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Dybing KM, Vetter CJ, Dempsey DA, Chaudhuri S, Saykin AJ, Risacher SL. Traumatic brain injury and Alzheimer's Disease biomarkers: A systematic review of findings from amyloid and tau positron emission tomography (PET). MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.11.30.23298528. [PMID: 38077068 PMCID: PMC10705648 DOI: 10.1101/2023.11.30.23298528] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/21/2023]
Abstract
Traumatic brain injury (TBI) has been discussed as a risk factor for Alzheimer's disease (AD) due to its association with dementia risk and earlier cognitive symptom onset. However, the mechanisms behind this relationship are unclear. Some studies have suggested TBI may increase pathological protein deposition in an AD-like pattern; others have failed to find such associations. This review covers literature that uses positron emission tomography (PET) of amyloid-β and/or tau to examine subjects with history of TBI who are at risk for AD due to advanced age. A comprehensive literature search was conducted on January 9, 2023, and 24 resulting citations met inclusion criteria. Common methodological concerns included small samples, limited clinical detail about subjects' TBI, recall bias due to reliance on self-reported TBI, and an inability to establish causation. For both amyloid and tau, results were widespread but inconsistent. The regions which showed the most compelling evidence for increased amyloid deposition were the cingulate gyrus, cuneus/precuneus, and parietal lobe. Evidence for increased tau was strongest in the medial temporal lobe, entorhinal cortex, precuneus, and frontal, temporal, parietal, and occipital lobes. However, conflicting findings across most regions of interest in both amyloid- and tau-PET studies indicate the critical need for future work in expanded samples and with greater clinical detail to offer a clearer picture of the relationship between TBI and protein deposition in older subjects at risk for AD.
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Affiliation(s)
- Kaitlyn M. Dybing
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
- Indiana Alzheimer’s Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
- Stark Neurosciences Research Institute, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
| | - Cecelia J. Vetter
- Ruth Lilly Medical Library, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
| | - Desarae A. Dempsey
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
- Indiana Alzheimer’s Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
- Stark Neurosciences Research Institute, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
| | - Soumilee Chaudhuri
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
- Indiana Alzheimer’s Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
- Stark Neurosciences Research Institute, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
| | - Andrew J. Saykin
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
- Indiana Alzheimer’s Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
- Stark Neurosciences Research Institute, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
- Department of Neurology, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
- Department of Psychiatry, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
| | - Shannon L. Risacher
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
- Indiana Alzheimer’s Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
- Stark Neurosciences Research Institute, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
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Pemberton HG, Buckley C, Battle M, Bollack A, Patel V, Tomova P, Cooke D, Balhorn W, Hegedorn K, Lilja J, Brand C, Farrar G. Software compatibility analysis for quantitative measures of [ 18F]flutemetamol amyloid PET burden in mild cognitive impairment. EJNMMI Res 2023; 13:48. [PMID: 37225974 DOI: 10.1186/s13550-023-00994-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2022] [Accepted: 05/05/2023] [Indexed: 05/26/2023] Open
Abstract
RATIONALE Amyloid-β (Aβ) pathology is one of the earliest detectable brain changes in Alzheimer's disease pathogenesis. In clinical practice, trained readers will visually categorise positron emission tomography (PET) scans as either Aβ positive or negative. However, adjunct quantitative analysis is becoming more widely available, where regulatory approved software can currently generate metrics such as standardised uptake value ratios (SUVr) and individual Z-scores. Therefore, it is of direct value to the imaging community to assess the compatibility of commercially available software packages. In this collaborative project, the compatibility of amyloid PET quantification was investigated across four regulatory approved software packages. In doing so, the intention is to increase visibility and understanding of clinically relevant quantitative methods. METHODS Composite SUVr using the pons as the reference region was generated from [18F]flutemetamol (GE Healthcare) PET in a retrospective cohort of 80 amnestic mild cognitive impairment (aMCI) patients (40 each male/female; mean age = 73 years, SD = 8.52). Based on previous autopsy validation work, an Aβ positivity threshold of ≥ 0.6 SUVrpons was applied. Quantitative results from MIM Software's MIMneuro, Syntermed's NeuroQ, Hermes Medical Solutions' BRASS and GE Healthcare's CortexID were analysed using intraclass correlation coefficient (ICC), percentage agreement around the Aβ positivity threshold and kappa scores. RESULTS Using an Aβ positivity threshold of ≥ 0.6 SUVrpons, 95% agreement was achieved across the four software packages. Two patients were narrowly classed as Aβ negative by one software package but positive by the others, and two patients vice versa. All kappa scores around the same Aβ positivity threshold, both combined (Fleiss') and individual software pairings (Cohen's), were ≥ 0.9 signifying "almost perfect" inter-rater reliability. Excellent reliability was found between composite SUVr measurements for all four software packages, with an average measure ICC of 0.97 and 95% confidence interval of 0.957-0.979. Correlation coefficient analysis between the two software packages reporting composite z-scores was strong (r2 = 0.98). CONCLUSION Using an optimised cortical mask, regulatory approved software packages provided highly correlated and reliable quantification of [18F]flutemetamol amyloid PET with a ≥ 0.6 SUVrpons positivity threshold. In particular, this work could be of interest to physicians performing routine clinical imaging rather than researchers performing more bespoke image analysis. Similar analysis is encouraged using other reference regions as well as the Centiloid scale, when it has been implemented by more software packages.
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Affiliation(s)
- Hugh G Pemberton
- GE Healthcare, Pollards Wood, Chalfont St Giles, Amersham, HP8 4SP, UK.
- Centre for Medical Image Computing (CMIC), Department of Medical Physics and Bioengineering, University College London, London, UK.
- UCL Queen Square Institute of Neurology, University College London, London, UK.
| | | | - Mark Battle
- GE Healthcare, Pollards Wood, Chalfont St Giles, Amersham, HP8 4SP, UK
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmö, Sweden
| | - Ariane Bollack
- Centre for Medical Image Computing (CMIC), Department of Medical Physics and Bioengineering, University College London, London, UK
| | - Vrajesh Patel
- GE Healthcare, Pollards Wood, Chalfont St Giles, Amersham, HP8 4SP, UK
| | - Petya Tomova
- GE Healthcare, Pollards Wood, Chalfont St Giles, Amersham, HP8 4SP, UK
| | | | | | | | | | - Christine Brand
- GE Healthcare, Pollards Wood, Chalfont St Giles, Amersham, HP8 4SP, UK
| | - Gill Farrar
- GE Healthcare, Pollards Wood, Chalfont St Giles, Amersham, HP8 4SP, UK
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Duan J, Liu Y, Wu H, Wang J, Chen L, Chen CLP. Broad learning for early diagnosis of Alzheimer's disease using FDG-PET of the brain. Front Neurosci 2023; 17:1137567. [PMID: 36992851 PMCID: PMC10040750 DOI: 10.3389/fnins.2023.1137567] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2023] [Accepted: 02/13/2023] [Indexed: 03/14/2023] Open
Abstract
Alzheimer's disease (AD) is a progressive neurodegenerative disease, and the development of AD is irreversible. However, preventive measures in the presymptomatic stage of AD can effectively slow down deterioration. Fluorodeoxyglucose positron emission tomography (FDG-PET) can detect the metabolism of glucose in patients' brains, which can help to identify changes related to AD before brain damage occurs. Machine learning is useful for early diagnosis of patients with AD using FDG-PET, but it requires a sufficiently large dataset, and it is easy for overfitting to occur in small datasets. Previous studies using machine learning for early diagnosis with FDG-PET have either involved the extraction of elaborately handcrafted features or validation on a small dataset, and few studies have explored the refined classification of early mild cognitive impairment (EMCI) and late mild cognitive impairment (LMCI). This article presents a broad network-based model for early diagnosis of AD (BLADNet) through PET imaging of the brain; this method employs a novel broad neural network to enhance the features of FDG-PET extracted via 2D CNN. BLADNet can search for information over a broad space through the addition of new BLS blocks without retraining of the whole network, thus improving the accuracy of AD classification. Experiments conducted on a dataset containing 2,298 FDG-PET images of 1,045 subjects from the ADNI database demonstrate that our methods are superior to those used in previous studies on early diagnosis of AD with FDG-PET. In particular, our methods achieved state-of-the-art results in EMCI and LMCI classification with FDG-PET.
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Affiliation(s)
- Junwei Duan
- College of Information Science and Technology, Jinan University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Traditional Chinese Medicine Informatization, Jinan University, Guangzhou, China
- *Correspondence: Junwei Duan
| | - Yang Liu
- College of Information Science and Technology, Jinan University, Guangzhou, China
| | - Huanhua Wu
- Department of Nuclear Medicine and PET/CT-MRI Centre, The First Affiliated Hospital of Jinan University, Guangzhou, China
| | - Jing Wang
- School of Computer Science, Guangdong Polytechnic Normal University, Guangzhou, China
- Jing Wang
| | - Long Chen
- Department of Computer and Information Science, Faculty of Science and Technology, University of Macau, Taipa, Macau SAR, China
| | - C. L. Philip Chen
- School of Computer Science and Engineering, South China University of Technology, Guangzhou, China
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Pemberton HG, Collij LE, Heeman F, Bollack A, Shekari M, Salvadó G, Alves IL, Garcia DV, Battle M, Buckley C, Stephens AW, Bullich S, Garibotto V, Barkhof F, Gispert JD, Farrar G. Quantification of amyloid PET for future clinical use: a state-of-the-art review. Eur J Nucl Med Mol Imaging 2022; 49:3508-3528. [PMID: 35389071 PMCID: PMC9308604 DOI: 10.1007/s00259-022-05784-y] [Citation(s) in RCA: 30] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2021] [Accepted: 03/25/2022] [Indexed: 12/15/2022]
Abstract
Amyloid-β (Aβ) pathology is one of the earliest detectable brain changes in Alzheimer's disease (AD) pathogenesis. The overall load and spatial distribution of brain Aβ can be determined in vivo using positron emission tomography (PET), for which three fluorine-18 labelled radiotracers have been approved for clinical use. In clinical practice, trained readers will categorise scans as either Aβ positive or negative, based on visual inspection. Diagnostic decisions are often based on these reads and patient selection for clinical trials is increasingly guided by amyloid status. However, tracer deposition in the grey matter as a function of amyloid load is an inherently continuous process, which is not sufficiently appreciated through binary cut-offs alone. State-of-the-art methods for amyloid PET quantification can generate tracer-independent measures of Aβ burden. Recent research has shown the ability of these quantitative measures to highlight pathological changes at the earliest stages of the AD continuum and generate more sensitive thresholds, as well as improving diagnostic confidence around established binary cut-offs. With the recent FDA approval of aducanumab and more candidate drugs on the horizon, early identification of amyloid burden using quantitative measures is critical for enrolling appropriate subjects to help establish the optimal window for therapeutic intervention and secondary prevention. In addition, quantitative amyloid measurements are used for treatment response monitoring in clinical trials. In clinical settings, large multi-centre studies have shown that amyloid PET results change both diagnosis and patient management and that quantification can accurately predict rates of cognitive decline. Whether these changes in management reflect an improvement in clinical outcomes is yet to be determined and further validation work is required to establish the utility of quantification for supporting treatment endpoint decisions. In this state-of-the-art review, several tools and measures available for amyloid PET quantification are summarised and discussed. Use of these methods is growing both clinically and in the research domain. Concurrently, there is a duty of care to the wider dementia community to increase visibility and understanding of these methods.
