for the use of WM reference regions for [18F]flortaucipir-PET imaging.
Collapse
|
11
|
White matter hyperintensities are associated with subthreshold amyloid accumulation. Neuroimage 2020; 218:116944. [PMID: 32445880 DOI: 10.1016/j.neuroimage.2020.116944] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2020] [Revised: 04/30/2020] [Accepted: 05/11/2020] [Indexed: 11/20/2022] Open
Abstract
The association between white matter hyperintensities (WMH) and amyloid accumulation over time in cognitively normal, amyloid-negative elderly people remains largely unexplored. In order to study whether baseline WMH were associated with longitudinal subthreshold amyloid accumulation, 159 cognitively normal participants from the Alzheimer's Disease Neuroimaging Initiative who were amyloid-negative at baseline were examined. All the participants underwent a T1 and a Fluid-Attenuated Inversion Recovery MRI scan at baseline. Amyloid PET imaging was performed at baseline and follow-up visits in 2-year intervals for up to 8 years. Partial volume correction was applied for quantifying cortical Standardised Uptake Value Ratios (SUVR). The associations between global and regional WMH burden and amyloid accumulation were assessed using linear mixed models adjusted by demographic characteristics and baseline SUVR. Partial volume correction increased the measured annual rate of change (+2.4%) compared to that obtained from non-corrected data (+0.5%). There were no significant correlations between baseline WMHs and baseline subthreshold cortical amyloid uptake. In a longitudinal analysis, increased baseline cortical SUVR and increased baseline burden of global (p = 0.006), frontal (p = 0.006), and parietal WMH (p = 0.003) were associated with faster amyloid accumulation. WMH-related amyloid accumulation occurred in parietal, frontal, and, to a lesser extent, cingulate cortices. These results remained unchanged after a sensitivity analysis excluding participants with the highest cortical SUVRs. This is the first study to identify a specific spatial distribution of WMH which is associated with future amyloid accumulation in cognitively normal elderly subjects without PET-detectable amyloid pathology. These findings may have important implications in prevention trials for the early identification of amyloid accumulation.
Collapse
|
12
|
The impact of supine hypertension on target organ damage and survival in patients with synucleinopathies and neurogenic orthostatic hypotension. Parkinsonism Relat Disord 2020; 75:97-104. [PMID: 32516630 DOI: 10.1016/j.parkreldis.2020.04.011] [Citation(s) in RCA: 35] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/26/2019] [Revised: 03/27/2020] [Accepted: 04/19/2020] [Indexed: 12/30/2022]
Abstract
INTRODUCTION In addition to neurogenic orthostatic hypotension (nOH), patients with synucleinopathies frequently have hypertension when supine. The long-term consequences of both abnormalities are difficult to disentangle. We aimed to determine if supine hypertension is associated with target organ damage and worse survival in patients with nOH. METHODS Patients with nOH due to multiple system atrophy (MSA), Parkinson disease (PD), or pure autonomic failure (PAF) were classified into those with or without supine hypertension (systolic BP of at least 140 mmHg or diastolic BP of at least 90 mmHg). Organ damage was assessed by measuring cerebral white matter hyperintensities (WMH), left ventricular hypertrophy (LVH), and renal function. We prospectively followed patients for 30 months (range: 12-66 months) and recorded incident cardiovascular events and all-cause mortality. RESULTS Fifty-seven patients (35 with probable MSA, 14 with PD and 8 with PAF) completed all evaluations. In addition to nOH (average fall 35 ± 21/17 ± 14 mmHg, systolic/diastolic, mean ± SD), 38 patients (67%) had supine hypertension (systolic BP > 140 mmHg). Compared to those without hypertension, patients with hypertension had higher blood urea nitrogen levels (P = 0.005), lower estimated glomerular filtration rate (P = 0.008), higher prevalence of LVH (P = 0.040), and higher WMH volume (P = 0.019). Longitudinal follow-up of patients for over 2 years (27.1 ± 14.5 months) showed that supine hypertension was independently associated with earlier incidence of cardiovascular events and death (HR = 0.25; P = 0.039). CONCLUSIONS Supine hypertension in patients with nOH was associated with an increased risk for target organ damage, cardiovascular events, and premature death. Defining management strategies and safe blood pressure ranges in patients with nOH remains an important research question.
