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Li W, Sun L, Yue L, Xiao S. Diagnostic and predictive power of plasma proteins in Alzheimer's disease: a cross-sectional and longitudinal study in China. Sci Rep 2024; 14:17557. [PMID: 39080359 PMCID: PMC11289122 DOI: 10.1038/s41598-024-66195-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2023] [Accepted: 06/28/2024] [Indexed: 08/02/2024] Open
Abstract
Convenient and effective biomarkers are essential for the early diagnosis and treatment of Alzheimer's disease (AD). In the cross-sectional study, 103 patients with AD, 82 patients with aMCI and 508 normal controls (NC) were enrolled. The single-molecule array (Simoa) technique was used to assess the levels of plasma proteins, including NfL, T-tau, P-tau-181, Aβ40, Aβ42. Montreal Cognitive Assessment (MoCA) was used to assess the overall cognitive function of all subjects. Moreover, Amyloid PET and structural head MRI were also performed in a subset of the population. In the follow-up, the previous 508 normal older adults were followed up for two years, then COX regression analysis was used to investigate the association between baseline plasma proteins and future cognitive outcomes. NfL, T-tau, P-tau-181, Aβ40, Aβ42 and Aβ42/40 were altered in AD dementia, and NfL, Aβ42 and Aβ42/40 significantly outperformed all plasma proteins in differentiating AD dementia from NC, while NfL and Aβ42/40 could effectively distinguish between aMCI and NC. However, only plasma NfL was associated with future cognitive decline, and it was negatively correlated with MoCA (r = - 0.298, p < 0.001) and the volume of the left globus pallidus (r = - 0.278, p = 0.033). Plasma NfL can help distinguish between cognitively normal and cognitively impaired individuals (MCI/dementia) at the syndrome level. However, since we have not introduced other biomarkers for AD, such as PET CT or cerebrospinal fluid, and have not verified in other neurodegenerative diseases, whether plasma NFL can be used as a biomarker for AD needs to be further studied and explored.
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Affiliation(s)
- Wei Li
- Department of Geriatric Psychiatry, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, China
- Alzheimer's Disease and Related Disorders Center, Shanghai Jiao Tong University, Shanghai, China
| | - Lin Sun
- Department of Geriatric Psychiatry, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, China
- Alzheimer's Disease and Related Disorders Center, Shanghai Jiao Tong University, Shanghai, China
| | - Ling Yue
- Department of Geriatric Psychiatry, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, China.
- Alzheimer's Disease and Related Disorders Center, Shanghai Jiao Tong University, Shanghai, China.
| | - Shifu Xiao
- Department of Geriatric Psychiatry, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, China.
- Alzheimer's Disease and Related Disorders Center, Shanghai Jiao Tong University, Shanghai, China.
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Wang X, Peng L, Zhan S, Yin X, Huang L, Huang J, Yang J, Zhang Y, Zeng Y, Liang S. Alterations in hippocampus-centered morphological features and function of the progression from normal cognition to mild cognitive impairment. Asian J Psychiatr 2024; 93:103921. [PMID: 38237533 DOI: 10.1016/j.ajp.2024.103921] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/29/2023] [Revised: 12/21/2023] [Accepted: 01/06/2024] [Indexed: 03/08/2024]
Abstract
Mild cognitive impairment (MCI) is a significant precursor to dementia, highlighting the critical need for early identification of individuals at high risk of MCI to prevent cognitive decline. The study aimed to investigate the changes in brain structure and function before the onset of MCI. This study enrolled 19 older adults with progressive normal cognition (pNC) to MCI and 19 older adults with stable normal cognition (sNC). The gray matter (GM) volume and functional connectivity (FC) were estimated via magnetic resonance imaging during their normal cognition state 3 years prior. Additionally, spatial associations between FC maps and neurochemical profiles were examined using JuSpace. Compared to the sNC group, the pNC group showed decreased volume in the left hippocampus and left amygdala. The significantly positive correlation was observed between the GM volume of the left hippocampus and the MMSE scores after 3 years in pNC group. Besides, it showed that the pNC group had increased FC between the left hippocampus and the anterior-posterior cingulate gyrus, which was significantly correlated with the spatial distribution of dopamine D2 and noradrenaline transporter. Taken together, the study identified the abnormal brain characteristics before the onset of MCI, which might provide insight into clinical research.
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Affiliation(s)
- Xiuxiu Wang
- National-Local Joint Engineering Research Center of Rehabilitation Medicine Technology, Fujian University of Traditional Chinese Medicine, Fuzhou 350122, China; College of Rehabilitation Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou 350122, China
| | - Lixin Peng
- College of Rehabilitation Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou 350122, China
| | - Shiqi Zhan
- College of Rehabilitation Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou 350122, China
| | - Xiaolong Yin
- National-Local Joint Engineering Research Center of Rehabilitation Medicine Technology, Fujian University of Traditional Chinese Medicine, Fuzhou 350122, China; Rehabilitation Industry Institute, Fujian University of Traditional Chinese Medicine, Fuzhou 350122, China
| | - Li Huang
- National-Local Joint Engineering Research Center of Rehabilitation Medicine Technology, Fujian University of Traditional Chinese Medicine, Fuzhou 350122, China; Rehabilitation Industry Institute, Fujian University of Traditional Chinese Medicine, Fuzhou 350122, China
| | - Jiayang Huang
- College of Rehabilitation Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou 350122, China
| | - Junchao Yang
- College of Rehabilitation Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou 350122, China
| | - Yusi Zhang
- College of Rehabilitation Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou 350122, China
| | - Yi Zeng
- College of Rehabilitation Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou 350122, China
| | - Shengxiang Liang
- National-Local Joint Engineering Research Center of Rehabilitation Medicine Technology, Fujian University of Traditional Chinese Medicine, Fuzhou 350122, China; Rehabilitation Industry Institute, Fujian University of Traditional Chinese Medicine, Fuzhou 350122, China; Traditional Chinese Medicine Rehabilitation Research Center of State Administration of Traditional Chinese Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou 350122, China; Fujian Key Laboratory of Cognitive Rehabilitation, Affiliated Rehabilitation Hospital of Fujian University of Traditional Chinese Medicine, Fuzhou, Fuzhou 350001, China.
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Gentreau M, Maller JJ, Meslin C, Cyprien F, Lopez-Castroman J, Artero S. Is Hippocampal Volume a Relevant Early Marker of Dementia? Am J Geriatr Psychiatry 2023; 31:932-942. [PMID: 37394314 DOI: 10.1016/j.jagp.2023.05.015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/21/2022] [Revised: 05/09/2023] [Accepted: 05/31/2023] [Indexed: 07/04/2023]
Abstract
OBJECTIVE Hippocampal volume (HV) is a key imaging marker to improve Alzheimer's disease risk prediction. However, longitudinal studies are rare, and hippocampus may also be implicated in the subtle aging-related cognitive decline observed in dementia-free individuals. Our aim was to determine whether HV, measured by manual or automatic segmentation, is associated with dementia risk and cognitive decline in participants with and without incident dementia. METHODS At baseline, 510 dementia-free participants from the French longitudinal ESPRIT cohort underwent magnetic resonance imaging. HV was measured by manual and by automatic segmentation (FreeSurfer 6.0). The presence of dementia and cognitive functions were investigated at each follow-up (2, 4, 7, 10, 12, and 15 years). Cox proportional hazards models and linear mixed models were used to assess the association of HV with dementia risk and with cognitive decline, respectively. RESULTS During the 15-years follow-up, 42 participants developed dementia. Reduced HV (regardless of the measurement method) was significantly associated with higher dementia risk and cognitive decline in the whole sample. However, only the automatically measured HV was associated with cognitive decline in dementia-free participants. CONCLUSION These results suggest that HV can be used to predict the long-term risk of dementia but also cognitive decline in a dementia-free population. This raises the question of the relevance of HV measurement as an early marker of dementia in the general population.
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Affiliation(s)
- Mélissa Gentreau
- Institute of Functional Genomics (MG, FC, JLC, SA), University of Montpellier, CNRS, INSERM, Montpellier, France
| | - Jerome J Maller
- Monash Alfred Psychiatry Research Centre (JJM), Melbourne, Victoria, Australia; General Electric Healthcare (JJM), Richmond, Melbourne, Victoria, Australia
| | - Chantal Meslin
- Centre for Mental Health Research (CM), Australian National University, Canberra, Australia
| | - Fabienne Cyprien
- Institute of Functional Genomics (MG, FC, JLC, SA), University of Montpellier, CNRS, INSERM, Montpellier, France
| | - Jorge Lopez-Castroman
- Institute of Functional Genomics (MG, FC, JLC, SA), University of Montpellier, CNRS, INSERM, Montpellier, France; Department of Adult Psychiatry (JLC), Nimes University Hospital, Nimes, France; Centro de Investigación Biomédica en Red de Salud Mental (JLC), Madrid, Spain
| | - Sylvaine Artero
- Institute of Functional Genomics (MG, FC, JLC, SA), University of Montpellier, CNRS, INSERM, Montpellier, France.