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Affiliation(s)
- Hugh G Pemberton
- GE Healthcare, Amersham, UK.
- Centre for Medical Image Computing (CMIC), Department of Medical Physics and Bioengineering, University College London, London, UK.
- UCL Queen Square Institute of Neurology, University College London, London, UK.
| | - Lyduine E Collij
- Department of Radiology and Nuclear Medicine, Amsterdam Neurocience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Fiona Heeman
- Department of Radiology and Nuclear Medicine, Amsterdam Neurocience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Ariane Bollack
- Centre for Medical Image Computing (CMIC), Department of Medical Physics and Bioengineering, University College London, London, UK
| | - Mahnaz Shekari
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- Universitat Pompeu Fabra, Barcelona, Spain
- IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain
| | - Gemma Salvadó
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmö, Sweden
| | - Isadora Lopes Alves
- Department of Radiology and Nuclear Medicine, Amsterdam Neurocience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Brain Research Center, Amsterdam, The Netherlands
| | - David Vallez Garcia
- Department of Radiology and Nuclear Medicine, Amsterdam Neurocience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Mark Battle
- GE Healthcare, Amersham, UK
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmö, Sweden
| | | | | | | | - Valentina Garibotto
- Division of Nuclear Medicine and Molecular Imaging, University Hospitals of Geneva, Geneva, Switzerland
- NIMTLab, Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Frederik Barkhof
- Centre for Medical Image Computing (CMIC), Department of Medical Physics and Bioengineering, University College London, London, UK
- UCL Queen Square Institute of Neurology, University College London, London, UK
- Department of Radiology and Nuclear Medicine, Amsterdam Neurocience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Juan Domingo Gispert
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- Universitat Pompeu Fabra, Barcelona, Spain
- IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain
- Centro de Investigación Biomédica en Red Bioingeniería, Biomateriales y Nanomedicina, Madrid, Spain
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Langheinrich T, Kobylecki C, Jones M, Thompson JC, Snowden JS, Hinz R, Pickering-Brown S, Mann D, Roncaroli F, Herholz K, Gerhard A. Amyloid-PET-Positive Patient With bvFTD: Wrong Diagnosis, False Positive Scan, or Copathology? Neurol Clin Pract 2022; 11:e952-e955. [PMID: 34992994 DOI: 10.1212/cpj.0000000000001049] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2020] [Accepted: 11/30/2020] [Indexed: 11/15/2022]
Abstract
A 65-year-old man was referred to a local memory clinic with memory complaints but clinical assessment found no abnormalities. When he presented two years later to our clinic social disinhibition, reduced empathy, poor judgment and hoarding had become obvious. He showed no insight. He had ischemic heart disease and was on preventive treatment. His mother died aged 97 suffering from dementia. Neurological examination was normal. During neuropsychological examination he exhibited verbal and behavioral disinhibition, inattention, emotional blunting and unconcern. He had prominent difficulties in abstraction, set shifting and sequencing with significant impact on memory tests (table1). A clinical diagnosis of behavioral variant FTD (bvFTD) was made. MRI (figure A) showed right more than left-sided temporal atrophy, bilateral frontal and milder parietal atrophy. Fluorodeoxyglucose (FDG)-PET (figure B) demonstrated fronto-temporal hypometabolism. Metabolism in the posterior cingulate was normal. He was homozygous for the APOE ε4 allele and negative for the C9orf72 expansion and mutations in MAPT, GRN, PSEN1, and APP. [18F]-Florbetapir PET (figure C) revealed increased tracer binding in all cortical regions corresponding to a centiloid value of 74%.
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Affiliation(s)
- Tobias Langheinrich
- Cerebral Function Unit (TL, MJ, JCT, JSS), Manchester Centre for Clinical Neurosciences, Salford Royal NHS Foundation Trust, United Kingdom; Division of Neuroscience and Experimental Psychology (TL, CK, MJ, JCT, JSS, RH, SP-B, DM, FR, KH, AG), School of Biological Sciences, University of Manchester; Department of Neurology (CK), Manchester Centre for Clinical Neurosciences, Salford Royal NHS Foundation Trust, United Kingdom; and Departments of Geriatric Medicine and Nuclear Medicine (AG), University of Duisburg-Essen, Germany
| | - Christopher Kobylecki
- Cerebral Function Unit (TL, MJ, JCT, JSS), Manchester Centre for Clinical Neurosciences, Salford Royal NHS Foundation Trust, United Kingdom; Division of Neuroscience and Experimental Psychology (TL, CK, MJ, JCT, JSS, RH, SP-B, DM, FR, KH, AG), School of Biological Sciences, University of Manchester; Department of Neurology (CK), Manchester Centre for Clinical Neurosciences, Salford Royal NHS Foundation Trust, United Kingdom; and Departments of Geriatric Medicine and Nuclear Medicine (AG), University of Duisburg-Essen, Germany
| | - Matthew Jones
- Cerebral Function Unit (TL, MJ, JCT, JSS), Manchester Centre for Clinical Neurosciences, Salford Royal NHS Foundation Trust, United Kingdom; Division of Neuroscience and Experimental Psychology (TL, CK, MJ, JCT, JSS, RH, SP-B, DM, FR, KH, AG), School of Biological Sciences, University of Manchester; Department of Neurology (CK), Manchester Centre for Clinical Neurosciences, Salford Royal NHS Foundation Trust, United Kingdom; and Departments of Geriatric Medicine and Nuclear Medicine (AG), University of Duisburg-Essen, Germany
| | - Jennifer C Thompson
- Cerebral Function Unit (TL, MJ, JCT, JSS), Manchester Centre for Clinical Neurosciences, Salford Royal NHS Foundation Trust, United Kingdom; Division of Neuroscience and Experimental Psychology (TL, CK, MJ, JCT, JSS, RH, SP-B, DM, FR, KH, AG), School of Biological Sciences, University of Manchester; Department of Neurology (CK), Manchester Centre for Clinical Neurosciences, Salford Royal NHS Foundation Trust, United Kingdom; and Departments of Geriatric Medicine and Nuclear Medicine (AG), University of Duisburg-Essen, Germany
| | - Julie S Snowden
- Cerebral Function Unit (TL, MJ, JCT, JSS), Manchester Centre for Clinical Neurosciences, Salford Royal NHS Foundation Trust, United Kingdom; Division of Neuroscience and Experimental Psychology (TL, CK, MJ, JCT, JSS, RH, SP-B, DM, FR, KH, AG), School of Biological Sciences, University of Manchester; Department of Neurology (CK), Manchester Centre for Clinical Neurosciences, Salford Royal NHS Foundation Trust, United Kingdom; and Departments of Geriatric Medicine and Nuclear Medicine (AG), University of Duisburg-Essen, Germany
| | - Rainer Hinz
- Cerebral Function Unit (TL, MJ, JCT, JSS), Manchester Centre for Clinical Neurosciences, Salford Royal NHS Foundation Trust, United Kingdom; Division of Neuroscience and Experimental Psychology (TL, CK, MJ, JCT, JSS, RH, SP-B, DM, FR, KH, AG), School of Biological Sciences, University of Manchester; Department of Neurology (CK), Manchester Centre for Clinical Neurosciences, Salford Royal NHS Foundation Trust, United Kingdom; and Departments of Geriatric Medicine and Nuclear Medicine (AG), University of Duisburg-Essen, Germany
| | - Stuart Pickering-Brown
- Cerebral Function Unit (TL, MJ, JCT, JSS), Manchester Centre for Clinical Neurosciences, Salford Royal NHS Foundation Trust, United Kingdom; Division of Neuroscience and Experimental Psychology (TL, CK, MJ, JCT, JSS, RH, SP-B, DM, FR, KH, AG), School of Biological Sciences, University of Manchester; Department of Neurology (CK), Manchester Centre for Clinical Neurosciences, Salford Royal NHS Foundation Trust, United Kingdom; and Departments of Geriatric Medicine and Nuclear Medicine (AG), University of Duisburg-Essen, Germany
| | - David Mann
- Cerebral Function Unit (TL, MJ, JCT, JSS), Manchester Centre for Clinical Neurosciences, Salford Royal NHS Foundation Trust, United Kingdom; Division of Neuroscience and Experimental Psychology (TL, CK, MJ, JCT, JSS, RH, SP-B, DM, FR, KH, AG), School of Biological Sciences, University of Manchester; Department of Neurology (CK), Manchester Centre for Clinical Neurosciences, Salford Royal NHS Foundation Trust, United Kingdom; and Departments of Geriatric Medicine and Nuclear Medicine (AG), University of Duisburg-Essen, Germany
| | - Federico Roncaroli
- Cerebral Function Unit (TL, MJ, JCT, JSS), Manchester Centre for Clinical Neurosciences, Salford Royal NHS Foundation Trust, United Kingdom; Division of Neuroscience and Experimental Psychology (TL, CK, MJ, JCT, JSS, RH, SP-B, DM, FR, KH, AG), School of Biological Sciences, University of Manchester; Department of Neurology (CK), Manchester Centre for Clinical Neurosciences, Salford Royal NHS Foundation Trust, United Kingdom; and Departments of Geriatric Medicine and Nuclear Medicine (AG), University of Duisburg-Essen, Germany
| | - Karl Herholz
- Cerebral Function Unit (TL, MJ, JCT, JSS), Manchester Centre for Clinical Neurosciences, Salford Royal NHS Foundation Trust, United Kingdom; Division of Neuroscience and Experimental Psychology (TL, CK, MJ, JCT, JSS, RH, SP-B, DM, FR, KH, AG), School of Biological Sciences, University of Manchester; Department of Neurology (CK), Manchester Centre for Clinical Neurosciences, Salford Royal NHS Foundation Trust, United Kingdom; and Departments of Geriatric Medicine and Nuclear Medicine (AG), University of Duisburg-Essen, Germany
| | - Alex Gerhard
- Cerebral Function Unit (TL, MJ, JCT, JSS), Manchester Centre for Clinical Neurosciences, Salford Royal NHS Foundation Trust, United Kingdom; Division of Neuroscience and Experimental Psychology (TL, CK, MJ, JCT, JSS, RH, SP-B, DM, FR, KH, AG), School of Biological Sciences, University of Manchester; Department of Neurology (CK), Manchester Centre for Clinical Neurosciences, Salford Royal NHS Foundation Trust, United Kingdom; and Departments of Geriatric Medicine and Nuclear Medicine (AG), University of Duisburg-Essen, Germany
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Sarikaya I, Kamel WA, Ateyah KK, Essa NB, AlTailji S, Sarikaya A. Visual versus semiquantitative analysis of 18F- fluorodeoxyglucose-positron emission tomography brain images in patients with dementia. World J Nucl Med 2021; 20:82-89. [PMID: 33850493 PMCID: PMC8034786 DOI: 10.4103/wjnm.wjnm_53_18] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2018] [Revised: 05/31/2018] [Accepted: 07/19/2018] [Indexed: 11/04/2022] Open
Abstract
Various studies have reported to the superiority of semiquantitative (SQ) analysis over visual analysis in detecting metabolic changes in the brain. In this study, we aimed to determine the limitations of SQ analysis programs and the current status of 18F- fluorodeoxyglucose (FDG)-positron emission tomography (PET) scan in dementia. 18F- FDG-PET/computed tomography (CT) brain images of 39 patients with a history of dementia were analyzed both visually and semiquantitatively. Using the visually markedly abnormal 18F- FDG-PET images as standard, we wanted to test the accuracy of two commercially available SQ analysis programs. SQ analysis results were classified as matching, partially matching and nonmatching with visually markedly abnormal studies. On visual analysis, 18F- FDG-PET showed marked regional hypometabolism in 19 patients, mild abnormalities in 8 and was normal in 12 patients. SQ analysis-1 results matched with visual analysis in 8 patients (42.1%) and partially matched in 11. SQ analysis-2 findings matched with visual analysis in 11 patients (57.8%) and partially matched in 7 and did not match in 1. Marked regional hypometabolism was either on the left side of the brain or was more significant on the left than the right in 63% of patients. Preservation of metabolism in sensorimotor cortex was seen in various dementia subtypes. Reviewing images in color scale and maximum intensity projection (MIP) image was helpful in demonstrating and displaying regional abnormalities, respectively. SQ analysis provides less accurate results as compared to visual analysis by experts. Due to suboptimal image registration and selection of brain areas, SQ analysis provides inaccurate results, particularly in small areas and areas in close proximity. Image registration and selection of areas with SQ programs should be checked carefully before reporting the results.