Collapse
|
13
|
de Paula Faria D. Myelin positron emission tomography (PET) imaging in multiple sclerosis. Neural Regen Res 2020; 15:1842-1843. [PMID: 32246627 PMCID: PMC7513961 DOI: 10.4103/1673-5374.280311] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
|
14
|
Tanaka T, Stephenson MC, Nai YH, Khor D, Saridin FN, Hilal S, Villaraza S, Gyanwali B, Ihara M, Vrooman H, Weekes AA, Totman JJ, Robins EG, Chen CP, Reilhac A. Improved quantification of amyloid burden and associated biomarker cut-off points: results from the first amyloid Singaporean cohort with overlapping cerebrovascular disease. Eur J Nucl Med Mol Imaging 2019; 47:319-331. [PMID: 31863136 DOI: 10.1007/s00259-019-04642-8] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2019] [Accepted: 11/26/2019] [Indexed: 12/19/2022]
Abstract
PURPOSE The analysis of the [11C]PiB-PET amyloid images of a unique Asian cohort of 186 participants featuring overlapping vascular diseases raised the question about the validity of current standards for amyloid quantification under abnormal conditions. In this work, we implemented a novel pipeline for improved amyloid PET quantification of this atypical cohort. METHODS The investigated data correction and amyloid quantification methods included motion correction, standardized uptake value ratio (SUVr) quantification using the parcellated MRI (standard method) and SUVr quantification without MRI. We introduced a novel amyloid analysis method yielding 2 biomarkers: AβL which quantifies the global Aβ burden and ns that characterizes the non-specific uptake. Cut-off points were first determined using visual assessment as ground truth and then using unsupervised classification techniques. RESULTS Subject's motion impacts the accuracy of the measurement outcome but has however a limited effect on the visual rating and cut-off point determination. SUVr computation can be reliably performed for all the subjects without MRI parcellation while, when required, the parcellation failed or was of mediocre quality in 10% of the cases. The novel biomarker AβL showed an association increase of 29.5% with the cognitive tests and increased effect size between positive and negative scans compared with SUVr. ns was found sensitive to cerebral microbleeds, white matter hyperintensity, volume, and age. The cut-off points for SUVr using parcellated MRI, SUVr without parcellation, and AβL were 1.56, 1.39, and 25.5. Finally, k-means produced valid cut-off points without the requirement of visual assessment. CONCLUSION The optimal processing for the amyloid quantification of this atypical cohort allows the quantification of all the subjects, producing SUVr values and two novel biomarkers: AβL, showing important increased in their association with various cognitive tests, and ns, a parameter sensitive to non-specific retention variations caused by age and cerebrovascular diseases.
Collapse
Affiliation(s)
- Tomotaka Tanaka
- Clinical Imaging Research Centre, National University of Singapore, 14 Medical Drive, #B1-01, Singapore, 117599, Singapore. .,Department of Pharmacology, Yong Loo Lin School of Medicine, National University of Singapore, Blk MD3, 16 Medical Drive. Level 4, #04-01, Singapore, 117600, Singapore. .,Department of Neurology, National Cerebral and Cardiovascular Center, 5-7-1 Fujishiro-dai, Suita, Osaka, 565-8565, Japan.
| | - Mary C Stephenson
- Clinical Imaging Research Centre, National University of Singapore, 14 Medical Drive, #B1-01, Singapore, 117599, Singapore
| | - Ying-Hwey Nai
- Clinical Imaging Research Centre, National University of Singapore, 14 Medical Drive, #B1-01, Singapore, 117599, Singapore
| | - Damian Khor
- Department of Diagnostic Imaging, National Cancer Institute of Singapore, 11 Hospital Drive, Singapore, 169610, Singapore
| | - Francis N Saridin
- Department of Pharmacology, Yong Loo Lin School of Medicine, National University of Singapore, Blk MD3, 16 Medical Drive. Level 4, #04-01, Singapore, 117600, Singapore
| | - Saima Hilal
- Department of Pharmacology, Yong Loo Lin School of Medicine, National University of Singapore, Blk MD3, 16 Medical Drive. Level 4, #04-01, Singapore, 117600, Singapore.,Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
| | - Steven Villaraza
- Department of Pharmacology, Yong Loo Lin School of Medicine, National University of Singapore, Blk MD3, 16 Medical Drive. Level 4, #04-01, Singapore, 117600, Singapore
| | - Bibek Gyanwali
- Department of Pharmacology, Yong Loo Lin School of Medicine, National University of Singapore, Blk MD3, 16 Medical Drive. Level 4, #04-01, Singapore, 117600, Singapore
| | - Masafumi Ihara
- Department of Neurology, National Cerebral and Cardiovascular Center, 5-7-1 Fujishiro-dai, Suita, Osaka, 565-8565, Japan
| | - Henri Vrooman
- Biomedical Imaging group Rotterdam, Erasmus MC, University Medical Center, P.O. Box 2040, 3000 CA, Rotterdam, Netherlands
| | - Ashley A Weekes
- Clinical Imaging Research Centre, National University of Singapore, 14 Medical Drive, #B1-01, Singapore, 117599, Singapore
| | - John J Totman
- Clinical Imaging Research Centre, National University of Singapore, 14 Medical Drive, #B1-01, Singapore, 117599, Singapore
| | - Edward G Robins
- Clinical Imaging Research Centre, National University of Singapore, 14 Medical Drive, #B1-01, Singapore, 117599, Singapore.,Singapore Bioimaging Consortium, Agency for Science, A*Star,1Fusionopolis way, #20-10 Connexis North Tower, Singapore, 138632, Singapore
| | - Christopher P Chen
- Department of Pharmacology, Yong Loo Lin School of Medicine, National University of Singapore, Blk MD3, 16 Medical Drive. Level 4, #04-01, Singapore, 117600, Singapore
| | - Anthonin Reilhac
- Clinical Imaging Research Centre, National University of Singapore, 14 Medical Drive, #B1-01, Singapore, 117599, Singapore
| |
Collapse
|
15
|
Zhang M, Liu J, Li B, Chen S. 18F-florbetapir PET/MRI for quantitatively monitoring demyelination and remyelination in acute disseminated encephalomyelitis. EJNMMI Res 2019; 9:96. [PMID: 31720882 PMCID: PMC6851275 DOI: 10.1186/s13550-019-0568-8] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2019] [Accepted: 10/16/2019] [Indexed: 01/31/2023] Open
Affiliation(s)
- Min Zhang
- Department of Nuclear Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jun Liu
- Department of Neurology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 197 Ruijin 2nd Road, Shanghai, 200025, China
| | - Biao Li
- Department of Nuclear Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Sheng Chen
- Department of Neurology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 197 Ruijin 2nd Road, Shanghai, 200025, China.