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Amlerova J, Laczó J, Nedelska Z, Laczó M, Vyhnálek M, Zhang B, Sheardova K, Angelucci F, Andel R, Hort J. Emotional prosody recognition is impaired in Alzheimer’s disease. Alzheimers Res Ther 2022; 14:50. [PMID: 35382868 PMCID: PMC8985328 DOI: 10.1186/s13195-022-00989-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2021] [Accepted: 03/10/2022] [Indexed: 11/17/2022]
Abstract
Background The ability to understand emotions is often disturbed in patients with cognitive impairments. Right temporal lobe structures play a crucial role in emotional processing, especially the amygdala, temporal pole (TP), superior temporal sulcus (STS), and anterior cingulate (AC). Those regions are affected in early stages of Alzheimer´s disease (AD). The aim of our study was to evaluate emotional prosody recognition (EPR) in participants with amnestic mild cognitive impairment (aMCI) due to AD, AD dementia patients, and cognitively healthy controls and to measure volumes or thickness of the brain structures involved in this process. In addition, we correlated EPR score to cognitive impairment as measured by MMSE. The receiver operating characteristic (ROC) analysis was used to assess the ability of EPR tests to differentiate the control group from the aMCI and dementia groups. Methods Eighty-nine participants from the Czech Brain Aging Study: 43 aMCI due to AD, 36 AD dementia, and 23 controls, underwent Prosody Emotional Recognition Test. This experimental test included the playback of 25 sentences with neutral meaning each recorded with different emotional prosody (happiness, sadness, fear, disgust, anger). Volume of the amygdala and thickness of the TP, STS, and rostral and caudal parts of AC (RAC and CAC) were measured using FreeSurfer algorithm software. ANCOVA was used to evaluate EPR score differences. ROC analysis was used to assess the ability of EPR test to differentiate the control group from the aMCI and dementia groups. The Pearson’s correlation coefficients were calculated to explore relationships between EPR scores, structural brain measures, and MMSE. Results EPR was lower in the dementia and aMCI groups compared with controls. EPR total score had high sensitivity in distinguishing between not only controls and patients, but also controls and aMCI, controls and dementia, and aMCI and dementia. EPR decreased with disease severity as it correlated with MMSE. There was a significant positive correlation of EPR and thickness of the right TP, STS, and bilateral RAC. Conclusions EPR is impaired in AD dementia and aMCI due to AD. These data suggest that the broad range of AD symptoms may include specific deficits in the emotional sphere which further complicate the patient’s quality of life.
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Cummings J, Kinney J. Biomarkers for Alzheimer's Disease: Context of Use, Qualification, and Roadmap for Clinical Implementation. MEDICINA (KAUNAS, LITHUANIA) 2022; 58:952. [PMID: 35888671 PMCID: PMC9318582 DOI: 10.3390/medicina58070952] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/21/2022] [Revised: 07/13/2022] [Accepted: 07/15/2022] [Indexed: 12/30/2022]
Abstract
Background and Objectives: The US Food and Drug Administration (FDA) defines a biomarker as a characteristic that is measured as an indicator of normal biological processes, pathogenic processes, or responses to an exposure or intervention. Biomarkers may be used in clinical care or as drug development tools (DDTs) in clinical trials. The goal of this review and perspective is to provide insight into the regulatory guidance for the use of biomarkers in clinical trials and clinical care. Materials and Methods: We reviewed FDA guidances relevant to biomarker use in clinical trials and their transition to use in clinical care. We identified instructive examples of these biomarkers in Alzheimer's disease (AD) drug development and their application in clinical practice. Results: For use in clinical trials, biomarkers must have a defined context of use (COU) as a risk/susceptibility, diagnostic, monitoring, predictive, prognostic, pharmacodynamic, or safety biomarker. A four-stage process defines the pathway to establish the regulatory acceptance of the COU for a biomarker including submission of a letter of intent, description of the qualification plan, submission of a full qualification package, and acceptance through a qualification recommendation. Biomarkers used in clinical care may be companion biomarkers, in vitro diagnostic devices (IVDs), or laboratory developed tests (LDTs). A five-phase biomarker development process has been proposed to structure the biomarker development process. Conclusions: Biomarkers are increasingly important in drug development and clinical care. Adherence to regulatory guidance for biomarkers used in clinical trials and patient care is required to advance these important drug development and clinical tools.
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Affiliation(s)
- Jeffrey Cummings
- Pam Quirk Brain Health and Biomarker Laboratory, Chambers-Grundy Center for Transformative Neuroscience, Department of Brain Health, School of Integrated Health Sciences, University of Nevada Las Vegas, Las Vegas, NV 89154, USA;
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Alzheimer's Disease Connected Genes in the Post-Ischemic Hippocampus and Temporal Cortex. Genes (Basel) 2022; 13:genes13061059. [PMID: 35741821 PMCID: PMC9222545 DOI: 10.3390/genes13061059] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2022] [Revised: 06/08/2022] [Accepted: 06/12/2022] [Indexed: 12/13/2022] Open
Abstract
It is considered that brain ischemia can be causative connected to Alzheimer’s disease. In the CA1 and CA3 regions of the hippocampus and temporal cortex, genes related to Alzheimer’s disease, such as the amyloid protein precursor (APP), β-secretase (BACE1), presenilin 1 (PSEN1) and 2 (PSEN2), are deregulated by ischemia. The pattern of change in the CA1 area of the hippocampus covers all genes tested, and the changes occur at all post-ischemic times. In contrast, the pattern of gene changes in the CA3 subfield is much less intense, does not occur at all post-ischemic times, and is delayed in time post-ischemia relative to the CA1 field. Conversely, the pattern of gene alterations in the temporal cortex appears immediately after ischemia, and does not occur at all post-ischemic times and does not affect all genes. Evidence therefore suggests that various forms of dysregulation of the APP, BACE1 and PSEN1 and PSEN2 genes are associated with individual neuronal cell responses in the CA1 and CA3 areas of the hippocampus and temporal cortex with reversible cerebral ischemia. Scientific data indicate that an ischemic episode of the brain is a trigger of amyloidogenic processes. From the information provided, it appears that post-ischemic brain injury additionally activates neuronal death in the hippocampus and temporal cortex in an amyloid-dependent manner.
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Functional Imaging for Neurodegenerative Diseases. Presse Med 2022; 51:104121. [PMID: 35490910 DOI: 10.1016/j.lpm.2022.104121] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/14/2021] [Revised: 03/13/2022] [Accepted: 04/11/2022] [Indexed: 12/16/2022] Open
Abstract
Diagnosis and monitoring of neurodegenerative diseases has changed profoundly over the past twenty years. Biomarkers are now included in most diagnostic procedures as well as in clinical trials. Neuroimaging biomarkers provide access to brain structure and function over the course of neurodegenerative diseases. They have brought new insights into a wide range of neurodegenerative diseases and have made it possible to describe some of the imaging challenges in clinical populations. MRI mainly explores brain structure while molecular imaging, functional MRI and electro- and magnetoencephalography examine brain function. In this paper, we describe and analyse the current and potential contribution of MRI and molecular imaging in the field of neurodegenerative diseases.
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Sun W, Huang L, Cheng Y, Qin R, Xu H, Shao P, Ma J, Yao Z, Shi L, Xu Y. Medial Temporal Atrophy Contributes to Cognitive Impairment in Cerebral Small Vessel Disease. Front Neurol 2022; 13:858171. [PMID: 35665031 PMCID: PMC9159509 DOI: 10.3389/fneur.2022.858171] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2022] [Accepted: 04/14/2022] [Indexed: 11/18/2022] Open
Abstract
Background The role of brain atrophy in cognitive decline related to cerebral small vessel disease (CSVD) remains unclear. This study used AccuBrain™ to identify major CSVD-related brain changes and verified the relationship between brain atrophy and different cognition domains in CSVD patients. Methods All enrolled 242 CSVD patients and 76 healthy participants underwent magnetic resonance imaging examinations and detailed neuropsychological scale assessments were collected at the same time. The AccuBrain™ technology was applied to fully automated image segmentation, measurement, and calculation of the acquired imaging results to obtain the volumes of different brain partitions and the volume of WMH for quantitative analysis. Correlation analyses were used to estimate the relationship between MRI features and different cognitive domains. Multifactor linear regression models were performed to analyze independent predictors of MTA and cognitive decline. Results CSVD patients exhibited multiple gray matter nucleus volume decreases in the basal ganglia regions and brain lobes, including the temporal lobe (P = 0.019), especially in the medial temporal lobe (p < 0.001), parietal lobe (p = 0.013), and cingulate lobe (p = 0.036) compare to HC. The volume of PWMH was an independent predictor of MTA for CSVD patients. Both medial temporal atrophy (MTA) and PWMH were associated with cognition impairment in CSVD-CI patients. MTA mediated the effect of PWMH on executive function in CSVD-CI patients. Conclusions Our results showed that MTA was related to cognition impairment in CSVD patients, which might become a potential imaging marker for CSVD-CI.