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Affiliation(s)
- Ismet Sarikaya
- Department of Nuclear Medicine, Faculty of Medicine, Kuwait University, Kuwait University, Kuwait
| | - Walaa A Kamel
- Department of Neurology, Faculty of Medicine, Beni-Suef University, Egypt.,Department of Nuclear Medicine, Ibn Sina Hospital, Kuwait
| | | | - Nooraessa Bin Essa
- Department of Nuclear Medicine, Mubarak Al-Kabeer Hospital, Kuwait City, Kuwait
| | | | - Ali Sarikaya
- Department of Nuclear Medicine, Faculty of Medicine, Trakya University, Edirne, Turkey
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7
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Leuzy A, Lilja J, Buckley CJ, Ossenkoppele R, Palmqvist S, Battle M, Farrar G, Thal DR, Janelidze S, Stomrud E, Strandberg O, Smith R, Hansson O. Derivation and utility of an Aβ-PET pathology accumulation index to estimate Aβ load. Neurology 2020; 95:e2834-e2844. [PMID: 33077542 PMCID: PMC7734735 DOI: 10.1212/wnl.0000000000011031] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2020] [Accepted: 08/03/2020] [Indexed: 11/15/2022] Open
Abstract
OBJECTIVE To evaluate a novel β-amyloid (Aβ)-PET-based quantitative measure (Aβ accumulation index [Aβ index]), including the assessment of its ability to discriminate between participants based on Aβ status using visual read, CSF Aβ42/Aβ40, and post-mortem neuritic plaque burden as standards of truth. METHODS One thousand one hundred twenty-one participants (with and without cognitive impairment) were scanned with Aβ-PET: Swedish BioFINDER, n = 392, [18F]flutemetamol; Alzheimer's Disease Neuroimaging Initiative (ADNI), n = 692, [18F]florbetapir; and a phase 3 end-of-life study, n = 100, [18F]flutemetamol. The relationships between Aβ index and standardized uptake values ratios (SUVR) from Aβ-PET were assessed. The diagnostic performances of Aβ index and SUVR were compared with visual reads, CSF Aβ42/Aβ40, and Aβ histopathology used as reference standards. RESULTS Strong associations were observed between Aβ index and SUVR (R 2: BioFINDER 0.951, ADNI 0.943, end-of-life, 0.916). Both measures performed equally well in differentiating Aβ-positive from Aβ-negative participants, with areas under the curve (AUCs) of 0.979 to 0.991 to detect abnormal visual reads, AUCs of 0.961 to 0.966 to detect abnormal CSF Aβ42/Aβ40, and AUCs of 0.820 to 0.823 to detect abnormal Aβ histopathology. Both measures also showed a similar distribution across postmortem-based Aβ phases (based on anti-Aβ 4G8 antibodies). Compared to models using visual read alone, the addition of the Aβ index resulted in a significant increase in AUC and a decrease in Akaike information criterion to detect abnormal Aβ histopathology. CONCLUSION The proposed Aβ index showed a tight association to SUVR and carries an advantage over the latter in that it does not require the definition of regions of interest or the use of MRI. Aβ index may thus prove simpler to implement in clinical settings and may also facilitate the comparison of findings using different Aβ-PET tracers. CLASSIFICATION OF EVIDENCE This study provides Class III evidence that the Aβ accumulation index accurately differentiates Aβ-positive from Aβ-negative participants compared to Aβ-PET visual reads, CSF Aβ42/Aβ40, and Aβ histopathology.
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Affiliation(s)
- Antoine Leuzy
- From the Clinical Memory Research Unit (A.L., J.L., R.O., S.P., S.J., E.S., O.S., R.S., O.H.), Department of Clinical Sciences, Lund University, Malmö; Department of Surgical Sciences, Nuclear Medicine and PET (J.L.), Uppsala University; Hermes Medical Solutions (J.L.), Stockholm, Sweden; GE Healthcare Life Sciences (C.J.B., M.B., G.F.), Amersham, UK; VU University Medical Center (R.O.), Neuroscience Campus Amsterdam, the Netherlands; Department of Neurology (S.P., R.S.) and Memory Clinic (E.S., O.H.), Skåne University Hospital, Lund, Sweden; Department of Imaging and Pathology (D.R.T.), Laboratory of Neuropathology, and Leuven Brain Institute (D.R.T.), Campus Gasthuisberg; and Department of Pathology (D.R.T.), UZ-Leuven, Belgium.
| | - Johan Lilja
- From the Clinical Memory Research Unit (A.L., J.L., R.O., S.P., S.J., E.S., O.S., R.S., O.H.), Department of Clinical Sciences, Lund University, Malmö; Department of Surgical Sciences, Nuclear Medicine and PET (J.L.), Uppsala University; Hermes Medical Solutions (J.L.), Stockholm, Sweden; GE Healthcare Life Sciences (C.J.B., M.B., G.F.), Amersham, UK; VU University Medical Center (R.O.), Neuroscience Campus Amsterdam, the Netherlands; Department of Neurology (S.P., R.S.) and Memory Clinic (E.S., O.H.), Skåne University Hospital, Lund, Sweden; Department of Imaging and Pathology (D.R.T.), Laboratory of Neuropathology, and Leuven Brain Institute (D.R.T.), Campus Gasthuisberg; and Department of Pathology (D.R.T.), UZ-Leuven, Belgium
| | - Christopher J Buckley
- From the Clinical Memory Research Unit (A.L., J.L., R.O., S.P., S.J., E.S., O.S., R.S., O.H.), Department of Clinical Sciences, Lund University, Malmö; Department of Surgical Sciences, Nuclear Medicine and PET (J.L.), Uppsala University; Hermes Medical Solutions (J.L.), Stockholm, Sweden; GE Healthcare Life Sciences (C.J.B., M.B., G.F.), Amersham, UK; VU University Medical Center (R.O.), Neuroscience Campus Amsterdam, the Netherlands; Department of Neurology (S.P., R.S.) and Memory Clinic (E.S., O.H.), Skåne University Hospital, Lund, Sweden; Department of Imaging and Pathology (D.R.T.), Laboratory of Neuropathology, and Leuven Brain Institute (D.R.T.), Campus Gasthuisberg; and Department of Pathology (D.R.T.), UZ-Leuven, Belgium
| | - Rik Ossenkoppele
- From the Clinical Memory Research Unit (A.L., J.L., R.O., S.P., S.J., E.S., O.S., R.S., O.H.), Department of Clinical Sciences, Lund University, Malmö; Department of Surgical Sciences, Nuclear Medicine and PET (J.L.), Uppsala University; Hermes Medical Solutions (J.L.), Stockholm, Sweden; GE Healthcare Life Sciences (C.J.B., M.B., G.F.), Amersham, UK; VU University Medical Center (R.O.), Neuroscience Campus Amsterdam, the Netherlands; Department of Neurology (S.P., R.S.) and Memory Clinic (E.S., O.H.), Skåne University Hospital, Lund, Sweden; Department of Imaging and Pathology (D.R.T.), Laboratory of Neuropathology, and Leuven Brain Institute (D.R.T.), Campus Gasthuisberg; and Department of Pathology (D.R.T.), UZ-Leuven, Belgium
| | - Sebastian Palmqvist
- From the Clinical Memory Research Unit (A.L., J.L., R.O., S.P., S.J., E.S., O.S., R.S., O.H.), Department of Clinical Sciences, Lund University, Malmö; Department of Surgical Sciences, Nuclear Medicine and PET (J.L.), Uppsala University; Hermes Medical Solutions (J.L.), Stockholm, Sweden; GE Healthcare Life Sciences (C.J.B., M.B., G.F.), Amersham, UK; VU University Medical Center (R.O.), Neuroscience Campus Amsterdam, the Netherlands; Department of Neurology (S.P., R.S.) and Memory Clinic (E.S., O.H.), Skåne University Hospital, Lund, Sweden; Department of Imaging and Pathology (D.R.T.), Laboratory of Neuropathology, and Leuven Brain Institute (D.R.T.), Campus Gasthuisberg; and Department of Pathology (D.R.T.), UZ-Leuven, Belgium
| | - Mark Battle
- From the Clinical Memory Research Unit (A.L., J.L., R.O., S.P., S.J., E.S., O.S., R.S., O.H.), Department of Clinical Sciences, Lund University, Malmö; Department of Surgical Sciences, Nuclear Medicine and PET (J.L.), Uppsala University; Hermes Medical Solutions (J.L.), Stockholm, Sweden; GE Healthcare Life Sciences (C.J.B., M.B., G.F.), Amersham, UK; VU University Medical Center (R.O.), Neuroscience Campus Amsterdam, the Netherlands; Department of Neurology (S.P., R.S.) and Memory Clinic (E.S., O.H.), Skåne University Hospital, Lund, Sweden; Department of Imaging and Pathology (D.R.T.), Laboratory of Neuropathology, and Leuven Brain Institute (D.R.T.), Campus Gasthuisberg; and Department of Pathology (D.R.T.), UZ-Leuven, Belgium
| | - Gill Farrar