| |
Collapse
|
16
|
Evaluation of Myelin Radiotracers in the Lysolecithin Rat Model of Focal Demyelination: Beware of Pitfalls! CONTRAST MEDIA & MOLECULAR IMAGING 2019; 2019:9294586. [PMID: 31281236 PMCID: PMC6594279 DOI: 10.1155/2019/9294586] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/28/2018] [Revised: 02/06/2019] [Accepted: 02/21/2019] [Indexed: 11/29/2022]
Abstract
The observation that amyloid radiotracers developed for Alzheimer's disease bind to cerebral white matter paved the road to nuclear imaging of myelin in multiple sclerosis. The lysolecithin (lysophosphatidylcholine (LPC)) rat model of demyelination proved useful in evaluating and comparing candidate radiotracers to target myelin. Focal demyelination following stereotaxic LPC injection is larger than lesions observed in experimental autoimmune encephalitis models and is followed by spontaneous progressive remyelination. Moreover, the contralateral hemisphere may serve as an internal control in a given animal. However, demyelination can be accompanied by concurrent focal necrosis and/or adjacent ventricle dilation. The influence of these side effects on imaging findings has never been carefully assessed. The present study describes an optimization of the LPC model and highlights the use of MRI for controlling the variability and pitfalls of the model. The prototypical amyloid radiotracer [11C]PIB was used to show that in vivo PET does not provide sufficient sensitivity to reliably track myelin changes and may be sensitive to LPC side effects instead of demyelination as such. Ex vivo autoradiography with a fluorine radiotracer should be preferred, to adequately evaluate and compare radiotracers for the assessment of myelin content.
Collapse
|
17
|
Kalheim LF, Fladby T, Coello C, Bjørnerud A, Selnes P. [18F]-Flutemetamol Uptake in Cortex and White Matter: Comparison with Cerebrospinal Fluid Biomarkers and [18F]-Fludeoxyglucose. J Alzheimers Dis 2019; 62:1595-1607. [PMID: 29504529 PMCID: PMC6218124 DOI: 10.3233/jad-170582] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
Flutemetamol (18F-Flut) is an [18F]-labelled amyloid PET tracer with increasing availability. The main objectives of this study were to investigate 1) cerebrospinal fluid (CSF) Aβ 1-42 (Aβ42) concentrations associated with regional 18F-Flut uptake, 2) associations between cortical 18F-Flut and [18F]-fludeoxyglucose (18F-FDG)-PET, and 3) the potential use of 18F-Flut in WM pathology. Cognitively impaired, nondemented subjects were recruited (n = 44). CSF was drawn, and 18F-Flut-PET, 18F-FDG-PET, and MRI performed. Our main findings were: 1) Different Alzheimer’s disease predilection areas showed increased 18F-Flut retention at different CSF Aβ42 concentrations (posterior regions were involved at higher concentrations). 2) There were strong negative correlations between regional cortical 18F-Flut and 18F-FDG uptake. 3) Increased 18F-Flut uptake were observed in multiple subcortical regions in amyloid positive subjects, including investigated reference regions. However, WM hyperintensity 18F-Flut standardized uptake value ratios (SUVr) were not significantly different, thus we cannot definitely conclude that the higher uptake in 18F-Flut(+) is due to amyloid deposition. In conclusion, our findings support clinical use of CSF Aβ42, putatively relate decreasing CSF Aβ42 concentrations to a sequence of regional amyloid deposition, and associate amyloid pathology to cortical hypometabolism. However, we cannot conclude that 18F-Flut-PET is a suitable marker for WM pathology due to high aberrant WM uptake.