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Affiliation(s)
- Wenshan Sun
- Department of Neurology, Nanjing Drum Tower Hospital, Clinical College of Nanjing Medical University, Nanjing, China
- Department of Neurology, Nanjing Drum Tower Hospital, Medical School and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Jiangsu Key Laboratory for Molecular Medicine, Nanjing University, Nanjing, China
- Department of Neurology, Affiliated Jiangning Hospital of Nanjing Medical University, Nanjing, China
| | - Lili Huang
- Department of Neurology, Nanjing Drum Tower Hospital, Medical School and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Jiangsu Key Laboratory for Molecular Medicine, Nanjing University, Nanjing, China
| | - Yue Cheng
- Department of Neurology, Nanjing Drum Tower Hospital, Medical School and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Jiangsu Key Laboratory for Molecular Medicine, Nanjing University, Nanjing, China
| | - Ruomeng Qin
- Department of Neurology, Nanjing Drum Tower Hospital, Medical School and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Jiangsu Key Laboratory for Molecular Medicine, Nanjing University, Nanjing, China
| | - Hengheng Xu
- Department of Neurology, Nanjing Drum Tower Hospital, Medical School and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Jiangsu Key Laboratory for Molecular Medicine, Nanjing University, Nanjing, China
| | - Pengfei Shao
- Department of Neurology, Nanjing Drum Tower Hospital, Medical School and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Jiangsu Key Laboratory for Molecular Medicine, Nanjing University, Nanjing, China
| | - Junyi Ma
- Department of Neurology, Nanjing Drum Tower Hospital, Medical School and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Jiangsu Key Laboratory for Molecular Medicine, Nanjing University, Nanjing, China
| | - Zhelv Yao
- Department of Neurology, Nanjing Drum Tower Hospital, Medical School and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Jiangsu Key Laboratory for Molecular Medicine, Nanjing University, Nanjing, China
| | - Lin Shi
- Department of Imaging and Interventional Radiology, The Chinese University of Hong Kong, Hong Kong, Hong Kong SAR, China
- BrainNow Research Institute, Hong Kong Science and Technology Park, Hong Kong, Hong Kong SAR, China
| | - Yun Xu
- Department of Neurology, Nanjing Drum Tower Hospital, Clinical College of Nanjing Medical University, Nanjing, China
- Department of Neurology, Nanjing Drum Tower Hospital, Medical School and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Jiangsu Key Laboratory for Molecular Medicine, Nanjing University, Nanjing, China
- *Correspondence: Yun Xu
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Balboni E, Nocetti L, Carbone C, Dinsdale N, Genovese M, Guidi G, Malagoli M, Chiari A, Namburete AIL, Jenkinson M, Zamboni G. The impact of transfer learning on 3D deep learning convolutional neural network segmentation of the hippocampus in mild cognitive impairment and Alzheimer disease subjects. Hum Brain Mapp 2022; 43:3427-3438. [PMID: 35373881 PMCID: PMC9248306 DOI: 10.1002/hbm.25858] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2021] [Revised: 02/04/2022] [Accepted: 03/21/2022] [Indexed: 11/23/2022] Open
Abstract
Research on segmentation of the hippocampus in magnetic resonance images through deep learning convolutional neural networks (CNNs) shows promising results, suggesting that these methods can identify small structural abnormalities of the hippocampus, which are among the earliest and most frequent brain changes associated with Alzheimer disease (AD). However, CNNs typically achieve the highest accuracy on datasets acquired from the same domain as the training dataset. Transfer learning allows domain adaptation through further training on a limited dataset. In this study, we applied transfer learning on a network called spatial warping network segmentation (SWANS), developed and trained in a previous study. We used MR images of patients with clinical diagnoses of mild cognitive impairment (MCI) and AD, segmented by two different raters. By using transfer learning techniques, we developed four new models, using different training methods. Testing was performed using 26% of the original dataset, which was excluded from training as a hold‐out test set. In addition, 10% of the overall training dataset was used as a hold‐out validation set. Results showed that all the new models achieved better hippocampal segmentation quality than the baseline SWANS model (ps < .001), with high similarity to the manual segmentations (mean dice [best model] = 0.878 ± 0.003). The best model was chosen based on visual assessment and volume percentage error (VPE). The increased precision in estimating hippocampal volumes allows the detection of small hippocampal abnormalities already present in the MCI phase (SD = [3.9 ± 0.6]%), which may be crucial for early diagnosis.
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Affiliation(s)
- Erica Balboni
- Health Physics Unit, Azienda Ospedaliera di Modena, Modena, Italy.,Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy
| | - Luca Nocetti
- Health Physics Unit, Azienda Ospedaliera di Modena, Modena, Italy
| | - Chiara Carbone
- Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy.,Center for Neurosciences and Neurotechnology, Università di Modena e Reggio Emilia, Modena, Italy
| | - Nicola Dinsdale
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.,Oxford Machine Learning in NeuroImaging Lab, Department of Computer Science, Oxford, UK
| | | | - Gabriele Guidi
- Health Physics Unit, Azienda Ospedaliera di Modena, Modena, Italy
| | | | - Annalisa Chiari
- Neuroradiology Unit, Azienda Ospedaliera di Modena, Modena, Italy
| | - Ana I L Namburete
- Oxford Machine Learning in NeuroImaging Lab, Department of Computer Science, Oxford, UK
| | - Mark Jenkinson
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.,Australian Institute for Machine Learning, School of Computer Science, University of Adelaide, Adelaide, South Australia, Australia.,South Australian Health and Medical Research Institute (SAHMRI), Adelaide, South Australia, Australia
| | - Giovanna Zamboni
- Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy.,Center for Neurosciences and Neurotechnology, Università di Modena e Reggio Emilia, Modena, Italy.,Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
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Tarawneh HY, Menegola HK, Peou A, Tarawneh H, Jayakody DMP. Central Auditory Functions of Alzheimer's Disease and Its Preclinical Stages: A Systematic Review and Meta-Analysis. Cells 2022; 11:1007. [PMID: 35326458 PMCID: PMC8947537 DOI: 10.3390/cells11061007] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2022] [Revised: 03/01/2022] [Accepted: 03/12/2022] [Indexed: 01/01/2023] Open
Abstract
In 2020, 55 million people worldwide were living with dementia, and this number is projected to reach 139 million in 2050. However, approximately 75% of people living with dementia have not received a formal diagnosis. Hence, they do not have access to treatment and care. Without effective treatment in the foreseeable future, it is essential to focus on modifiable risk factors and early intervention. Central auditory processing is impaired in people diagnosed with Alzheimer's disease (AD) and its preclinical stages and may manifest many years before clinical diagnosis. This study systematically reviewed central auditory processing function in AD and its preclinical stages using behavioural central auditory processing tests. Eleven studies met the full inclusion criteria, and seven were included in the meta-analyses. The results revealed that those with mild cognitive impairment perform significantly worse than healthy controls within channel adaptive tests of temporal response (ATTR), time-compressed speech test (TCS), Dichotic Digits Test (DDT), Dichotic Sentence Identification (DSI), Speech in Noise (SPIN), and Synthetic Sentence Identification-Ipsilateral Competing Message (SSI-ICM) central auditory processing tests. In addition, this analysis indicates that participants with AD performed significantly worse than healthy controls in DDT, DSI, and SSI-ICM tasks. Clinical implications are discussed in detail.
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Affiliation(s)
- Hadeel Y. Tarawneh
- Ear Science Institute Australia, Subiaco, WA 6008, Australia; (H.Y.T.); (H.K.M.); (A.P.); (H.T.)
- Ear Sciences Centre, School of Surgery, University of Western Australia, Crawley, WA 6009, Australia
- School of Human Sciences, The University of Western Australia, Crawley, WA 6009, Australia
| | - Holly K. Menegola
- Ear Science Institute Australia, Subiaco, WA 6008, Australia; (H.Y.T.); (H.K.M.); (A.P.); (H.T.)
- Ear Sciences Centre, School of Surgery, University of Western Australia, Crawley, WA 6009, Australia
| | - Andrew Peou
- Ear Science Institute Australia, Subiaco, WA 6008, Australia; (H.Y.T.); (H.K.M.); (A.P.); (H.T.)