- From the Clinical Memory Research Unit (A.L., J.L., R.O., S.P., S.J., E.S., O.S., R.S., O.H.), Department of Clinical Sciences, Lund University, Malmö; Department of Surgical Sciences, Nuclear Medicine and PET (J.L.), Uppsala University; Hermes Medical Solutions (J.L.), Stockholm, Sweden; GE Healthcare Life Sciences (C.J.B., M.B., G.F.), Amersham, UK; VU University Medical Center (R.O.), Neuroscience Campus Amsterdam, the Netherlands; Department of Neurology (S.P., R.S.) and Memory Clinic (E.S., O.H.), Skåne University Hospital, Lund, Sweden; Department of Imaging and Pathology (D.R.T.), Laboratory of Neuropathology, and Leuven Brain Institute (D.R.T.), Campus Gasthuisberg; and Department of Pathology (D.R.T.), UZ-Leuven, Belgium
| | - Dietmar R Thal
- From the Clinical Memory Research Unit (A.L., J.L., R.O., S.P., S.J., E.S., O.S., R.S., O.H.), Department of Clinical Sciences, Lund University, Malmö; Department of Surgical Sciences, Nuclear Medicine and PET (J.L.), Uppsala University; Hermes Medical Solutions (J.L.), Stockholm, Sweden; GE Healthcare Life Sciences (C.J.B., M.B., G.F.), Amersham, UK; VU University Medical Center (R.O.), Neuroscience Campus Amsterdam, the Netherlands; Department of Neurology (S.P., R.S.) and Memory Clinic (E.S., O.H.), Skåne University Hospital, Lund, Sweden; Department of Imaging and Pathology (D.R.T.), Laboratory of Neuropathology, and Leuven Brain Institute (D.R.T.), Campus Gasthuisberg; and Department of Pathology (D.R.T.), UZ-Leuven, Belgium
| | - Shorena Janelidze
- From the Clinical Memory Research Unit (A.L., J.L., R.O., S.P., S.J., E.S., O.S., R.S., O.H.), Department of Clinical Sciences, Lund University, Malmö; Department of Surgical Sciences, Nuclear Medicine and PET (J.L.), Uppsala University; Hermes Medical Solutions (J.L.), Stockholm, Sweden; GE Healthcare Life Sciences (C.J.B., M.B., G.F.), Amersham, UK; VU University Medical Center (R.O.), Neuroscience Campus Amsterdam, the Netherlands; Department of Neurology (S.P., R.S.) and Memory Clinic (E.S., O.H.), Skåne University Hospital, Lund, Sweden; Department of Imaging and Pathology (D.R.T.), Laboratory of Neuropathology, and Leuven Brain Institute (D.R.T.), Campus Gasthuisberg; and Department of Pathology (D.R.T.), UZ-Leuven, Belgium
| | - Erik Stomrud
- From the Clinical Memory Research Unit (A.L., J.L., R.O., S.P., S.J., E.S., O.S., R.S., O.H.), Department of Clinical Sciences, Lund University, Malmö; Department of Surgical Sciences, Nuclear Medicine and PET (J.L.), Uppsala University; Hermes Medical Solutions (J.L.), Stockholm, Sweden; GE Healthcare Life Sciences (C.J.B., M.B., G.F.), Amersham, UK; VU University Medical Center (R.O.), Neuroscience Campus Amsterdam, the Netherlands; Department of Neurology (S.P., R.S.) and Memory Clinic (E.S., O.H.), Skåne University Hospital, Lund, Sweden; Department of Imaging and Pathology (D.R.T.), Laboratory of Neuropathology, and Leuven Brain Institute (D.R.T.), Campus Gasthuisberg; and Department of Pathology (D.R.T.), UZ-Leuven, Belgium
| | - Olof Strandberg
- From the Clinical Memory Research Unit (A.L., J.L., R.O., S.P., S.J., E.S., O.S., R.S., O.H.), Department of Clinical Sciences, Lund University, Malmö; Department of Surgical Sciences, Nuclear Medicine and PET (J.L.), Uppsala University; Hermes Medical Solutions (J.L.), Stockholm, Sweden; GE Healthcare Life Sciences (C.J.B., M.B., G.F.), Amersham, UK; VU University Medical Center (R.O.), Neuroscience Campus Amsterdam, the Netherlands; Department of Neurology (S.P., R.S.) and Memory Clinic (E.S., O.H.), Skåne University Hospital, Lund, Sweden; Department of Imaging and Pathology (D.R.T.), Laboratory of Neuropathology, and Leuven Brain Institute (D.R.T.), Campus Gasthuisberg; and Department of Pathology (D.R.T.), UZ-Leuven, Belgium
| | - Ruben Smith
- From the Clinical Memory Research Unit (A.L., J.L., R.O., S.P., S.J., E.S., O.S., R.S., O.H.), Department of Clinical Sciences, Lund University, Malmö; Department of Surgical Sciences, Nuclear Medicine and PET (J.L.), Uppsala University; Hermes Medical Solutions (J.L.), Stockholm, Sweden; GE Healthcare Life Sciences (C.J.B., M.B., G.F.), Amersham, UK; VU University Medical Center (R.O.), Neuroscience Campus Amsterdam, the Netherlands; Department of Neurology (S.P., R.S.) and Memory Clinic (E.S., O.H.), Skåne University Hospital, Lund, Sweden; Department of Imaging and Pathology (D.R.T.), Laboratory of Neuropathology, and Leuven Brain Institute (D.R.T.), Campus Gasthuisberg; and Department of Pathology (D.R.T.), UZ-Leuven, Belgium
| | - Oskar Hansson
- From the Clinical Memory Research Unit (A.L., J.L., R.O., S.P., S.J., E.S., O.S., R.S., O.H.), Department of Clinical Sciences, Lund University, Malmö; Department of Surgical Sciences, Nuclear Medicine and PET (J.L.), Uppsala University; Hermes Medical Solutions (J.L.), Stockholm, Sweden; GE Healthcare Life Sciences (C.J.B., M.B., G.F.), Amersham, UK; VU University Medical Center (R.O.), Neuroscience Campus Amsterdam, the Netherlands; Department of Neurology (S.P., R.S.) and Memory Clinic (E.S., O.H.), Skåne University Hospital, Lund, Sweden; Department of Imaging and Pathology (D.R.T.), Laboratory of Neuropathology, and Leuven Brain Institute (D.R.T.), Campus Gasthuisberg; and Department of Pathology (D.R.T.), UZ-Leuven, Belgium
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8
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Applications of Hybrid PET/Magnetic Resonance Imaging in Central Nervous System Disorders. PET Clin 2020; 15:497-508. [DOI: 10.1016/j.cpet.2020.06.004] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/16/2023]
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Beaurain M, Salabert AS, Ribeiro MJ, Arlicot N, Damier P, Le Jeune F, Demonet JF, Payoux P. Innovative Molecular Imaging for Clinical Research, Therapeutic Stratification, and Nosography in Neuroscience. Front Med (Lausanne) 2019; 6:268. [PMID: 31828073 PMCID: PMC6890558 DOI: 10.3389/fmed.2019.00268] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2019] [Accepted: 11/01/2019] [Indexed: 01/06/2023] Open
Abstract
Over the past few decades, several radiotracers have been developed for neuroimaging applications, especially in PET. Because of their low steric hindrance, PET radionuclides can be used to label molecules that are small enough to cross the blood brain barrier, without modifying their biological properties. As the use of 11C is limited by its short physical half-life (20 min), there has been an increasing focus on developing tracers labeled with 18F for clinical use. The first such tracers allowed cerebral blood flow and glucose metabolism to be measured, and the development of molecular imaging has since enabled to focus more closely on specific targets such as receptors, neurotransmitter transporters, and other proteins. Hence, PET and SPECT biomarkers have become indispensable for innovative clinical research. Currently, the treatment options for a number of pathologies, notably neurodegenerative diseases, remain only supportive and symptomatic. Treatments that slow down or reverse disease progression are therefore the subject of numerous studies, in which molecular imaging is proving to be a powerful tool. PET and SPECT biomarkers already make it possible to diagnose several neurological diseases in vivo and at preclinical stages, yielding topographic, and quantitative data about the target. As a result, they can be used for assessing patients' eligibility for new treatments, or for treatment follow-up. The aim of the present review was to map major innovative radiotracers used in neuroscience, and explain their contribution to clinical research. We categorized them according to their target: dopaminergic, cholinergic or serotoninergic systems, β-amyloid plaques, tau protein, neuroinflammation, glutamate or GABA receptors, or α-synuclein. Most neurological disorders, and indeed mental disorders, involve the dysfunction of one or more of these targets. Combinations of molecular imaging biomarkers can afford us a better understanding of the mechanisms underlying disease development over time, and contribute to early detection/screening, diagnosis, therapy delivery/monitoring, and treatment follow-up in both research and clinical settings.