Collapse
Affiliation(s)
- Lisa Flem Kalheim
- Department of Neurology, Akershus University Hospital, L-renskog, Norway.,Institute of Clinical Medicine, Campus Ahus, University of Oslo, Oslo, Norway
| | - Tormod Fladby
- Department of Neurology, Akershus University Hospital, L-renskog, Norway.,Institute of Clinical Medicine, Campus Ahus, University of Oslo, Oslo, Norway
| | - Christopher Coello
- Preclinical PET/CT, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Atle Bjørnerud
- The Intervention Centre, Oslo University Hospital, Oslo, Norway
| | - Per Selnes
- Department of Neurology, Akershus University Hospital, L-renskog, Norway.,Institute of Clinical Medicine, Campus Ahus, University of Oslo, Oslo, Norway
| |
Collapse
|
18
|
Zeydan B, Schwarz CG, Lowe VJ, Reid RI, Przybelski SA, Lesnick TG, Kremers WK, Senjem ML, Gunter JL, Min H, Vemuri P, Knopman DS, Petersen RC, Jack CR, Kantarci OH, Kantarci K. Investigation of white matter PiB uptake as a marker of white matter integrity. Ann Clin Transl Neurol 2019; 6:678-688. [PMID: 31019992 PMCID: PMC6469255 DOI: 10.1002/acn3.741] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2018] [Revised: 01/14/2019] [Accepted: 02/03/2019] [Indexed: 01/20/2023] Open
Abstract
OBJECTIVE To investigate the associations of Pittsburgh compound-B (PiB) uptake in white matter hyperintensities (WMH) and normal appearing white matter (NAWM) with white matter (WM) integrity measured with DTI and cognitive function in cognitively unimpaired older adults. METHODS Cognitively unimpaired older adults from the population-based Mayo Clinic Study of Aging (n = 537, age 65-95) who underwent both PiB PET and DTI were included. The associations of WM PiB standard uptake value ratio (SUVr) with fractional anisotropy (FA) and mean diffusivity (MD) in the WMH and NAWM were tested after adjusting for age. The associations of PiB SUVr with cognitive function z-scores were tested after adjusting for age and global cortical PiB SUVr. RESULTS The WMH PiB SUVr was lower than NAWM PiB SUVr (P < 0.001). In the WMH, lower PiB SUVr correlated with lower FA (r = 0.21, P < 0.001), and higher MD (r = -0.31, P < 0.001). In the NAWM, lower PiB SUVr only correlated with higher MD (r = -0.10, P = 0.02). Both in the WMH and NAWM, lower PiB SUVr was associated with lower memory, language, and global cognitive function z-scores after adjusting for age and global cortical PiB SUVr. INTERPRETATION Reduced PiB uptake in the WMH is associated with a loss of WM integrity and cognitive function after accounting for the global cortical PiB uptake, suggesting that WM PiB uptake may be an early biomarker of WM integrity that precedes cognitive impairment in older adults. When using WM as a reference region in cross-sectional analysis of PiB SUVr, individual variability in WMH volume as well as age should be considered.
Collapse
Affiliation(s)
- Burcu Zeydan
- Department of RadiologyMayo ClinicRochesterMinnesota
- Department of NeurologyMayo ClinicRochesterMinnesota
- Center for Multiple Sclerosis and Autoimmune NeurologyMayo ClinicRochesterMinnesota
| | | | - Val J. Lowe
- Department of RadiologyMayo ClinicRochesterMinnesota
| | - Robert I. Reid
- Department of Information TechnologyMayo ClinicRochesterMinnesota
| | | | | | | | - Matthew L. Senjem
- Department of RadiologyMayo ClinicRochesterMinnesota
- Department of Information TechnologyMayo ClinicRochesterMinnesota
| | - Jeffrey L. Gunter
- Department of RadiologyMayo ClinicRochesterMinnesota
- Department of Information TechnologyMayo ClinicRochesterMinnesota
| | - Hoon‐Ki Min
- Department of RadiologyMayo ClinicRochesterMinnesota
| | | | | | | | | | - Orhun H. Kantarci
- Department of NeurologyMayo ClinicRochesterMinnesota
- Center for Multiple Sclerosis and Autoimmune NeurologyMayo ClinicRochesterMinnesota
| | | |
Collapse
|
19
|
Pietroboni AM, Carandini T, Colombi A, Mercurio M, Ghezzi L, Giulietti G, Scarioni M, Arighi A, Fenoglio C, De Riz MA, Fumagalli GG, Basilico P, Serpente M, Bozzali M, Scarpini E, Galimberti D, Marotta G. Amyloid PET as a marker of normal-appearing white matter early damage in multiple sclerosis: correlation with CSF β-amyloid levels and brain volumes. Eur J Nucl Med Mol Imaging 2018; 46:280-287. [PMID: 30343433 DOI: 10.1007/s00259-018-4182-1] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2018] [Accepted: 09/25/2018] [Indexed: 12/20/2022]
Abstract
PURPOSE The disease course of multiple sclerosis (MS) is unpredictable, and reliable prognostic biomarkers are needed. Positron emission tomography (PET) with β-amyloid tracers is a promising tool for evaluating white matter (WM) damage and repair. Our aim was to investigate amyloid uptake in damaged (DWM) and normal-appearing WM (NAWM) of MS patients, and to evaluate possible correlations between cerebrospinal fluid (CSF) β-amyloid1-42 (Aβ) levels, amyloid tracer uptake, and brain volumes. METHODS Twelve MS patients were recruited and divided according to their disease activity into active and non-active groups. All participants underwent neurological examination, neuropsychological testing, lumbar puncture, brain magnetic resonance (MRI) imaging, and 18F-florbetapir PET. Aβ levels were determined in CSF samples from all patients. MRI and PET images were co-registered, and mean standardized uptake values (SUV) were calculated for each patient in the NAWM and in the DWM. To calculate brain volumes, brain segmentation was performed using statistical parametric mapping software. Nonparametric statistical analyses for between-group comparisons and regression analyses were conducted. RESULTS We found a lower SUV in DWM compared to NAWM (p < 0.001) in all patients. Decreased NAWM-SUV was observed in the active compared to non-active group (p < 0.05). Considering only active patients, NAWM volume correlated with NAWM-SUV (p = 0.01). Interestingly, CSF Aβ concentration was a predictor of both NAWM-SUV (r = 0.79; p = 0.01) and NAWM volume (r = 0.81, p = 0.01). CONCLUSIONS The correlation between CSF Aβ levels and NAWM-SUV suggests that the predictive role of β-amyloid may be linked to early myelin damage and may reflect disease activity and clinical progression.