- School of Human Sciences, The University of Western Australia, Crawley, WA 6009, Australia
| | - Hanadi Tarawneh
- Ear Science Institute Australia, Subiaco, WA 6008, Australia; (H.Y.T.); (H.K.M.); (A.P.); (H.T.)
- Ear Sciences Centre, School of Surgery, University of Western Australia, Crawley, WA 6009, Australia
| | - Dona M. P. Jayakody
- Ear Science Institute Australia, Subiaco, WA 6008, Australia; (H.Y.T.); (H.K.M.); (A.P.); (H.T.)
- Ear Sciences Centre, School of Surgery, University of Western Australia, Crawley, WA 6009, Australia
- WA Centre for Health and Aging, University of Western Australia, Crawley, WA 6009, Australia
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11
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Gallucci M, Cenesi L, White C, Antuono P, Quaglio G, Bonanni L. Lights and Shadows of Cerebrospinal Fluid Biomarkers in the Current Alzheimer's Disease Framework. J Alzheimers Dis 2022; 86:1061-1072. [PMID: 35180122 PMCID: PMC9108561 DOI: 10.3233/jad-215432] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND The most significant biomarkers that are included in the Alzheimer's disease (AD) research framework are amyloid-β plaques deposition, p-tau, t-tau, and neurodegeneration.Although cerebrospinal fluid (CSF) biomarkers are included in the most recent AD research criteria, their use is increasing in the routine clinical practice and is applied also to the preclinical phases of AD, including mild cognitive impairment. The role of these biomarkers is still unclear concerning the preclinical stage of AD diagnosis, the CSF methodology, and the costs-benefits of the biomarkers' tests. The controversies regarding the use of biomarkers in the clinical practice are related to the concepts of analytical validity, clinical validity, and clinical utility and to the question of whether they are able to diagnose AD without the support of AD clinical phenotypes. OBJECTIVE The objective of the present work is to expose the strengths and weaknesses of the use of CSF biomarkers in the diagnosis of AD in a clinical context. METHODS We used PubMed as main source for articles published and the final reference list was generated on the basis of relevance to the topics covered in this work. RESULTS The use of CSF biomarkers for AD diagnosis is certainly important but its indication in routine clinical practice, especially for prodromal conditions, needs to be regulated and also contextualized considering the variety of possible clinical AD phenotypes. CONCLUSION We suggest that the diagnosis of AD should be understood both as clinical and pathological.
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Affiliation(s)
- Maurizio Gallucci
- Cognitive Impairment Center, Local Health Authority n. 2 Marca Trevigiana, Treviso, Italy.,Associazione Alzheimer Treviso Onlus, Treviso, Italy
| | - Leandro Cenesi
- Cognitive Impairment Center, Local Health Authority n. 2 Marca Trevigiana, Treviso, Italy
| | - Céline White
- Cognitive Impairment Center, Local Health Authority n. 2 Marca Trevigiana, Treviso, Italy
| | - Piero Antuono
- Department of Neurology, Medical College of Wisconsin, Milwaukee, WI, USA
| | - Gianluca Quaglio
- Scientific Foresight Unit (STOA), European Parliamentary Research Service, European Parliament, Brussels, Belgium
| | - Laura Bonanni
- Department of Medicine and Aging Sciences, University G. d'Annunzio of Chieti-Pescara, Chieti, Italy
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12
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Pendlebury ST, Thomson RJ, Welch SJV, Kuker W, Rothwell PM. Utility of white matter disease and atrophy on routinely acquired brain imaging for prediction of long-term delirium risk: population-based cohort study. Age Ageing 2022; 51:6427231. [PMID: 34793588 PMCID: PMC8753040 DOI: 10.1093/ageing/afab200] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2021] [Revised: 07/04/2021] [Indexed: 12/15/2022] Open
Abstract
Background brain imaging done as part of standard care may have clinical utility beyond its immediate indication. Using delirium as an exemplar, we determined the predictive value of baseline brain imaging variables [white matter changes (WMC) and atrophy] for delirium risk on long-term follow-up after transient ischemic attack (TIA)/stroke in a population-based cohort study. Methods surviving TIA/stroke participants in the Oxford Vascular Study (OXVASC) were assessed prospectively for delirium during all hospitalisations over 6 months (2013–14). Using logistic regression, independent associations were determined between baseline OXVASC computed tomography or magnetic resonance brain imaging measures of WMC and cerebral atrophy (none/mild versus moderate/severe) and delirium adjusted for age, sex, baseline stroke severity, depression, illness severity and pre-admission cognition. Results among 1,565 TIA/stroke survivors with 194 hospital admissions (158 patients, mean/standard deviation age at admission = 79.2/11.5 years), delirium occurred in 59 (37%). WMC and atrophy on baseline imaging were associated with delirium [odds ratio (OR) = 3.41, 1.21–5.85, P = 0.001 and OR = 2.50, 1.23–5.08, P = 0.01 (unadjusted) and OR = 2.67, 1.21–5.85, P = 0.02 and OR = 2.18, 1.00–4.73, P = 0.05 (adjusted age and sex)]. Associations were strengthened when analyses were restricted to patients hospitalised within 5 years of baseline brain imaging [OR = 6.04, 2.39–15.24, P < 0.0001 and OR = 4.64, 1.46–14.82, P = 0.009 (unadjusted)] but only WMC remained significant after adjustment for all covariates including pre-admission cognition (OR = 4.83, 1.29–18.13, P = 0.02 for Mini-Mental State Examination and OR = 5.15, 1.26–21.09, P = 0.02 for Montreal Cognitive Assessment). Conclusions WMC and atrophy on brain imaging done up to 5 years earlier predicted delirium and may have clinical utility in risk stratification. Associations with WMC but not atrophy were independent of pre-admission cognitive impairment.
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Affiliation(s)
- Sarah T Pendlebury
- Wolfson Centre for Prevention of Stroke and Dementia, Wolfson Building, Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital and the University of Oxford, Oxford, UK
- NIHR Oxford Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
- Departments of General (Internal) Medicine and Geratology, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - Ross J Thomson
- Department of Cardiology, Royal Free Hospital, London, UK
| | - Sarah J V Welch
- Wolfson Centre for Prevention of Stroke and Dementia, Wolfson Building, Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital and the University of Oxford, Oxford, UK
| | - Wilhelm Kuker
- Wolfson Centre for Prevention of Stroke and Dementia, Wolfson Building, Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital and the University of Oxford, Oxford, UK
| | - Peter M Rothwell
- Wolfson Centre for Prevention of Stroke and Dementia, Wolfson Building, Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital and the University of Oxford, Oxford, UK
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13
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Alzheimer resemblance atrophy index, BrainAGE, and normal pressure hydrocephalus score in the prediction of subtle cognitive decline: added value compared to existing MR imaging markers. Eur Radiol 2022; 32:7833-7842. [PMID: 35486172 PMCID: PMC9668758 DOI: 10.1007/s00330-022-08798-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2021] [Revised: 03/09/2022] [Accepted: 04/01/2022] [Indexed: 01/03/2023]
Abstract
OBJECTIVES Established visual brain MRI markers for dementia include hippocampal atrophy (mesio-temporal atrophy MTA), white matter lesions (Fazekas score), and number of cerebral microbleeds (CMBs). We assessed whether novel quantitative, artificial intelligence (AI)-based volumetric scores provide additional value in predicting subsequent cognitive decline in elderly controls. METHODS A prospective study including 80 individuals (46 females, mean age 73.4 ± 3.5 years). 3T MR imaging was performed at baseline. Extensive neuropsychological assessment was performed at baseline and at 4.5-year follow-up. AI-based volumetric scores were derived from 3DT1: Alzheimer Disease Resemblance Atrophy Index (AD-RAI), Brain Age Gap Estimate (BrainAGE), and normal pressure hydrocephalus (NPH) index. Analyses included regression models between cognitive scores and imaging markers. RESULTS AD-RAI score at baseline was associated with Corsi (visuospatial memory) decline (10.6% of cognitive variability in multiple regression models). After inclusion of MTA, CMB, and Fazekas scores simultaneously, the AD-RAI score remained as the sole valid predictor of the cognitive outcome explaining 16.7% of its variability. Its percentage reached 21.4% when amyloid positivity was considered an additional explanatory factor. BrainAGE score was associated with Trail Making B (executive functions) decrease (8.5% of cognitive variability). Among the conventional MRI markers, only the Fazekas score at baseline was positively related to the cognitive outcome (8.7% of cognitive variability). The addition of the BrainAGE score as an independent variable significantly increased the percentage of cognitive variability explained by the regression model (from 8.7 to 14%). The addition of amyloid positivity led to a further increase in this percentage reaching 21.8%. CONCLUSIONS The AI-based AD-RAI index and BrainAGE scores have limited but significant added value in predicting the subsequent cognitive decline in elderly controls when compared to the established visual MRI markers of brain aging, notably MTA, Fazekas score, and number of CMBs. KEY POINTS • AD-RAI score at baseline was associated with Corsi score (visuospatial memory) decline. • BrainAGE score was associated with Trail Making B (executive functions) decrease. • AD-RAI index and BrainAGE scores have limited but significant added value in predicting the subsequent cognitive decline in elderly controls when compared to the established visual MRI markers of brain aging, notably MTA, Fazekas score, and number of CMBs.