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Affiliation(s)
- Marie Beaurain
- CHU de Toulouse, Toulouse, France.,ToNIC, Toulouse NeuroImaging Center, Inserm U1214, Toulouse, France
| | - Anne-Sophie Salabert
- CHU de Toulouse, Toulouse, France.,ToNIC, Toulouse NeuroImaging Center, Inserm U1214, Toulouse, France
| | - Maria Joao Ribeiro
- UMR 1253, iBrain, Université de Tours, Inserm, Tours, France.,Inserm CIC 1415, University Hospital, Tours, France.,CHRU Tours, Tours, France
| | - Nicolas Arlicot
- UMR 1253, iBrain, Université de Tours, Inserm, Tours, France.,Inserm CIC 1415, University Hospital, Tours, France.,CHRU Tours, Tours, France
| | - Philippe Damier
- Inserm U913, Neurology Department, University Hospital, Nantes, France
| | | | - Jean-François Demonet
- Leenards Memory Centre, Department of Clinical Neuroscience, Centre Hospitalier Universitaire Vaudois, Lausanne, Switzerland
| | - Pierre Payoux
- CHU de Toulouse, Toulouse, France.,ToNIC, Toulouse NeuroImaging Center, Inserm U1214, Toulouse, France
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Ishii K. Diagnostic imaging of dementia with Lewy bodies, frontotemporal lobar degeneration, and normal pressure hydrocephalus. Jpn J Radiol 2019; 38:64-76. [DOI: 10.1007/s11604-019-00881-9] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2019] [Accepted: 09/10/2019] [Indexed: 10/25/2022]
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11
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Shoda C, Kitagawa Y, Shimada H, Yuzawa M, Tateno A, Okubo Y. Relationship of Area of Soft Drusen in Retina with Cerebral Amyloid-β Accumulation and Blood Amyloid-β Level in the Elderly. J Alzheimers Dis 2019; 62:239-245. [PMID: 29439351 DOI: 10.3233/jad-170956] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
BACKGROUND Histopathological studies have confirmed that soft drusen contains amyloid-β (Aβ). OBJECTIVE To examine the relationship between the area of soft drusen in the macular area and cerebral Aβ accumulation or plasma Aβ level in elderly persons without dementia. METHODS Fourteen consecutive patients (18 eyes) aged ≥50 years with macular soft drusen were studied prospectively. From color fundus photographs, the area of soft drusen (pixel) within a 6,000 μm diameter with the macula as center was measured. Standard uptake value ratio (SUVR) was obtained from positron emission tomography using florbetapir, which indicates the ratio of cerebral cortical-to-cerebellar Aβ accumulation. Ratio of plasma Aβ1-42 to Aβ1-40 level was calculated. RESULTS Mean age was 73.3±7.6 years. The soft drusen area was 4.32±2.42 mm2. The SUVR was 1.08±0.15. Plasma Aβ1-42/Aβ1-40 ratio was 0.17±0.08. When SUVR ≥1.10 was defined as positive and <1.10 as negative, the soft drusen area in SUVR-positive patients (6.19±1.14 mm2) was significantly (p = 0.0043) larger than that in SUVR-negative patients (3.13±2.27 mm2). Multivariate regression analysis showed that SUVR positivity correlated with soft drusen area (p = 0.0484) and with Voxel-based Specific Regional Analysis System for Alzheimer's Disease score (p = 0.0360). However, there was no correlation with gender (p = 0.1921), age (p = 0.2361), Alzheimer's Disease Assessment Scale score (p = 0.6310), Mini-Mental State Examination score (p = 0.4246), or plasma Aβ1-42/Aβ1-40 ratio (p = 0.8398). CONCLUSION Among elderly persons without dementia, the area of soft drusen was larger in those with more extensive cerebral Aβ accumulation. The area of soft drusen may be a biomarker of cerebral Aβ accumulation.
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Affiliation(s)
- Chiho Shoda
- Department of Ophthalmology, School of Medicine, Nihon University, Chiyoda-ku, Tokyo, Japan
| | - Yorihisa Kitagawa
- Department of Ophthalmology, School of Medicine, Nihon University, Chiyoda-ku, Tokyo, Japan
| | - Hiroyuki Shimada
- Department of Ophthalmology, School of Medicine, Nihon University, Chiyoda-ku, Tokyo, Japan
| | - Mitsuko Yuzawa
- Department of Ophthalmology, School of Medicine, Nihon University, Chiyoda-ku, Tokyo, Japan
| | - Amane Tateno
- Department of Neuropsychiatry, Nippon Medical School, Bunkyo-ku, Tokyo, Japan
| | - Yoshiro Okubo
- Department of Neuropsychiatry, Nippon Medical School, Bunkyo-ku, Tokyo, Japan
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12
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Asghar M, Hinz R, Herholz K, Carter SF. Dual-phase [18F]florbetapir in frontotemporal dementia. Eur J Nucl Med Mol Imaging 2019; 46:304-311. [PMID: 30569187 PMCID: PMC6333719 DOI: 10.1007/s00259-018-4238-2] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2018] [Accepted: 12/05/2018] [Indexed: 12/14/2022]
Abstract
PURPOSE The PET tracer [18F]florbetapir is a specific fibrillar amyloid-beta (Aβ) biomarker. During the late scan phase (> 40 min), it provides pathological information about Aβ status. Early scan phase (0-10 min) can provide FDG-'like' information. The current investigation tested the feasibility of using florbetapir as a dual-phase biomarker in behavioural variant frontotemporal dementia (bvFTD). METHODS Eight bvFTD patients underwent [18F]florbetapir and [18]FDG-PET scans. Additionally, ten healthy controls and ten AD patients underwent florbetapir-PET only. PET data were acquired dynamically for 60-min post-injection. The bvFTD PET data were used to define an optimal time window, representing blood flow-related pseudo-metabolism ('pseudo-FDG'), of florbetapir data that maximally correlated with the corresponding real FDG SUVR (40-60 min) in a composite neocortical FTD region. RESULTS A 2 to 5-min time window post-injection of the florbetapir-PET data provided the largest correlation (Pearson's r = 0.79, p = 0.02) to the FDG data. The pseudo-FDG images demonstrated strong internal consistency with actual FDG data and were also visually consistent with the bvFTD patients' hypometabolic profiles. The ability to identify bvFTD from blind visual rating of pseudo-FDG images was consistent with previous reports using FDG data (sensitivity = 75%, specificity = 85%). CONCLUSIONS This investigation demonstrates that early phase florbetapir uptake shows a reduction of frontal lobe perfusion in bvFTD, similar to metabolic findings with FDG. Thus, dynamic florbetapir scans can serve as a dual-phase biomarker in dementia patients to distinguish FTD from AD and cognitively normal elderly, removing the need for a separate FDG-PET scan in challenging dementia cases.
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Affiliation(s)
- Michael Asghar
- Wolfson Molecular Imaging Centre, Faculty of Medicine, Biology and Health, University of Manchester, 27 Palatine Road, Manchester, M20 3LJ, UK
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, NG7 2RD, UK
| | - Rainer Hinz
- Wolfson Molecular Imaging Centre, Faculty of Medicine, Biology and Health, University of Manchester, 27 Palatine Road, Manchester, M20 3LJ, UK
| | - Karl Herholz
- Wolfson Molecular Imaging Centre, Faculty of Medicine, Biology and Health, University of Manchester, 27 Palatine Road, Manchester, M20 3LJ, UK
| | - Stephen F Carter
- Wolfson Molecular Imaging Centre, Faculty of Medicine, Biology and Health, University of Manchester, 27 Palatine Road, Manchester, M20 3LJ, UK.
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Sarikaya I, Sarikaya A, Elgazzar AH. Current Status of 18F-FDG PET Brain Imaging in Patients with Dementia. J Nucl Med Technol 2018; 46:362-367. [DOI: 10.2967/jnmt.118.210237] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2018] [Accepted: 05/07/2018] [Indexed: 11/16/2022] Open
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Frontal Variant Alzheimer Disease or Frontotemporal Lobe Degeneration With Incidental Amyloidosis? Alzheimer Dis Assoc Disord 2018; 30:183-5. [PMID: 26583500 DOI: 10.1097/wad.0000000000000123] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
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Martínez G, Vernooij RWM, Fuentes Padilla P, Zamora J, Bonfill Cosp X, Flicker L. 18F PET with florbetapir for the early diagnosis of Alzheimer's disease dementia and other dementias in people with mild cognitive impairment (MCI). Cochrane Database Syst Rev 2017; 11:CD012216. [PMID: 29164603 PMCID: PMC6486090 DOI: 10.1002/14651858.cd012216.pub2] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
BACKGROUND 18F-florbetapir uptake by brain tissue measured by positron emission tomography (PET) is accepted by regulatory agencies like the Food and Drug Administration (FDA) and the European Medicine Agencies (EMA) for assessing amyloid load in people with dementia. Its added value is mainly demonstrated by excluding Alzheimer's pathology in an established dementia diagnosis. However, the National Institute on Aging and Alzheimer's Association (NIA-AA) revised the diagnostic criteria for Alzheimer's disease and confidence in the diagnosis of mild cognitive impairment (MCI) due to Alzheimer's disease may be increased when using amyloid biomarkers tests like 18F-florbetapir. These tests, added to the MCI core clinical criteria, might increase the diagnostic test accuracy (DTA) of a testing strategy. However, the DTA of 18F-florbetapir to predict the progression from MCI to Alzheimer's disease dementia (ADD) or other dementias has not yet been systematically evaluated. OBJECTIVES To determine the DTA of the 18F-florbetapir PET scan for detecting people with MCI at time of performing the test who will clinically progress to ADD, other forms of dementia (non-ADD), or any form of dementia at follow-up. SEARCH METHODS This review is current to May 2017. We searched MEDLINE (OvidSP), Embase (OvidSP), PsycINFO (OvidSP), BIOSIS Citation Index (Thomson Reuters Web of Science), Web of Science Core Collection, including the Science Citation Index (Thomson Reuters Web of Science) and the Conference Proceedings Citation Index (Thomson Reuters Web of Science), LILACS (BIREME), CINAHL (EBSCOhost), ClinicalTrials.gov (https://clinicaltrials.gov), and the World Health Organization International Clinical Trials Registry Platform (WHO ICTRP) (http://www.who.int/ictrp/search/en/). We also searched ALOIS, the Cochrane Dementia & Cognitive Improvement Group's specialised register of dementia studies (http://www.medicine.ox.ac.uk/alois/). We checked the reference lists of any relevant studies and systematic reviews, and performed citation tracking using the Science Citation Index to identify any additional relevant studies. No language or date restrictions were applied to the electronic searches. SELECTION CRITERIA We included studies that had prospectively defined cohorts with any accepted definition of MCI at time of performing the test and the use of 18F-florbetapir scan to evaluate the DTA of the progression from MCI to ADD or other forms of dementia. In addition, we only selected studies that applied a reference standard for Alzheimer's dementia diagnosis, for example, National Institute of Neurological and Communicative Disorders and Stroke and the Alzheimer's Disease and Related Disorders Association (NINCDS-ADRDA) or Diagnostic and Statistical Manual of Mental Disorders-IV (DSM-IV) criteria. DATA COLLECTION AND ANALYSIS We screened all titles and abstracts identified in electronic-database searches. Two review authors independently selected studies for inclusion and extracted data to create two-by-two tables, showing the binary test results cross-classified with the binary reference standard. We used these data to calculate sensitivities, specificities, and their 95% confidence intervals. Two independent assessors performed quality assessment using the QUADAS-2 tool plus some additional items to assess the methodological quality of the included studies. MAIN RESULTS We included three studies, two of which evaluated the progression from MCI to ADD, and one evaluated the progression from MCI to any form of dementia.Progression from MCI to ADD was evaluated in 448 participants. The studies reported data on 401 participants with 1.6 years of follow-up and in 47 participants with three years of follow-up. Sixty-one (15.2%) participants converted at 1.6 years follow-up; nine (19.1%) participants converted at three years of follow-up.Progression from MCI to any form of dementia was evaluated in five participants with 1.5 years of follow-up, with three (60%) participants converting to any form of dementia.There were concerns regarding applicability in the reference standard in all three studies. Regarding the domain of flow and timing, two studies were considered at high risk of bias. MCI to ADD;Progression from MCI to ADD in those with a follow-up between two to less than four years had a sensitivity of 67% (95% CI 30 to 93) and a specificity of 71% (95% CI 54 to 85) by visual assessment (n = 47, 1 study).Progression from MCI to ADD in those with a follow-up between one to less than two years had a sensitivity of 89% (95% CI 78 to 95) and a specificity of 58% (95% CI 53 to 64) by visual assessment, and a sensitivity of 87% (95% CI 76 to 94) and a specificity of 51% (95% CI 45 to 56) by quantitative assessment by the standardised uptake value ratio (SUVR)(n = 401, 1 study). MCI to any form of dementia;Progression from MCI to any form of dementia in those with a follow-up between one to less than two years had a sensitivity of 67% (95% CI 9 to 99) and a specificity of 50% (95% CI 1 to 99) by visual assessment (n = 5, 1 study). MCI to any other forms of dementia (non-ADD);There was no information regarding the progression from MCI to any other form of dementia (non-ADD). AUTHORS' CONCLUSIONS Although sensitivity was good in one included study, considering the poor specificity and the limited data available in the literature, we cannot recommend routine use of 18F-florbetapir PET in clinical practice to predict the progression from MCI to ADD.Because of the poor sensitivity and specificity, limited number of included participants, and the limited data available in the literature, we cannot recommend its routine use in clinical practice to predict the progression from MCI to any form of dementia.Because of the high financial costs of 18F-florbetapir, clearly demonstrating the DTA and standardising the process of this modality are important prior to its wider use.