Collapse
Affiliation(s)
- Anna M Pietroboni
- Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Via F. Sforza 35, 20122, Milan, Italy. .,University of Milan, Milan, Italy. .,Dino Ferrari Center, Milan, Italy.
| | - Tiziana Carandini
- Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Via F. Sforza 35, 20122, Milan, Italy.,University of Milan, Milan, Italy.,Dino Ferrari Center, Milan, Italy
| | - Annalisa Colombi
- Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Via F. Sforza 35, 20122, Milan, Italy.,University of Milan, Milan, Italy.,Dino Ferrari Center, Milan, Italy
| | - Matteo Mercurio
- Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Via F. Sforza 35, 20122, Milan, Italy
| | - Laura Ghezzi
- Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Via F. Sforza 35, 20122, Milan, Italy.,University of Milan, Milan, Italy.,Dino Ferrari Center, Milan, Italy
| | | | - Marta Scarioni
- Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Via F. Sforza 35, 20122, Milan, Italy.,University of Milan, Milan, Italy.,Dino Ferrari Center, Milan, Italy
| | - Andrea Arighi
- Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Via F. Sforza 35, 20122, Milan, Italy.,University of Milan, Milan, Italy.,Dino Ferrari Center, Milan, Italy
| | | | - Milena A De Riz
- Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Via F. Sforza 35, 20122, Milan, Italy.,University of Milan, Milan, Italy.,Dino Ferrari Center, Milan, Italy
| | - Giorgio G Fumagalli
- Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Via F. Sforza 35, 20122, Milan, Italy.,University of Milan, Milan, Italy.,Dino Ferrari Center, Milan, Italy.,Department of Neurosciences, Psychology, Drug Research and Child Health (NEUROFARBA), University of Florence, Florence, Italy
| | - Paola Basilico
- Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Via F. Sforza 35, 20122, Milan, Italy.,University of Milan, Milan, Italy.,Dino Ferrari Center, Milan, Italy
| | | | - Marco Bozzali
- Neuroimaging Laboratory, IRCCS Santa Lucia Foundation, Rome, Italy.,Department of Neuroscience, Brighton and Sussex Medical School, University of Sussex, Brighton, UK
| | - Elio Scarpini
- Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Via F. Sforza 35, 20122, Milan, Italy.,University of Milan, Milan, Italy.,Dino Ferrari Center, Milan, Italy
| | - Daniela Galimberti
- Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Via F. Sforza 35, 20122, Milan, Italy.,University of Milan, Milan, Italy.,Dino Ferrari Center, Milan, Italy
| | - Giorgio Marotta
- Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Via F. Sforza 35, 20122, Milan, Italy.,University of Milan, Milan, Italy
| |
Collapse
|
20
|
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.
Collapse
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
| | | | | |
Collapse
|
21
|
Landau SM. Optimizing Longitudinal Amyloid-β PET Measurement: The Challenges of Intensity Normalization. J Nucl Med 2018; 59:1581-1582. [PMID: 30213847 DOI: 10.2967/jnumed.118.212662] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2018] [Accepted: 09/10/2018] [Indexed: 11/16/2022] Open
Affiliation(s)
- Susan M Landau
- Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, California; and Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, California
| |
Collapse
|
22
|
Zeydan B, Lowe VJ, Schwarz CG, Przybelski SA, Tosakulwong N, Zuk SM, Senjem ML, Gunter JL, Roberts RO, Mielke MM, Benarroch EE, Rodriguez M, Machulda MM, Lesnick TG, Knopman DS, Petersen RC, Jack CR, Kantarci K, Kantarci OH. Pittsburgh compound-B PET white matter imaging and cognitive function in late multiple sclerosis. Mult Scler 2018; 24:739-749. [PMID: 28474977 PMCID: PMC5665724 DOI: 10.1177/1352458517707346] [Citation(s) in RCA: 30] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
Abstract
BACKGROUND There is growing interest in white matter (WM) imaging with positron emission tomography (PET). OBJECTIVES We studied the association of cognitive function in late multiple sclerosis (MS) with cortical and WM Pittsburgh compound-B PET (PiB-PET) binding. METHODS In the population-based Mayo Clinic Study of Aging, 24 of 4869 participants had MS (12 underwent PiB-PET). Controls were age and sex matched (5:1). We used automated or semi-automated processing for quantitative image analyses and conditional logistic regression for group differences. RESULTS MS patients had lower memory ( p = 0.03) and language ( p = 0.02) performance; smaller thalamic volumes ( p = 0.003); and thinner temporal ( p = 0.001) and frontal ( p = 0.045) cortices on magnetic resonance imaging (MRI) than controls. There was no difference in global cortical PiB standardized uptake value ratios between MS and controls ( p = 0.35). PiB uptake was lower in areas of WM hyperintensities compared to normal-appearing white matter (NAWM) in MS ( p = 0.0002). Reduced PiB uptake in both the areas of WM hyperintensities ( r = 0.65; p = 0.02) and NAWM ( r = 0.69; p = 0.01) was associated with decreased visuospatial performance in MS. CONCLUSION PiB uptake in the cortex in late MS is not different from normal age-matched controls. PiB uptake in the WM in late MS may be a marker of the large network structures' integrity such as those involved in visuospatial performance.