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14
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Gonzalez-Rodriguez M, Villar-Conde S, Astillero-Lopez V, Villanueva-Anguita P, Ubeda-Banon I, Flores-Cuadrado A, Martinez-Marcos A, Saiz-Sanchez D. Neurodegeneration and Astrogliosis in the Human CA1 Hippocampal Subfield Are Related to hsp90ab1 and bag3 in Alzheimer's Disease. Int J Mol Sci 2021; 23:165. [PMID: 35008592 PMCID: PMC8745315 DOI: 10.3390/ijms23010165] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2021] [Revised: 12/19/2021] [Accepted: 12/20/2021] [Indexed: 02/06/2023] Open
Abstract
Alzheimer's disease (AD), the most prevalent neurodegenerative disorder, is characterized by executive dysfunction and memory impairment mediated by the accumulation of extracellular amyloid-β peptide (Aβ) and intracellular hyperphosphorylated tau protein. The hippocampus (HIPP) is essential for memory formation and is involved in early stages of disease. In fact, hippocampal atrophy is used as an early biomarker of neuronal injury and to evaluate disease progression. It is not yet well-understood whether changes in hippocampal volume are due to neuronal or glial loss. The aim of the study was to assess hippocampal atrophy and/or gliosis using unbiased stereological quantification and to obtain hippocampal proteomic profiles related to neurodegeneration and gliosis. Hippocampal volume measurement, stereological quantification of NeuN-, Iba-1- and GFAP-positive cells, and sequential window acquisition of all theoretical mass spectrometry (SWATH-MS) analysis were performed in AD and non-AD cases. Reduced hippocampal volume was identified using the Cavalieri probe, particularly in the CA1 region, where it correlated with neuronal loss and astrogliosis. A total of 102 downregulated and 47 upregulated proteins were identified in the SWATH-MS analysis after restrictive filtering based on an FC > 1.5 and p value < 0.01. The Hsp90 family of chaperones, particularly BAG3 and HSP90AB1, are closely related to astrocytes, indicating a possible role in degrading Aβ and tau through chaperone-mediated autophagy.
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Affiliation(s)
| | | | | | | | | | | | - Alino Martinez-Marcos
- CRIB, Neuroplasticity and Neurodegeneration Laboratory, Ciudad Real Medical School, University of Castilla-La Mancha, 13071 Ciudad Real, Spain; (M.G.-R.); (S.V.-C.); (V.A.-L.); (P.V.-A.); (I.U.-B.); (A.F.-C.)
| | - Daniel Saiz-Sanchez
- CRIB, Neuroplasticity and Neurodegeneration Laboratory, Ciudad Real Medical School, University of Castilla-La Mancha, 13071 Ciudad Real, Spain; (M.G.-R.); (S.V.-C.); (V.A.-L.); (P.V.-A.); (I.U.-B.); (A.F.-C.)
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15
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Lenhart L, Seiler S, Pirpamer L, Goebel G, Potrusil T, Wagner M, Dal Bianco P, Ransmayr G, Schmidt R, Benke T, Scherfler C. Anatomically Standardized Detection of MRI Atrophy Patterns in Early-Stage Alzheimer's Disease. Brain Sci 2021; 11:brainsci11111491. [PMID: 34827490 PMCID: PMC8615991 DOI: 10.3390/brainsci11111491] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2021] [Revised: 11/05/2021] [Accepted: 11/06/2021] [Indexed: 11/16/2022] Open
Abstract
MRI studies have consistently identified atrophy patterns in Alzheimer’s disease (AD) through a whole-brain voxel-based analysis, but efforts to investigate morphometric profiles using anatomically standardized and automated whole-brain ROI analyses, performed at the individual subject space, are still lacking. In this study we aimed (i) to utilize atlas-derived measurements of cortical thickness and subcortical volumes, including of the hippocampal subfields, to identify atrophy patterns in early-stage AD, and (ii) to compare cognitive profiles at baseline and during a one-year follow-up of those previously identified morphometric AD subtypes to predict disease progression. Through a prospectively recruited multi-center study, conducted at four Austrian sites, 120 patients were included with probable AD, a disease onset beyond 60 years and a clinical dementia rating of ≤1. Morphometric measures of T1-weighted images were obtained using FreeSurfer. A principal component and subsequent cluster analysis identified four morphometric subtypes, including (i) hippocampal predominant (30.8%), (ii) hippocampal-temporo-parietal (29.2%), (iii) parieto-temporal (hippocampal sparing, 20.8%) and (iv) hippocampal-temporal (19.2%) atrophy patterns that were associated with phenotypes differing predominately in the presentation and progression of verbal memory and visuospatial impairments. These morphologically distinct subtypes are based on standardized brain regions, which are anatomically defined and freely accessible so as to validate its diagnostic accuracy and enhance the prediction of disease progression.
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Affiliation(s)
- Lukas Lenhart
- Department of Neurology, Medical University of Innsbruck, 6020 Innsbruck, Austria; (L.L.); (T.P.); (T.B.)
- Department of Neuroradiology, Medical University of Innsbruck, 6020 Innsbruck, Austria;
| | - Stephan Seiler
- Center for Neurosciences, Department of Neurology, University of California, Davis, CA 95616, USA;
- Imaging of Dementia and Aging (IDeA) Laboratory, Davis, CA 95616, USA
- Department of Neurology, Medical University of Graz, 8036 Graz, Austria; (L.P.); (R.S.)
| | - Lukas Pirpamer
- Department of Neurology, Medical University of Graz, 8036 Graz, Austria; (L.P.); (R.S.)
| | - Georg Goebel
- Department of Medical Statistics, Informatics and Health Economics, Medical University of Innsbruck, Müllerstraße 44, 6020 Innsbruck, Austria;
| | - Thomas Potrusil
- Department of Neurology, Medical University of Innsbruck, 6020 Innsbruck, Austria; (L.L.); (T.P.); (T.B.)
| | - Michaela Wagner
- Department of Neuroradiology, Medical University of Innsbruck, 6020 Innsbruck, Austria;
| | - Peter Dal Bianco
- Department of Neurology, Medical University of Vienna, 1090 Vienna, Austria;
| | - Gerhard Ransmayr
- Department of Neurology, Kepler University Hospital, 4021 Linz, Austria;
| | - Reinhold Schmidt
- Department of Neurology, Medical University of Graz, 8036 Graz, Austria; (L.P.); (R.S.)
| | - Thomas Benke
- Department of Neurology, Medical University of Innsbruck, 6020 Innsbruck, Austria; (L.L.); (T.P.); (T.B.)
| | - Christoph Scherfler
- Department of Neurology, Medical University of Innsbruck, 6020 Innsbruck, Austria; (L.L.); (T.P.); (T.B.)
- Correspondence: ; Tel.: +43-512-504-26276
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16
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Pemberton HG, Zaki LAM, Goodkin O, Das RK, Steketee RME, Barkhof F, Vernooij MW. Technical and clinical validation of commercial automated volumetric MRI tools for dementia diagnosis-a systematic review. Neuroradiology 2021; 63:1773-1789. [PMID: 34476511 PMCID: PMC8528755 DOI: 10.1007/s00234-021-02746-3] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2021] [Accepted: 06/02/2021] [Indexed: 12/22/2022]
Abstract
Developments in neuroradiological MRI analysis offer promise in enhancing objectivity and consistency in dementia diagnosis through the use of quantitative volumetric reporting tools (QReports). Translation into clinical settings should follow a structured framework of development, including technical and clinical validation steps. However, published technical and clinical validation of the available commercial/proprietary tools is not always easy to find and pathways for successful integration into the clinical workflow are varied. The quantitative neuroradiology initiative (QNI) framework highlights six necessary steps for the development, validation and integration of quantitative tools in the clinic. In this paper, we reviewed the published evidence regarding regulatory-approved QReports for use in the memory clinic and to what extent this evidence fulfils the steps of the QNI framework. We summarize unbiased technical details of available products in order to increase the transparency of evidence and present the range of reporting tools on the market. Our intention is to assist neuroradiologists in making informed decisions regarding the adoption of these methods in the clinic. For the 17 products identified, 11 companies have published some form of technical validation on their methods, but only 4 have published clinical validation of their QReports in a dementia population. Upon systematically reviewing the published evidence for regulatory-approved QReports in dementia, we concluded that there is a significant evidence gap in the literature regarding clinical validation, workflow integration and in-use evaluation of these tools in dementia MRI diagnosis.