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Affiliation(s)
- Gabriel Martínez
- Iberoamerican Cochrane CentreC/ Sant Antoni Maria Claret 167Pavelló 18 Planta 0BarcelonaBarcelonaSpain08025
- Universidad de AntofagastaFaculty of Medicine and DentistryAntofagastaChile
- Institut Català de Neurociències AplicadesAlzheimer Research Center and Memory Clinic of Fundació ACEBarcelonaSpain
| | - Robin WM Vernooij
- Iberoamerican Cochrane CentreC/ Sant Antoni Maria Claret 167Pavelló 18 Planta 0BarcelonaBarcelonaSpain08025
| | - Paulina Fuentes Padilla
- Iberoamerican Cochrane CentreC/ Sant Antoni Maria Claret 167Pavelló 18 Planta 0BarcelonaBarcelonaSpain08025
- Universidad de AntofagastaFaculty of Medicine and DentistryAntofagastaChile
| | - Javier Zamora
- Ramon y Cajal Institute for Health Research (IRYCIS), CIBER Epidemiology and Public Health (CIBERESP), Madrid (Spain) and Women's Health Research Unit, Centre for Primary Care and Public Health, Queen Mary University of LondonClinical Biostatistics UnitLondonMadridUK
| | - Xavier Bonfill Cosp
- CIBER Epidemiología y Salud Pública (CIBERESP)Iberoamerican Cochrane Centre, Biomedical Research Institute Sant Pau (IIB Sant Pau)Sant Antoni Maria Claret 167Pavilion 18BarcelonaCatalunyaSpain08025
- Universitat Autònoma de BarcelonaSant Antoni Maria Claret, 167Pavilion 18 (D‐13)BarcelonaCatalunyaSpain08025
| | - Leon Flicker
- University of Western AustraliaWestern Australian Centre for Health & Ageing ‐ WACHACrawleyPerthWestern AustraliaAustralia6014
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Martínez G, Vernooij RWM, Fuentes Padilla P, Zamora J, Flicker L, Bonfill Cosp X. 18F PET with flutemetamol for the early diagnosis of Alzheimer's disease dementia and other dementias in people with mild cognitive impairment (MCI). Cochrane Database Syst Rev 2017; 11:CD012884. [PMID: 29164602 PMCID: PMC6486287 DOI: 10.1002/14651858.cd012884] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
BACKGROUND 18F-flutemetamol uptake by brain tissue, measured by positron emission tomography (PET), is accepted by regulatory agencies like the Food and Drug Administration (FDA) and the European Medicine Agencies (EMA) for assessing amyloid load in people with dementia. Its added value is mainly demonstrated by excluding Alzheimer's pathology in an established dementia diagnosis. However, the National Institute on Aging and Alzheimer's Association (NIA-AA) revised the diagnostic criteria for Alzheimer's disease and the confidence in the diagnosis of mild cognitive impairment (MCI) due to Alzheimer's disease may be increased when using some amyloid biomarkers tests like 18F-flutemetamol. These tests, added to the MCI core clinical criteria, might increase the diagnostic test accuracy (DTA) of a testing strategy. However, the DTA of 18F-flutemetamol to predict the progression from MCI to Alzheimer's disease dementia (ADD) or other dementias has not yet been systematically evaluated. OBJECTIVES To determine the DTA of the 18F-flutemetamol PET scan for detecting people with MCI at time of performing the test who will clinically progress to ADD, other forms of dementia (non-ADD) or any form of dementia at follow-up. SEARCH METHODS The most recent search for this review was performed in May 2017. We searched MEDLINE (OvidSP), Embase (OvidSP), PsycINFO (OvidSP), BIOSIS Citation Index (Thomson Reuters Web of Science), Web of Science Core Collection, including the Science Citation Index (Thomson Reuters Web of Science) and the Conference Proceedings Citation Index (Thomson Reuters Web of Science), LILACS (BIREME), CINAHL (EBSCOhost), ClinicalTrials.gov (https://clinicaltrials.gov), and the World Health Organization International Clinical Trials Registry Platform (WHO ICTRP) (http://www.who.int/ictrp/search/en/). We also searched ALOIS, the Cochrane Dementia & Cognitive Improvement Group's specialised register of dementia studies (http://www.medicine.ox.ac.uk/alois/). We checked the reference lists of any relevant studies and systematic reviews, and performed citation tracking using the Science Citation Index to identify any additional relevant studies. No language or date restrictions were applied to the electronic searches. SELECTION CRITERIA We included studies that had prospectively defined cohorts with any accepted definition of MCI at time of performing the test and the use of 18F-flutemetamol scan to evaluate the DTA of the progression from MCI to ADD or other forms of dementia. In addition, we only selected studies that applied a reference standard for Alzheimer's dementia diagnosis, for example, National Institute of Neurological and Communicative Disorders and Stroke and the Alzheimer's Disease and Related Disorders Association (NINCDS-ADRDA) or Diagnostic and Statistical Manual of Mental Disorders-IV (DSM-IV) criteria. DATA COLLECTION AND ANALYSIS We screened all titles and abstracts identified in electronic-database searches. Two review authors independently selected studies for inclusion and extracted data to create two-by-two tables, showing the binary test results cross-classified with the binary reference standard. We used these data to calculate sensitivities, specificities, and their 95% confidence intervals. Two independent assessors performed quality assessment using the QUADAS-2 tool plus some additional items to assess the methodological quality of the included studies. MAIN RESULTS Progression from MCI to ADD was evaluated in 243 participants from two studies. The studies reported data on 19 participants with two years of follow-up and on 224 participants with three years of follow-up. Nine (47.4%) participants converted at two years follow-up and 81 (36.2%) converted at three years of follow-up.There were concerns about participant selection and sampling in both studies. The index test domain in one study was considered unclear and in the second study it was considered at low risk of bias. For the reference standard domain, one study was considered at low risk and the second study was considered to have an unclear risk of bias. Regarding the domains of flow and timing, both studies were considered at high risk of bias. MCI to ADD;Progression from MCI to ADD at two years of follow-up had a sensitivity of 89% (95% CI 52 to 100) and a specificity of 80% (95% CI 44 to 97) by quantitative assessment by SUVR (n = 19, 1 study).Progression from MCI to ADD at three years of follow-up had a sensitivity of 64% (95% CI 53 to 75) and a specificity of 69% (95% CI 60 to 76) by visual assessment (n = 224, 1 study).There was no information regarding the other two objectives in this systematic review (SR): progression from MCI to other forms of dementia and progression to any form of dementia at follow-up. AUTHORS' CONCLUSIONS Due to the varying sensitivity and specificity for predicting the progression from MCI to ADD and the limited data available, we cannot recommend routine use of 18F-flutemetamol in clinical practice. 18F-flutemetamol has high financial costs; therefore, clearly demonstrating its DTA and standardising the process of the 18F-flutemetamol modality is important prior to its wider use.
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Affiliation(s)
- Gabriel Martínez
- Iberoamerican Cochrane CentreC/ Sant Antoni Maria Claret 167Pavelló 18 Planta 0BarcelonaBarcelonaSpain08025
- Universidad de AntofagastaFaculty of Medicine and DentistryAntofagastaChile
- Institut Català de Neurociències AplicadesAlzheimer Research Center and Memory Clinic of Fundació ACEBarcelonaSpain
| | - Robin WM Vernooij
- Iberoamerican Cochrane CentreC/ Sant Antoni Maria Claret 167Pavelló 18 Planta 0BarcelonaBarcelonaSpain08025
| | - Paulina Fuentes Padilla
- Iberoamerican Cochrane CentreC/ Sant Antoni Maria Claret 167Pavelló 18 Planta 0BarcelonaBarcelonaSpain08025
- Universidad de AntofagastaFaculty of Medicine and DentistryAntofagastaChile
| | - Javier Zamora
- Ramon y Cajal Institute for Health Research (IRYCIS), CIBER Epidemiology and Public Health (CIBERESP), Madrid (Spain) and Women's Health Research Unit, Centre for Primary Care and Public Health, Queen Mary University of LondonClinical Biostatistics UnitLondonMadridUK
| | - Leon Flicker
- University of Western AustraliaWestern Australian Centre for Health & Ageing ‐ WACHACrawleyPerthWestern AustraliaAustralia6014
| | - Xavier Bonfill Cosp
- CIBER Epidemiología y Salud Pública (CIBERESP)Iberoamerican Cochrane Centre, Biomedical Research Institute Sant Pau (IIB Sant Pau)Sant Antoni Maria Claret 167Pavilion 18BarcelonaCatalunyaSpain08025
- Universitat Autònoma de BarcelonaSant Antoni Maria Claret, 167Pavilion 18 (D‐13)BarcelonaCatalunyaSpain08025
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Alves GS, de Carvalho LDA, Sudo FK, Briand L, Laks J, Engelhardt E. A panel of clinical and neuropathological features of cerebrovascular disease through the novel neuroimaging methods. Dement Neuropsychol 2017; 11:343-355. [PMID: 29354214 PMCID: PMC5769992 DOI: 10.1590/1980-57642016dn11-040003] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
UNLABELLED The last decade has witnessed substantial progress in acquiring diagnostic biomarkers for the diagnostic workup of cerebrovascular disease (CVD). Advanced neuroimaging methods not only provide a strategic contribution for the differential diagnosis of vascular dementia (VaD) and vascular cognitive impairment (VCI), but also help elucidate the pathophysiological mechanisms ultimately leading to small vessel disease (SVD) throughout its course. OBJECTIVE In this review, the novel imaging methods, both structural and metabolic, were summarized and their impact on the diagnostic workup of age-related CVD was analysed. Methods: An electronic search between January 2010 and 2017 was carried out on PubMed/MEDLINE, Institute for Scientific Information Web of Knowledge and EMBASE. RESULTS The use of full functional multimodality in simultaneous Magnetic Resonance (MR)/Positron emission tomography (PET) may potentially improve the clinical characterization of VCI-VaD; for structural imaging, MRI at 3.0 T enables higher-resolution scanning with greater imaging matrices, thinner slices and more detail on the anatomical structure of vascular lesions. CONCLUSION Although the importance of most of these techniques in the clinical setting has yet to be recognized, there is great expectancy in achieving earlier and more refined therapeutic interventions for the effective management of VCI-VaD.