Collapse
Affiliation(s)
- Burcu Zeydan
- Mayo Clinic College of Medicine, Department of Neurology, Rochester, Minnesota, United States of America
- Mayo Clinic College of Medicine, Department of Radiology, Rochester, Minnesota, United States of America
| | - Val J. Lowe
- Mayo Clinic College of Medicine, Department of Radiology, Rochester, Minnesota, United States of America
| | - Christopher G. Schwarz
- Mayo Clinic College of Medicine, Department of Radiology, Rochester, Minnesota, United States of America
| | - Scott A. Przybelski
- Mayo Clinic College of Medicine, Department of Health Sciences Research, Rochester, Minnesota, United States of America
| | - Nirubol Tosakulwong
- Mayo Clinic College of Medicine, Department of Health Sciences Research, Rochester, Minnesota, United States of America
| | - Samantha M. Zuk
- Mayo Clinic College of Medicine, Department of Radiology, Rochester, Minnesota, United States of America
| | - Matthew L. Senjem
- Mayo Clinic College of Medicine, Department of Radiology, Rochester, Minnesota, United States of America
- Mayo Clinic College of Medicine, Department of Information Technology, Rochester, Minnesota, United States of America
| | - Jeffrey L. Gunter
- Mayo Clinic College of Medicine, Department of Information Technology, Rochester, Minnesota, United States of America
| | - Rosebud O. Roberts
- Mayo Clinic College of Medicine, Department of Neurology, Rochester, Minnesota, United States of America
- Mayo Clinic College of Medicine, Department of Health Sciences Research, Rochester, Minnesota, United States of America
| | - Michelle M. Mielke
- Mayo Clinic College of Medicine, Department of Neurology, Rochester, Minnesota, United States of America
- Mayo Clinic College of Medicine, Department of Health Sciences Research, Rochester, Minnesota, United States of America
| | - Eduardo E. Benarroch
- Mayo Clinic College of Medicine, Department of Neurology, Rochester, Minnesota, United States of America
| | - Moses Rodriguez
- Mayo Clinic College of Medicine, Department of Neurology, Rochester, Minnesota, United States of America
| | - Mary M. Machulda
- Mayo Clinic College of Medicine, Department of Psychiatry and Psychology, Rochester, Minnesota, United States of America
| | - Timothy G. Lesnick
- Mayo Clinic College of Medicine, Department of Health Sciences Research, Rochester, Minnesota, United States of America
| | - David S. Knopman
- Mayo Clinic College of Medicine, Department of Neurology, Rochester, Minnesota, United States of America
| | - Ronald C. Petersen
- Mayo Clinic College of Medicine, Department of Neurology, Rochester, Minnesota, United States of America
| | - Clifford R. Jack
- Mayo Clinic College of Medicine, Department of Radiology, Rochester, Minnesota, United States of America
| | - Kejal Kantarci
- Mayo Clinic College of Medicine, Department of Radiology, Rochester, Minnesota, United States of America
| | - Orhun H. Kantarci
- Mayo Clinic College of Medicine, Department of Neurology, Rochester, Minnesota, United States of America
| |
Collapse
|
23
|
Hashimoto T, Yokota C, Koshino K, Temma T, Yamazaki M, Iguchi S, Shimomura R, Uehara T, Funatsu N, Hino T, Minematsu K, Iida H, Toyoda K. Binding of 11C-Pittsburgh compound-B correlated with white matter injury in hypertensive small vessel disease. Ann Nucl Med 2017; 31:227-234. [PMID: 28220365 DOI: 10.1007/s12149-017-1152-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2016] [Accepted: 01/06/2017] [Indexed: 12/13/2022]
Abstract
OBJECTIVE 11C-Pittsburgh compound-B (11C-PIB) positron emission tomography (PET) is used to visualize and quantify amyloid deposition in the brain cortex in pathological conditions such as Alzheimer's disease (AD). Intense 11C-PIB retention is also observed in the white matter (WM) of both healthy individuals and AD patients. However, the clinical implications of this retention in brain WM have not been clarified. We investigated the relationship between the extent of white matter lesions (WMLs) and the binding potential of 11C-PIB (BPND) in the WM in patients with hypertensive small vessel disease. We further examined the relationship between the extent of WMLs and BPND in WML and in normal-appearing white matter (NAWM). METHODS Twenty-one hypertensive vasculopathy patients, without AD and major cerebral arterial stenosis and/or occlusion, were enrolled (9 women, 68 ± 7 years). Regions of WML and NAWM were extracted using magnetization-prepared rapid gradient-echo and fluid-attenuated inversion recovery of magnetic resonance images. Volumes of interest (VOIs) were set in the cortex-subcortex, basal ganglia, and centrum semiovale (CS). BPND in the cortex-subcortex, basal ganglia, CS, WML, and NAWM were estimated on 11C-PIB PET using Logan graphical analysis with cerebellar regions as references. The relationships between WML volume and BPND in each region were examined by linear regression analysis. RESULTS BPND was higher in the CS and basal ganglia than in the cortex-subcortex regions. WML volume had a significant inverse correlation with BPND in the CS (Slope = -0.0042, R 2 = 0.44, P < 0.01). For intra WM comparison, BPND in NAWM was significantly higher than that in WML. In addition, although there were no correlations between WML volume and BPND in WML, WML volume was significantly correlated inversely with BPND in NAWM (Slope = -0.0017, R 2 = 0.26, P = 0.02). CONCLUSIONS 11C-PIB could be a marker of not only cortical amyloid-β deposition but also WM injury accompanying the development of WMLs in hypertensive small vessel disease.