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Affiliation(s)
- Hugh G Pemberton
- 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.
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK.
| | - Lara A M Zaki
- Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Olivia Goodkin
- 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
| | - Ravi K Das
- Clinical, Educational and Health Psychology, University College London, London, UK
| | - Rebecca M E Steketee
- Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - 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
- Radiology & Nuclear Medicine, VU University Medical Center, Amsterdam, The Netherlands
| | - Meike W Vernooij
- Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Center, Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
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17
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Silhan D, Pashkovska O, Bartos A. Hippocampo-Horn Percentage and Parietal Atrophy Score for Easy Visual Assessment of Brain Atrophy on Magnetic Resonance Imaging in Early- and Late-Onset Alzheimer's Disease. J Alzheimers Dis 2021; 84:1259-1266. [PMID: 34633317 PMCID: PMC8673546 DOI: 10.3233/jad-210372] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2023]
Abstract
BACKGROUND Magnetic resonance imaging (MRI) visual scales of brain atrophy are important for differential diagnosis of dementias in routine clinical practice. Atrophy patterns in early- and late-onset Alzheimer's disease (AD) can be different according to some studies. OBJECTIVE Our goal was to assess brain atrophy patterns in early- and late-onset AD using our recently developed simple MRI visual scales and evaluate their reliability. METHODS We used Hippocampo-horn percentage (Hip-hop) and Parietal Atrophy Score (PAS) to compare mediotemporal and parietal atrophy on brain MRI among 4 groups: 26 patients with early-onset AD, 21 younger cognitively normal persons, 32 patients with late-onset AD, and 36 older cognitively normal persons. Two raters scored all brain MRI to assess reliability of the Hip-hop and PAS. Brain MRIs were obtained from Alzheimer's Disease Neuroimaging Initiative (ADNI) database. RESULTS The patients with early-onset AD had significantly more pronounced mediotemporal and also parietal atrophy bilaterally compared to the controls (both p < 0.01). The patients with late-onset AD had significantly more pronounced only mediotemporal atrophy bilaterally compared to the controls (p < 0.000001), but parietal lobes were the same. Intra-rater and inter-rater reliability of both visual scales Hip-hop and PAS were almost perfect in all cases (weighted-kappa value ranged from 0.90 to 0.99). CONCLUSION While mediotemporal atrophy detected using Hip-hop is universal across the whole AD age spectrum, parietal atrophy detected using PAS is worth rating only in early-onset AD. Hip-hop and PAS are very reliable MRI visual scales.
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Affiliation(s)
- David Silhan
- Department of Neurology, Charles University, Third Faculty of Medicine, Prague, Czech Republic
| | - Olga Pashkovska
- Department of Neurology, Charles University, Third Faculty of Medicine, Prague, Czech Republic
| | - Ales Bartos
- Department of Neurology, Charles University, Third Faculty of Medicine, Prague, Czech Republic
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18
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Herrmann FR, Montandon ML, Garibotto V, Rodriguez C, Haller S, Giannakopoulos P. Determinants of Cognitive Trajectories in Normal Aging: A Longitudinal PET-MRI Study in a Community-based Cohort. Curr Alzheimer Res 2021; 18:482-491. [PMID: 34602046 DOI: 10.2174/1567205018666210930111806] [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: 06/16/2020] [Revised: 04/01/2021] [Accepted: 05/18/2021] [Indexed: 11/22/2022]
Abstract
BACKGROUND The determinants of the progressive decrement of cognition in normal aging are still a matter of debate. Alzheimer disease (AD)-signature markers and vascular lesions, but also psychological variables such as personality factors, are thought to have an impact on the longitudinal trajectories of neuropsychological performances in healthy elderly individuals. OBJECTIVE The current research aimed to identify the main determinants associated with cognitive trajectories in normal aging. METHODS We performed a 4.5-year longitudinal study in 90 older community-dwellers coupling two neuropsychological assessments, medial temporal atrophy (MTA), number of cerebral microbleeds (CMB), and white matter hyperintensities (WMH) at inclusion, visual rating of amyloid and FDG PET at follow-up, and APOE genotyping. Personality factors were assessed at baseline using the NEO-PIR. Univariate and backward stepwise regression models were built to explore the association between the continuous cognitive score (CCS) and both imaging and personality variables. RESULTS The number of strictly lobar CMB at baseline (4 or more) was related to a significant increase in the risk of cognitive decrement. In multivariable models, amyloid positivity was associated with a 1.73 unit decrease of the CCS at follow-up. MTA, WMH and abnormal FDG PET were not related to the cognitive outcome. Among personality factors, only higher agreeableness was related to better preservation of neuropsychological performances. CONCLUSION CMB and amyloid positivity are the only imaging determinants of cognitive trajectories in this highly selected series of healthy controls. Among personality factors, higher agreeableness confers a modest but significant protection against the decline of cognitive performances.
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Affiliation(s)
- François R Herrmann
- Department of Rehabilitation and Geriatrics, Geneva University Hospitals and University of Geneva, Geneva, Switzerland
| | - Marie-Louise Montandon
- Department of Rehabilitation and Geriatrics, Geneva University Hospitals and University of Geneva, Geneva, Switzerland
| | - Valentina Garibotto
- Division of Nuclear Medicine and Molecular Imaging, Diagnostic Department, Geneva University Hospitals and University of Geneva, Geneva, Switzerland
| | | | - Sven Haller
- CIMC - Centre d'Imagerie Médicale de Cornavin, Geneva, Switzerland
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19
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Montandon ML, Herrmann FR, Garibotto V, Rodriguez C, Haller S, Giannakopoulos P. Microbleeds and Medial Temporal Atrophy Determine Cognitive Trajectories in Normal Aging: A Longitudinal PET-MRI Study. J Alzheimers Dis 2021; 77:1431-1442. [PMID: 32925053 DOI: 10.3233/jad-200559] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/16/2023]
Abstract
BACKGROUND The cognitive trajectories in normal aging may be affected by medial temporal atrophy (MTA) and amyloid burden, as well as vascular pathologies such as cortical microbleeds (CMB) and white matter hyperintensities (WMH). OBJECTIVE We addressed here the role of imaging markers in their prediction in a real-world situation. METHODS We performed a 4.5-year longitudinal study in 90 older community-dwellers coupling two neuropsychological assessments, MTA estimated with the Schelten's scale, number of CMB, and WMH evaluated with the Fazekas score at inclusion and follow-up, visual rating of amyloid PET and glucose hypometabolism at follow-up, and APOE genotyping. Regression models were built to explore the association between the continuous cognitive score (CCS) and imaging parameters. RESULTS The number of strictly lobar CMB at baseline (4 or more) was related to a 5.5-fold increase of the risk of cognitive decrement. This association persisted in multivariable models explaining 10.6% of the CCS decrease variance. MTA, and Fazekas score at baseline and amyloid positivity or abnormal FDG PET, were not related to the cognitive outcome. The increase of right MTA at follow-up was the only correlate of CCS decrease both in univariate and multivariable models explaining 9.2% of its variance. CONCLUSION The present data show that the accumulation of more than four CMB is associated with significant cognitive decrement over time in highly educated elderly persons. They also reveal that the progressive deterioration of cognitive performance within the age-adjusted norms is also related to the increase of visually assessed MTA.