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Affiliation(s)
| | | | - Felipe Kenji Sudo
- Departamento de Psicologia, Pontifícia Universidade Católica do Rio de Janeiro, RJ, Brazil
- Instituto D'Or de Ensino e Pesquisa, Rio de Janeiro, RJ, Brazil
| | - Lucas Briand
- Departamento de Medicina Interna, Universidade Federal do Ceará, CE, Brazil
| | - Jerson Laks
- Instituto de Psiquiatria, Universidade Federal do Rio de Janeiro, RJ, Brazil
- Programa de Pós-Graduação em Biomedicina Translacional (BIOTRANS), Unigranrio, Duque de Caxias, RJ, Brazil
| | - Eliasz Engelhardt
- Setor de Neurologia Cognitiva e do Comportamento, Instituto de Neurologia Deolindo Couto (INDC-CDA/IPUB), Rio de Janeiro, RJ, Brazil
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Del Sole A, Malaspina S, Magenta Biasina A. Magnetic resonance imaging and positron emission tomography in the diagnosis of neurodegenerative dementias. FUNCTIONAL NEUROLOGY 2017; 31:205-215. [PMID: 28072381 DOI: 10.11138/fneur/2016.31.4.205] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
Abstract
Neuroimaging, both with magnetic resonance imaging (MRI) and positron emission tomography (PET), has gained a pivotal role in the diagnosis of primary neurodegenerative diseases. These two techniques are used as biomarkers of both pathology and progression of Alzheimer's disease (AD) and to differentiate AD from other neurodegenerative diseases. MRI is able to identify structural changes including patterns of atrophy characterizing neurodegenerative diseases, and to distinguish these from other causes of cognitive impairment, e.g. infarcts, space-occupying lesions and hydrocephalus. PET is widely used to identify regional patterns of glucose utilization, since distinct patterns of distribution of cerebral glucose metabolism are related to different subtypes of neurodegenerative dementia. The use of PET in mild cognitive impairment, though controversial, is deemed helpful for predicting conversion to dementia and the dementia clinical subtype. Recently, new radiopharmaceuticals for the in vivo imaging of amyloid burden have been licensed and more tracers are being developed for the assessment of tauopathies and inflammatory processes, which may underlie the onset of the amyloid cascade. At present, the cerebral amyloid burden, imaged with PET, may help to exclude the presence of AD as well as forecast its possible onset. Finally PET imaging may be particularly useful in ongoing clinical trials for the development of dementia treatments. In the near future, the use of the above methods, in accordance with specific guidelines, along with the use of effective treatments will likely lead to more timely and successful treatment of neurodegenerative dementias.
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Quantitation of PET signal as an adjunct to visual interpretation of florbetapir imaging. Eur J Nucl Med Mol Imaging 2017; 44:825-837. [DOI: 10.1007/s00259-016-3601-4] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2016] [Accepted: 12/16/2016] [Indexed: 02/03/2023]
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Tosun D, Schuff N, Rabinovici GD, Ayakta N, Miller BL, Jagust W, Kramer J, Weiner MM, Rosen HJ. Diagnostic utility of ASL-MRI and FDG-PET in the behavioral variant of FTD and AD. Ann Clin Transl Neurol 2016; 3:740-751. [PMID: 27752510 PMCID: PMC5048385 DOI: 10.1002/acn3.330] [Citation(s) in RCA: 37] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2016] [Revised: 06/06/2016] [Accepted: 06/08/2016] [Indexed: 12/12/2022] Open
Abstract
Objective To compare the values of arterial spin‐labeled (ASL) MRI and fluorodeoxyglucose (FDG) PET in the diagnosis of behavioral variant of frontotemporal dementia (bvFTD) and Alzheimer's disease (AD). Methods Partial least squares logistic regression was used to identify voxels with diagnostic value in cerebral blood flow (CBF) and cerebral metabolic rate of glucose (CMRgl) maps from patients with bvFTD (n = 32) and AD (n = 28), who were compared with each other and with cognitively normal controls (CN, n = 15). Diagnostic values of these maps were compared with each other. Results Regions that differentiated each disorder from controls were similar for CBF and CMRgl. For differentiating AD from CN, the areas under the curve (AUC) for CBF (0.89) and CMRgl (0.91) were similar, with similar sensitivity (CBF: 86%, CMRgl: 78%) and specificity (CBF: 92%, CMRgl: 100%). Likewise, for differentiating bvFTD from CN performances of CBF (AUC = 0.83) and CMRgl (AUC = 0.85) were equivalent, with similar sensitivity (CBF: 78%, CMRgl: 79%) and specificity (CBF: 92%, CMRgl: 100%). In differentiating bvFTD from AD, classification was again similar for CBF (AUC = 0.87) and CMRgl (AUC = 0.79), as were sensitivity (CBF: 83%, CMRgl: 89%) and specificity (CBF: 93%, CMRgl: 78%). None of the differences in any performance measure were statistically significant. Interpretation ASL‐MRI has similar diagnostic utility as FDG‐PET in the diagnosis of AD and bvFTD. Continued development of ASL‐MRI as a diagnostic tool for neurodegenerative dementias is warranted.
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Affiliation(s)
- Duygu Tosun
- Department of Radiology and Biomedical Imaging University of California San Francisco California
| | - Norbert Schuff
- Department of Radiology and Biomedical Imaging University of California San Francisco California
| | - Gil D Rabinovici
- Memory and Aging Center Department of Neurology University of California San Francisco California
| | - Nagehan Ayakta
- Memory and Aging Center Department of Neurology University of California San Francisco California; School of Public Health University of California Berkeley California
| | - Bruce L Miller
- Memory and Aging Center Department of Neurology University of California San Francisco California
| | - William Jagust
- School of Public Health University of California Berkeley California
| | - Joel Kramer
- Memory and Aging Center Department of Neurology University of California San Francisco California
| | - Michael M Weiner
- Department of Radiology and Biomedical Imaging University of California San Francisco California
| | - Howard J Rosen
- Memory and Aging Center Department of Neurology University of California San Francisco California
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Vijverberg EG, Wattjes MP, Dols A, Krudop WA, Möller C, Peters A, Kerssens CJ, Gossink F, Prins ND, Stek ML, Scheltens P, van Berckel BN, Barkhof F, Pijnenburg YA. Diagnostic Accuracy of MRI and Additional [18F]FDG-PET for Behavioral Variant Frontotemporal Dementia in Patients with Late Onset Behavioral Changes. J Alzheimers Dis 2016; 53:1287-97. [DOI: 10.3233/jad-160285] [Citation(s) in RCA: 41] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Affiliation(s)
- Everard G.B. Vijverberg
- Alzheimer Centre and Department of Neurology, Neuroscience Campus Amsterdam, VU University Medical Centre, Amsterdam, The Netherlands
- Department of Neurology, Haga Ziekenhuis, The Hague, The Netherlands
| | - Mike P. Wattjes
- Department of Radiology & Nuclear Medicine, VU University Medical Centre, Amsterdam, The Netherlands
| | - Annemiek Dols
- Department of Old Age Psychiatry, GGZ InGeest, Amsterdam, The Netherlands
| | - Welmoed A. Krudop
- Alzheimer Centre and Department of Neurology, Neuroscience Campus Amsterdam, VU University Medical Centre, Amsterdam, The Netherlands
| | - Christiane Möller
- Alzheimer Centre and Department of Neurology, Neuroscience Campus Amsterdam, VU University Medical Centre, Amsterdam, The Netherlands
- Leiden Institute for Brain and Cognition (LIBC), Institute of Psychology, Leiden University, Leiden, The Netherlands
| | - Anne Peters
- Alzheimer Centre and Department of Neurology, Neuroscience Campus Amsterdam, VU University Medical Centre, Amsterdam, The Netherlands
| | - Cora J. Kerssens
- Department of Old Age Psychiatry, GGZ InGeest, Amsterdam, The Netherlands
| | - Flora Gossink
- Department of Old Age Psychiatry, GGZ InGeest, Amsterdam, The Netherlands
| | - Niels D. Prins
- Alzheimer Centre and Department of Neurology, Neuroscience Campus Amsterdam, VU University Medical Centre, Amsterdam, The Netherlands
| | - Max L. Stek
- Department of Old Age Psychiatry, GGZ InGeest, Amsterdam, The Netherlands
| | - Philip Scheltens
- Alzheimer Centre and Department of Neurology, Neuroscience Campus Amsterdam, VU University Medical Centre, Amsterdam, The Netherlands
| | - Bart N.M. van Berckel
- Department of Nuclear Medicine & PET research, VU University Medical Centre, Amsterdam, The Netherlands
| | - Frederik Barkhof
- Department of Radiology & Nuclear Medicine, VU University Medical Centre, Amsterdam, The Netherlands
| | - Yolande A.L. Pijnenburg
- Alzheimer Centre and Department of Neurology, Neuroscience Campus Amsterdam, VU University Medical Centre, Amsterdam, The Netherlands
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Martínez G, Flicker L, Vernooij RWM, Fuentes Padilla P, Zamora J, Roqué i Figuls M, Urrútia G, Bonfill Cosp X. 18F PET ligands for the early diagnosis of Alzheimer’s disease dementia and other dementias in people with mild cognitive impairment (MCI). THE COCHRANE DATABASE OF SYSTEMATIC REVIEWS 2016. [DOI: 10.1002/14651858.cd012216] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Affiliation(s)
- Gabriel Martínez
- Iberoamerican Cochrane Centre; C/ Sant Antoni Maria Claret 167 Pavelló 18 Planta 0 Barcelona Barcelona Spain 08025
| | - Leon Flicker
- University of Western Australia; Western Australian Centre for Health & Ageing - WACHA; Crawley Perth Western Australia Australia 6014
| | - Robin WM Vernooij
- Iberoamerican Cochrane Centre; C/ Sant Antoni Maria Claret 167 Pavelló 18 Planta 0 Barcelona Barcelona Spain 08025
| | - Paulina Fuentes Padilla
- Iberoamerican Cochrane Centre; C/ Sant Antoni Maria Claret 167 Pavelló 18 Planta 0 Barcelona Barcelona Spain 08025
| | - Javier Zamora
- Ramon y Cajal Institute for Health Research (IRYCIS), CIBER Epidemiology and Public Health (CIBERESP), Madrid (Spain) and Queen Mary University of London; Clinical Biostatistics Unit; Ctra. Colmenar km 9,100 Madrid Madrid Spain 28034
| | - Marta Roqué i Figuls
- CIBER Epidemiología y Salud Pública (CIBERESP); Iberoamerican Cochrane Centre - Biomedical Research Institute Sant Pau (IIB Sant Pau); Sant Antoni Maria Claret 171 Edifici Casa de Convalescència Barcelona Catalunya Spain 08041
| | - Gerard Urrútia
- CIBER Epidemiología y Salud Pública (CIBERESP); Iberoamerican Cochrane Centre - Biomedical Research Institute Sant Pau (IIB Sant Pau); Sant Antoni Maria Claret 171 Edifici Casa de Convalescència Barcelona Catalunya Spain 08041
| | - Xavier Bonfill Cosp
- CIBER Epidemiología y Salud Pública (CIBERESP), Spain; Iberoamerican Cochrane Centre - Biomedical Research Institute Sant Pau (IIB Sant Pau); Sant Antoni Maria Claret, 167 Pavilion 18 (D-13) Barcelona Catalunya Spain 08025
- Universitat Autònoma de Barcelona; Sant Antoni Maria Claret, 167 Pavilion 18 (D-13) Barcelona Catalunya Spain 08025
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Recent Developments in Combined PET/MRI. CURRENT RADIOLOGY REPORTS 2016. [DOI: 10.1007/s40134-016-0149-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
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Fu CL, Hsu LS, Liao YF, Hu MK. New Hydroxyquinoline-Based Derivatives as Potent Modulators of Amyloid-β Aggregations. Arch Pharm (Weinheim) 2016; 349:327-41. [PMID: 27027880 DOI: 10.1002/ardp.201500453] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2015] [Revised: 02/16/2016] [Accepted: 02/23/2016] [Indexed: 12/26/2022]
Abstract
Copper and zinc have been found to contribute to the burden of amyloid-β (Aβ) aggregations in neurodegenerative Alzheimer's disease (AD). Dysregulation of these metals leads to the generation of reactive oxygen species (ROS) and eventually results in oxidative damage and accumulation of the Aβ peptide, which are the key elements of the disease. Aiming to pursue the discovery of new modulators for the disease, we here rationally focused on conjugating the core hydroxyquinoline of the metal-protein attenuating compound PBT2 and the N-methylanilide analogous moiety of the Aβ imaging agent to build a new type of multi-target modulators of Aβ aggregations. We found that the N,N-dimethylanilinyl imines 7a, 8a, and the corresponding amines 7b, 8b exerted efficient inhibition of Cu(2+) - or Zn(2+) -induced Aβ aggregations and significant disassembly of metal-mediated Aβ aggregated fibrils. Further, 7a and 7b also exhibited significant ROC scavenging effects compared to PBT2. The results suggested that 7a and 7b are promising lead compounds for the development of a new therapy for AD.