Collapse
Affiliation(s)
- Tetsuya Hashimoto
- Department of Cerebrovascular medicine, National Cerebral and Cardiovascular Center, 5-7-1 Fujishiro-dai, Suita, Osaka, 565-8565, Japan
| | - Chiaki Yokota
- Department of Cerebrovascular medicine, National Cerebral and Cardiovascular Center, 5-7-1 Fujishiro-dai, Suita, Osaka, 565-8565, Japan.
| | - Kazuhiro Koshino
- Department of Investigative Radiology, National Cerebral and Cardiovascular Center, Suita, Japan
| | - Takashi Temma
- Department of Investigative Radiology, National Cerebral and Cardiovascular Center, Suita, Japan
| | - Makoto Yamazaki
- Department of Investigative Radiology, National Cerebral and Cardiovascular Center, Suita, Japan
| | - Satoshi Iguchi
- Department of Investigative Radiology, National Cerebral and Cardiovascular Center, Suita, Japan
| | - Ryo Shimomura
- Department of Cerebrovascular medicine, National Cerebral and Cardiovascular Center, 5-7-1 Fujishiro-dai, Suita, Osaka, 565-8565, Japan
| | - Toshiyuki Uehara
- Department of Cerebrovascular medicine, National Cerebral and Cardiovascular Center, 5-7-1 Fujishiro-dai, Suita, Osaka, 565-8565, Japan
| | - Naoko Funatsu
- Department of Cerebrovascular medicine, National Cerebral and Cardiovascular Center, 5-7-1 Fujishiro-dai, Suita, Osaka, 565-8565, Japan
| | - Tenyu Hino
- Department of Cerebrovascular medicine, National Cerebral and Cardiovascular Center, 5-7-1 Fujishiro-dai, Suita, Osaka, 565-8565, Japan
| | - Kazuo Minematsu
- Department of Cerebrovascular medicine, National Cerebral and Cardiovascular Center, 5-7-1 Fujishiro-dai, Suita, Osaka, 565-8565, Japan
| | - Hidehiro Iida
- Department of Investigative Radiology, National Cerebral and Cardiovascular Center, Suita, Japan
| | - Kazunori Toyoda
- Department of Cerebrovascular medicine, National Cerebral and Cardiovascular Center, 5-7-1 Fujishiro-dai, Suita, Osaka, 565-8565, Japan
| |
Collapse
|
24
|
Matías-Guiu JA, Cabrera-Martín MN, Matías-Guiu J, Oreja-Guevara C, Riola-Parada C, Moreno-Ramos T, Arrazola J, Carreras JL. Amyloid PET imaging in multiple sclerosis: an (18)F-florbetaben study. BMC Neurol 2015; 15:243. [PMID: 26607782 PMCID: PMC4660647 DOI: 10.1186/s12883-015-0502-2] [Citation(s) in RCA: 51] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2015] [Accepted: 11/20/2015] [Indexed: 12/20/2022] Open
Abstract
Background Positron emission tomography (PET) images with amyloid tracers show normal uptake in healthy white matter, which suggests that amyloid tracers are potentially useful for studying such white matter diseases as multiple sclerosis (MS). Methods Twelve patients diagnosed with MS (5 with RRMS, 5 with SPMS, and 2 with PPMS) and 3 healthy controls underwent studies with MRI and 18F-florbetaben-PET imaging. Images were preprocessed using Statistical Parametric Mapping software. We analysed 18F-florbetaben uptake in demyelinating plaques (appearing as hyperintense lesions in FLAIR sequences), in normal-appearing white matter, and in grey matter. Results Mean standardized uptake value relative to cerebellum was higher in normally appearing white matter (NAWM) (1.51 ± 0.12) than in damaged white matter (DWM) (1.24 ± 0.12; P = .002). Mean percentage of change between NAWM and DWM was −17.56 % ± 6.22 %. This percentage of change correlated negatively with EDSS scores (r = −0.61, p < .05) and with age (r = −0.83, p < 0.01). Progressive forms of MS showed a more pronounced reduction of the uptake in DWM in comparison to relapsing-remitting form. Conclusions Uptake of 18F-florbetaben in damaged white matter is lower than that occurring in normally-appearing white matter. These findings indicate that amyloid tracers may be useful in studies of MS, although further research is needed to evaluate the utility of amyloid-PET in monitoring MS progression. Electronic supplementary material The online version of this article (doi:10.1186/s12883-015-0502-2) contains supplementary material, which is available to authorized users.