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Affiliation(s)
- Marie-Louise Montandon
- Department of Rehabilitation and Geriatrics, Geneva University Hospitals and University of Geneva, Switzerland.,Department of Psychiatry, University of Geneva, Switzerland
| | - François R Herrmann
- Department of Rehabilitation and Geriatrics, Geneva University Hospitals and University of Geneva, Switzerland
| | - Valentina Garibotto
- Division of Nuclear Medicine and Molecular Imaging, Diagnostic Department, Geneva University Hospitals and University of Geneva, Switzerland
| | - Cristelle Rodriguez
- Department of Psychiatry, University of Geneva, Switzerland.,Medical Direction, University of Geneva Hospitals, Geneva, Switzerland
| | - Sven Haller
- CIRD - Centre d'Imagerie Rive Droite in Geneva, Switzerland.,Department of Surgical Sciences, Radiology, Uppsala University, Uppsala, Sweden.,Department of Neuroradiology, Faculty of Medicine of the University of Geneva, Geneva, Switzerland
| | - Panteleimon Giannakopoulos
- Department of Psychiatry, University of Geneva, Switzerland.,Medical Direction, University of Geneva Hospitals, Geneva, Switzerland
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20
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Giannakopoulos P, Montandon ML, Rodriguez C, Haller S, Garibotto V, Herrmann FR. Prediction of Subtle Cognitive Decline in Normal Aging: Added Value of Quantitative MRI and PET Imaging. Front Aging Neurosci 2021; 13:664224. [PMID: 34322007 PMCID: PMC8313279 DOI: 10.3389/fnagi.2021.664224] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2021] [Accepted: 06/21/2021] [Indexed: 11/26/2022] Open
Abstract
Quantitative imaging processing tools have been proposed to improve clinic-radiological correlations but their added value at the initial stages of cognitive decline is still a matter of debate. We performed a longitudinal study in 90 community-dwelling elders with three neuropsychological assessments during a 4.5 year follow-up period, and visual assessment of medial temporal atrophy (MTA), white matter hyperintensities, cortical microbleeds (CMB) as well as amyloid positivity, and presence of abnormal FDG-PET patterns. Quantitative imaging data concerned ROI analysis of MRI volume, amyloid burden, and FDG-PET metabolism in several AD-signature areas. Multiple regression models, likelihood-ratio tests, and areas under the receiver operating characteristic curve (AUC) were used to compare quantitative imaging markers to visual inspection. The presence of more or equal to four CMB at inclusion and slight atrophy of the right MTL at follow-up were the only parameters to be independently related to the worst cognitive score explaining 6% of its variance. This percentage increased to 24.5% when the ROI-defined volume loss in the posterior cingulate cortex, baseline hippocampus volume, and MTL metabolism were also considered. When binary classification of cognition was made, the area under the ROC curve increased from 0.69 for the qualitative to 0.79 for the mixed imaging model. Our data reveal that the inclusion of quantitative imaging data significantly increases the prediction of cognitive changes in elderly controls compared to the single consideration of visual inspection.
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Affiliation(s)
- Panteleimon Giannakopoulos
- Department of Psychiatry, University of Geneva, Geneva, Switzerland.,Medical Direction, Geneva University Hospitals, Geneva, Switzerland
| | - Marie-Louise Montandon
- Department of Psychiatry, University of Geneva, Geneva, Switzerland.,Department of Rehabilitation and Geriatrics, Geneva University Hospitals and University of Geneva, Geneva, Switzerland
| | - Cristelle Rodriguez
- Department of Psychiatry, University of Geneva, Geneva, Switzerland.,Medical Direction, Geneva University Hospitals, Geneva, Switzerland
| | - Sven Haller
- Department of Neuroradiology, Faculty of Medicine of the University of Geneva, Geneva, Switzerland.,CIRD-Centre d'Imagerie Rive Droite, Geneva, Switzerland.,Department of Surgical Sciences, Radiology, Uppsala University, Uppsala, Sweden
| | - Valentina Garibotto
- Department of Nuclear Medicine and Molecular Imaging, Diagnostic Department, Geneva University Hospitals and University of Geneva, Geneva, Switzerland
| | - François R Herrmann
- Department of Rehabilitation and Geriatrics, Geneva University Hospitals and University of Geneva, Geneva, Switzerland
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Wolters EE, Dodich A, Boccardi M, Corre J, Drzezga A, Hansson O, Nordberg A, Frisoni GB, Garibotto V, Ossenkoppele R. Clinical validity of increased cortical uptake of [ 18F]flortaucipir on PET as a biomarker for Alzheimer's disease in the context of a structured 5-phase biomarker development framework. Eur J Nucl Med Mol Imaging 2021; 48:2097-2109. [PMID: 33547556 PMCID: PMC8175307 DOI: 10.1007/s00259-020-05118-w] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2020] [Accepted: 11/15/2020] [Indexed: 12/14/2022]
Abstract
PURPOSE In 2017, the Geneva Alzheimer's disease (AD) Biomarker Roadmap initiative adapted the framework of the systematic validation of oncological diagnostic biomarkers to AD biomarkers, with the aim to accelerate their development and implementation in clinical practice. With this work, we assess the maturity of [18F]flortaucipir PET and define its research priorities. METHODS The level of maturity of [18F]flortaucipir was assessed based on the AD Biomarker Roadmap. The framework assesses analytical validity (phases 1-2), clinical validity (phases 3-4), and clinical utility (phase 5). RESULTS The main aims of phases 1 (rationale for use) and 2 (discriminative ability) have been achieved. [18F]Flortaucipir binds with high affinity to paired helical filaments of tau and has favorable kinetic properties and excellent discriminative accuracy for AD. The majority of secondary aims of phase 2 were fully achieved. Multiple studies showed high correlations between ante-mortem [18F]flortaucipir PET and post-mortem tau (as assessed by histopathology), and also the effects of covariates on tracer binding are well studied. The aims of phase 3 (early detection ability) were only partially or preliminarily achieved, and the aims of phases 4 and 5 were not achieved. CONCLUSION Current literature provides partial evidence for clinical utility of [18F]flortaucipir PET. The aims for phases 1 and 2 were mostly achieved. Phase 3 studies are currently ongoing. Future studies including representative MCI populations and a focus on healthcare outcomes are required to establish full maturity of phases 4 and 5.
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Affiliation(s)
- E E Wolters
- Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, location VUmc, PO Box 7057, 1007 MB, Amsterdam, The Netherlands.
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands.
| | - A Dodich
- NIMTlab - Neuroimaging and Innovative Molecular Tracers Laboratory, University of Geneva, Geneva, Switzerland
- Centre for Mind/Brain Sciences-CIMeC, University of Trento, Rovereto, Italy
| | - M Boccardi
- Late Translational Dementia Studies Group, German Center for Neurodegenerative Diseases (DZNE), Rostock-Greifswald site, Rostock, Germany
| | - J Corre
- NIMTlab - Neuroimaging and Innovative Molecular Tracers Laboratory, University of Geneva, Geneva, Switzerland
- CURIC, Centre Universitaire Romand d'Implants Cochléaires, Department of Clinical Neurosciences, University of Geneva, Geneva, Switzerland
| | - A Drzezga
- Faculty of Medicine, University of Cologne, Cologne, Germany
- Institute of Neuroscience and Medicine (INM-2), Molecular Organization of the Brain, Research Center Jülich, Jülich, Germany
- German Center for Neurodegenerative Diseases (DZNE), Bonn-Cologne, Germany
| | - O Hansson
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
| | - A Nordberg
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - G B Frisoni
- LANVIE - Laboratory of Neuroimaging of Aging, University of Geneva, Geneva, Switzerland
- Memory Clinic, University Hospital, Geneva, Switzerland
| | - V Garibotto
- NIMTlab - Neuroimaging and Innovative Molecular Tracers Laboratory, University of Geneva, Geneva, Switzerland
| | - R Ossenkoppele
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
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Ashton NJ, Leuzy A, Karikari TK, Mattsson-Carlgren N, Dodich A, Boccardi M, Corre J, Drzezga A, Nordberg A, Ossenkoppele R, Zetterberg H, Blennow K, Frisoni GB, Garibotto V, Hansson O. The validation status of blood biomarkers of amyloid and phospho-tau assessed with the 5-phase development framework for AD biomarkers. Eur J Nucl Med Mol Imaging 2021; 48:2140-2156. [PMID: 33677733 PMCID: PMC8175325 DOI: 10.1007/s00259-021-05253-y] [Citation(s) in RCA: 75] [Impact Index Per Article: 25.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2020] [Accepted: 02/09/2021] [Indexed: 12/14/2022]
Abstract
PURPOSE The development of blood biomarkers that reflect Alzheimer's disease (AD) pathophysiology (phosphorylated tau and amyloid-β) has offered potential as scalable tests for dementia differential diagnosis and early detection. In 2019, the Geneva AD Biomarker Roadmap Initiative included blood biomarkers in the systematic validation of AD biomarkers. METHODS A panel of experts convened in November 2019 at a two-day workshop in Geneva. The level of maturity (fully achieved, partly achieved, preliminary evidence, not achieved, unsuccessful) of blood biomarkers was assessed based on the Biomarker Roadmap methodology and discussed fully during the workshop which also evaluated cerebrospinal fluid (CSF) and positron emission tomography (PET) biomarkers. RESULTS Plasma p-tau has shown analytical validity (phase 2 primary aim 1) and first evidence of clinical validity (phase 3 primary aim 1), whereas the maturity level for Aβ remains to be partially achieved. Full and partial achievement has been assigned to p-tau and Aβ, respectively, in their associations to ante-mortem measures (phase 2 secondary aim 2). However, only preliminary evidence exists for the influence of covariates, assay comparison and cut-off criteria. CONCLUSIONS Despite the relative infancy of blood biomarkers, in comparison to CSF biomarkers, much has already been achieved for phases 1 through 3 - with p-tau having greater success in detecting AD and predicting disease progression. However, sufficient data about the effect of covariates on the biomarker measurement is lacking. No phase 4 (real-world performance) or phase 5 (assessment of impact/cost) aim has been tested, thus not achieved.