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Affiliation(s)
- Chin-Lan Fu
- School of Pharmacy, National Defense Medical Center, Taipei, Taiwan
| | - Li-Shin Hsu
- School of Pharmacy, National Defense Medical Center, Taipei, Taiwan
| | - Yung-Feng Liao
- Laboratories of Molecular Neurobiology, Institute of Cellular and Organismic Biology, Academia Sinica, Taipei, Taiwan
| | - Ming-Kuan Hu
- School of Pharmacy, National Defense Medical Center, Taipei, Taiwan
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Masdeu JC, Pascual B. Genetic and degenerative disorders primarily causing dementia. HANDBOOK OF CLINICAL NEUROLOGY 2016; 135:525-564. [PMID: 27432682 DOI: 10.1016/b978-0-444-53485-9.00026-x] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
Neuroimaging comprises a powerful set of instruments to diagnose the different causes of dementia, clarify their neurobiology, and monitor their treatment. Magnetic resonance imaging (MRI) depicts volume changes with neurodegeneration and inflammation, as well as abnormalities in functional and structural connectivity. MRI arterial spin labeling allows for the quantification of regional cerebral blood flow, characteristically altered in Alzheimer's disease, diffuse Lewy-body disease, and the frontotemporal dementias. Positron emission tomography allows for the determination of regional metabolism, with similar abnormalities as flow, and for the measurement of β-amyloid and abnormal tau deposition in the brain, as well as regional inflammation. These instruments allow for the quantification in vivo of most of the pathologic features observed in disorders causing dementia. Importantly, they allow for the longitudinal study of these abnormalities, having revealed, for instance, that the deposition of β-amyloid in the brain can antecede by decades the onset of dementia. Thus, a therapeutic window has been opened and the efficacy of immunotherapies directed at removing β-amyloid from the brain of asymptomatic individuals is currently being tested. Tau and inflammation imaging, still in their infancy, combined with genomics, should provide powerful insights into these disorders and facilitate their treatment.
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Affiliation(s)
- Joseph C Masdeu
- Department of Neurology, Houston Methodist Hospital, Houston, TX, USA.
| | - Belen Pascual
- Department of Neurology, Houston Methodist Hospital, Houston, TX, USA
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Lai X, Ren J, Lu Y, Cui S, Chen J, Huang Y, Tang C, Shan B, Nie B. Effects of acupuncture at HT7 on glucose metabolism in a rat model of Alzheimer's disease: an 18F-FDG-PET study. Acupunct Med 2015; 34:215-22. [PMID: 26654890 PMCID: PMC4941154 DOI: 10.1136/acupmed-2015-010865] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/08/2015] [Indexed: 12/21/2022]
Abstract
Objective To explore the effects of acupuncture at HT7 on different cerebral regions in a rat model of Alzheimer's disease (AD) with the application of 18F-2-fluoro-deoxy-D-glucose positron emission tomography (FDG-PET). Methods Sixty Wistar rats were included after undergoing a Y-maze electric sensitivity test. Ten rats were used as a healthy control group. The remaining 50 rats were injected stereotaxically with ibotenic acid into the right nucleus basalis magnocellularis and injected intraperitoneally with D-galactose. AD was successfully modelled in 36 rats, which were randomly divided into three groups (n=12 each): the AD group, which remained untreated; the AD+HT7 group, which received 20 sessions of acupuncture at HT7 over 1 month; and the AD+Sham group, which received acupuncture at a distant non-acupuncture point. Total reaction time (TRT) was measured by Y-maze and 18F-FDG-PET scans were conducted on day 1 and 30. PET images were processed with Statistical Parametric Mapping 8.0. Results Pre-treatment, TRT was greater in all AD groups versus controls (mean±SD 24.10±2.48 vs 41.34±5.00 s). Post-treatment, TRT was shortened in AD+HT7 versus AD+Sham and AD groups (p<0.0001, two-way analysis of variance). Glucose metabolic activity in the hippocampus, thalamus, hypothalamus, frontal lobe, and temporal lobe was decreased in AD rats compared with healthy controls and relatively elevated after HT7 acupuncture. Compared with sham acupuncture, HT7 needling had a greater positive influence on brain glucose metabolism. Conclusions Needling at HT7 can improve memory ability and cerebral glucose metabolic activity of the hippocampus, thalamus, hypothalamus, and frontal/temporal lobes in an AD rat model.
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Affiliation(s)
- Xinsheng Lai
- Department of Acupuncture and Massage, Guangzhou University of Traditional Chinese Medicine, Guangzhou, China
| | - Jie Ren
- School of Traditional Chinese Medicine, Southern Medical University, Guangzhou, China
| | - Yangjia Lu
- School of Traditional Chinese Medicine, Southern Medical University, Guangzhou, China
- Department of Traditional Chinese Medicine, Guangdong Medical College, Dongguan, China
| | - Shaoyang Cui
- Department of Acupuncture and Massage, Guangzhou University of Traditional Chinese Medicine, Guangzhou, China
- Department of Acupuncture and Moxibustion, Futian TCM Hospital, Shenzhen, China
| | - Junqi Chen
- School of Traditional Chinese Medicine, Southern Medical University, Guangzhou, China
- Department of Rehabilitation, The 3rd affiliated Hospital of Southern Medical University, Guangzhou, China
| | - Yong Huang
- School of Traditional Chinese Medicine, Southern Medical University, Guangzhou, China
| | - Chunzhi Tang
- Department of Acupuncture and Massage, Guangzhou University of Traditional Chinese Medicine, Guangzhou, China
| | - Baoci Shan
- Key Laboratory of Nuclear Analytical Techniques, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing, China
| | - Bingbing Nie
- Key Laboratory of Nuclear Analytical Techniques, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing, China
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Machulla HJ. Alzheimer Disease: Approaches to Early Diagnosis and High-Accuracy Imaging. J Nucl Med 2015; 56:1466-7. [DOI: 10.2967/jnumed.115.162891] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
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Matsuzono K, Hishikawa N, Yamashita T, Ohta Y, Sato K, Kono S, Deguchi K, Morihara R, Abe K. Comprehensive Clinical Evaluations of Frontotemporal Dementia Contrasting to Alzheimer’s Disease (oFTD Study). J Alzheimers Dis 2015; 48:279-86. [DOI: 10.3233/jad-150416] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
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Abstract
In vivo imaging of brain amyloid using positron emission tomography (PET) scanning is widely used in research studies of dementia, with three amyloid PET ligands being licenced for clinical use. The main clinical use of PET is to help confirm or exclude the likely diagnosis of Alzheimer's disease in challenging cases, where diagnostic uncertainty remains after current clinical and investigative work up. Whilst diagnostically valuable in such select cases, much wider clinical adoption, especially for very early disease, will be limited by both cost and the lack of a currently effective disease-modifying treatment that requires such early case identification. The use of amyloid imaging to appropriately stratify subjects for prognostic studies and therapeutic trials should increase the efficiency and potentially shorten the time of such studies, and its use combined with other biomarkers and genetics will likely lead to new ways of defining and classifying the dementias.
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Affiliation(s)
- John T O'Brien
- Department of Psychiatry, University of Cambridge, Box 189, Level E4 Cambridge Biomedical Campus, Cambridge, CB2 0SP, UK.
| | - Karl Herholz
- The University of Manchester, Institute of Brain, Behaviour and Mental Health, Wolfson Molecular Imaging Centre, 27 Palatine Road, Manchester, M20 3LJ, UK.
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Abstract
Alzheimer's disease (AD) is one of the most debilitating neurodegenerative diseases and is predicted to affect 1 in 85 people by 2050. Despite much effort to discover a therapeutic strategy to prevent progression or to cure AD, to date no effective disease-modifying agent is available that can prevent, halt, or reverse the cognitive and functional decline of patients with AD. Several underlying etiologies to this failure are proposed. First, accumulating evidence from past trials suggests a preventive as opposed to therapeutic paradigm, and the precise temporal and mechanistic relationship of β-amyloid (Aβ) and tau protein should be elucidated to confirm this hypothesis. Second, we are in urgent need of revised diagnostic criteria to support future trials. Third, various technical and methodological improvements are required, based on the lessons learned from previous failed trials.
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Affiliation(s)
- Andreas Soejitno
- Department of General Medicine, National Hospital, Jl. Boulevard Famili Selatan Kav.1, Graha Famili, Surabaya, 60228, Indonesia,
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