Collapse
Affiliation(s)
- Jordi A Matías-Guiu
- Department of Neurology, Hospital Clínico San Carlos. San Carlos Institute for Health Research (IdISSC), Universidad Complutense de Madrid, Calle Profesor Martín Lagos, S/N, Madrid, 28040, Spain.
| | - María Nieves Cabrera-Martín
- Department of Nuclear Medicine, Hospital Clínico San Carlos. San Carlos Institute for Health Research (IdISSC), Universidad Complutense de Madrid, Calle Profesor Martín Lagos, S/N, Madrid, 28040, Spain.
| | - Jorge Matías-Guiu
- Department of Neurology, Hospital Clínico San Carlos. San Carlos Institute for Health Research (IdISSC), Universidad Complutense de Madrid, Calle Profesor Martín Lagos, S/N, Madrid, 28040, Spain.
| | - Celia Oreja-Guevara
- Department of Neurology, Hospital Clínico San Carlos. San Carlos Institute for Health Research (IdISSC), Universidad Complutense de Madrid, Calle Profesor Martín Lagos, S/N, Madrid, 28040, Spain.
| | - Cristina Riola-Parada
- Department of Nuclear Medicine, Hospital Clínico San Carlos. San Carlos Institute for Health Research (IdISSC), Universidad Complutense de Madrid, Calle Profesor Martín Lagos, S/N, Madrid, 28040, Spain.
| | - Teresa Moreno-Ramos
- Department of Neurology, Hospital Clínico San Carlos. San Carlos Institute for Health Research (IdISSC), Universidad Complutense de Madrid, Calle Profesor Martín Lagos, S/N, Madrid, 28040, Spain.
| | - Juan Arrazola
- Department of Radiology, Hospital Clínico San Carlos. San Carlos Institute for Health Research (IdISSC), Universidad Complutense de Madrid, Calle Profesor Martín Lagos, S/N, Madrid, 28040, Spain.
| | - José Luis Carreras
- Department of Nuclear Medicine, Hospital Clínico San Carlos. San Carlos Institute for Health Research (IdISSC), Universidad Complutense de Madrid, Calle Profesor Martín Lagos, S/N, Madrid, 28040, Spain.
| |
Collapse
|
25
|
Heurling K, Buckley C, Vandenberghe R, Laere KV, Lubberink M. Separation of β-amyloid binding and white matter uptake of (18)F-flutemetamol using spectral analysis. AMERICAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING 2015; 5:515-526. [PMID: 26550542 PMCID: PMC4620178] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Received: 07/31/2015] [Accepted: 08/26/2015] [Indexed: 06/05/2023]
Abstract
The kinetic components of the β-amyloid ligand (18)F-flutemetamol binding in grey and white matter were investigated through spectral analysis, and a method developed for creation of parametric images separating grey and white matter uptake. Tracer uptake in grey and white matter and cerebellar cortex was analyzed through spectral analysis in six subjects, with (n=4) or without (n=2) apparent β-amyloid deposition, having undergone dynamic (18)F-flutemetamol scanning with arterial blood sampling. The spectra were divided into three components: slow, intermediate and fast basis function rates. The contribution of each of the components to total volume of distribution (VT) was assessed for different tissue types. The slow component dominated in white matter (average 90%), had a higher contribution to grey matter VT in subjects with β-amyloid deposition (average 44%) than without (average 6%) and was absent in cerebellar cortex, attributing the slow component of (18)F-flutemetamol uptake in grey matter to β-amyloid binding. Parametric images of voxel-based spectral analysis were created for VT, the slow component and images segmented based on the slow component contribution; confirming that grey matter and white matter uptake can be discriminated on voxel-level using a threshold for the contribution from the slow component to VT.
Collapse
Affiliation(s)
- Kerstin Heurling
- Department of Surgical Sciences, Uppsala UniversityUppsala, Sweden
| | | | - Rik Vandenberghe
- Department of Neurosciences, KU Leuven and University Hospitals LeuvenLeuven, Belgium
| | - Koen Van Laere
- Department of Imaging and Pathology, KU Leuven and University Hospitals LeuvenLeuven, Belgium
| | - Mark Lubberink
- Department of Surgical Sciences, Uppsala UniversityUppsala, Sweden
- Medical Physics, Uppsala University HospitalUppsala, Sweden
| |
Collapse
|
26
|
Heurling K, Leuzy A, Zimmer ER, Lubberink M, Nordberg A. Imaging β-amyloid using [18F]flutemetamol positron emission tomography: from dosimetry to clinical diagnosis. Eur J Nucl Med Mol Imaging 2015; 43:362-373. [DOI: 10.1007/s00259-015-3208-1] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2015] [Accepted: 09/28/2015] [Indexed: 12/14/2022]
|