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Affiliation(s)
- N J Ashton
- Institute of Neuroscience & Physiology, Department of Psychiatry & Neurochemistry, Sahlgrenska Academy, University of Gothenburg, House V3/SU, SE-431 80, Mölndal, Sweden.
- Department of Old Age Psychiatry, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.
- Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, Gothenburg, Sweden.
| | - A Leuzy
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, Lund, Sweden
| | - T K Karikari
- Institute of Neuroscience & Physiology, Department of Psychiatry & Neurochemistry, Sahlgrenska Academy, University of Gothenburg, House V3/SU, SE-431 80, Mölndal, Sweden
| | - N Mattsson-Carlgren
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, Lund, Sweden
- Department of Neurology, Skåne University Hospital, Lund, Sweden
- Wallenberg Centre for Molecular Medicine, Lund University, Lund, Sweden
| | - A Dodich
- NIMTlab - Neuroimaging and Innovative Molecular Tracers Laboratory, University of Geneva, Geneva, Switzerland
- Center for Neurocognitive Rehabilitation (CeRiN), CIMeC, University of Trento, Trento, Italy
| | - M Boccardi
- German Center for Neurodegenerative Diseases (DZNE), Rostock-Greifswald, Rostock, Germany
- LANVIE - Laboratory of Neuroimaging of Aging, University of Geneva, Geneva, Switzerland
| | - J Corre
- Centre National de la Recherche Scientifique, Montpellier, France
| | - A Drzezga
- Medical Faculty and University Hospital of Cologne, Cologne, Germany
| | - A Nordberg
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
- Theme Aging, Karolinska University Hospital Stockholm, Stockholm, Sweden
| | - R Ossenkoppele
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, Lund, Sweden
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - H Zetterberg
- Institute of Neuroscience & Physiology, Department of Psychiatry & Neurochemistry, Sahlgrenska Academy, University of Gothenburg, House V3/SU, SE-431 80, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Gothenburg, Sweden
- Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK
- UK Dementia Research Institute at UCL, London, UK
| | - K Blennow
- Institute of Neuroscience & Physiology, Department of Psychiatry & Neurochemistry, Sahlgrenska Academy, University of Gothenburg, House V3/SU, SE-431 80, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - G B Frisoni
- German Center for Neurodegenerative Diseases (DZNE), Rostock-Greifswald, Rostock, Germany
- Memory Clinic, Geneva University Hospitals, Geneva, Switzerland
| | - V Garibotto
- NIMTlab - Neuroimaging and Innovative Molecular Tracers Laboratory, University of Geneva, Geneva, Switzerland
- Diagnostic Department, University Hospitals of Geneva, Geneva, Switzerland
| | - O Hansson
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, Lund, Sweden.
- UK Dementia Research Institute at UCL, London, UK.
- Memory Clinic, Skåne University Hospital, SE-205 02, Malmö, Sweden.
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Bischof GN, Dodich A, Boccardi M, van Eimeren T, Festari C, Barthel H, Hansson O, Nordberg A, Ossenkoppele R, Sabri O, Giovanni BFG, Garibotto V, Drzezga A. Clinical validity of second-generation tau PET tracers as biomarkers for Alzheimer's disease in the context of a structured 5-phase development framework. Eur J Nucl Med Mol Imaging 2021; 48:2110-2120. [PMID: 33590274 PMCID: PMC8175320 DOI: 10.1007/s00259-020-05156-4] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2020] [Accepted: 12/07/2020] [Indexed: 12/16/2022]
Abstract
PURPOSE In 2017, the Geneva Alzheimer's disease (AD) strategic biomarker roadmap initiative proposed a framework of the systematic validation AD biomarkers to harmonize and accelerate their development and implementation in clinical practice. Here, we use this framework to examine the translatability of the second-generation tau PET tracers into the clinical context. METHODS All available literature was systematically searched based on a set of search terms that related independently to analytic validity (phases 1-2), clinical validity (phase 3-4), and clinical utility (phase 5). The progress on each of the phases was determined based on scientific criteria applied for each phase and coded as fully, partially, preliminary achieved or not achieved at all. RESULTS The validation of the second-generation tau PET tracers has successfully passed the analytical phase 1 of the strategic biomarker roadmap. Assay definition studies showed evidence on the superiority over first-generation tau PET tracers in terms of off-target binding. Studies have partially achieved the primary aim of the analytical validity stage (phase 2), and preliminary evidence has been provided for the assessment of covariates on PET signal retention. Studies investigating of the clinical validity in phases 3, 4, and 5 are still underway. CONCLUSION The current literature provides overall preliminary evidence on the establishment of the second-generation tau PET tracers into the clinical context, thereby successfully addressing some methodological issues from the tau PET tracer of the first generation. Nevertheless, bigger cohort studies, longitudinal follow-up, and examination of diverse disease population are still needed to gauge their clinical validity.
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Affiliation(s)
- Gérard N Bischof
- Department of Nuclear Medicine, University Hospital Cologne, Cologne, Germany.
| | - Alessandra Dodich
- NIMTlab, Neuroimaging and Innovative Molecular Tracers Laboratory, University of Geneva, Geneva, Switzerland
- Center for Neurocognitive Rehabilitation (CeRiN), CIMeC, University of Trento, Trento, Italy
| | - Marina Boccardi
- German Center for Neurodegenerative Disorders (DZNE), Rostock/Greifswald, Rostock, Germany
- German Center for Neurodegenerative Disorders (DZNE), Bonn/Cologne, Germany
| | - Thilo van Eimeren
- Department of Nuclear Medicine, University Hospital Cologne, Cologne, Germany
- German Center for Neurodegenerative Disorders (DZNE), Rostock/Greifswald, Rostock, Germany
- German Center for Neurodegenerative Disorders (DZNE), Bonn/Cologne, Germany
| | - Cristina Festari
- LANE - Laboratory of Alzheimer's Neuroimaging and Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Henryk Barthel
- Department of Nuclear Medicine, University of Leipzig, Leipzig, Germany
| | - Oskar Hansson
- Memory Clinic, Skåne University Hopsital, Malmö, Sweden
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
| | - Agneta Nordberg
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - Rik Ossenkoppele
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, Netherlands
| | - Osama Sabri
- Department of Nuclear Medicine, University of Leipzig, Leipzig, Germany
| | - B Frisoni G Giovanni
- NIMTlab, Neuroimaging and Innovative Molecular Tracers Laboratory, University of Geneva, Geneva, Switzerland
- Memory Center - Department of Rehabilitation and Geriatrics, Geneva University Hospitals, Geneva, Switzerland
| | - Valentina Garibotto
- NIMTlab, Neuroimaging and Innovative Molecular Tracers Laboratory, University of Geneva, Geneva, Switzerland
- Nuclear Medicine and Molecular Imaging Division, Diagnostic Department, Geneva University Hospitals, Genève, Switzerland
| | - Alexander Drzezga
- Department of Nuclear Medicine, University Hospital Cologne, Cologne, Germany
- German Center for Neurodegenerative Disorders (DZNE), Rostock/Greifswald, Rostock, Germany
- German Center for Neurodegenerative Disorders (DZNE), Bonn/Cologne, Germany
- Molecular Organization of the Brain, Institute for Neuroscience and Medicine (INM-2), Jülich, Germany
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Boccardi M, Dodich A, Albanese E, Gayet-Ageron A, Festari C, Ashton NJ, Bischof GN, Chiotis K, Leuzy A, Wolters EE, Walter MA, Rabinovici GD, Carrillo M, Drzezga A, Hansson O, Nordberg A, Ossenkoppele R, Villemagne VL, Winblad B, Frisoni GB, Garibotto V. The strategic biomarker roadmap for the validation of Alzheimer's diagnostic biomarkers: methodological update. Eur J Nucl Med Mol Imaging 2021; 48:2070-2085. [PMID: 33688996 PMCID: PMC8175304 DOI: 10.1007/s00259-020-05120-2] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2020] [Accepted: 11/15/2020] [Indexed: 12/11/2022]
Abstract
BACKGROUND The 2017 Alzheimer's disease (AD) Strategic Biomarker Roadmap (SBR) structured the validation of AD diagnostic biomarkers into 5 phases, systematically assessing analytical validity (Phases 1-2), clinical validity (Phases 3-4), and clinical utility (Phase 5) through primary and secondary Aims. This framework allows to map knowledge gaps and research priorities, accelerating the route towards clinical implementation. Within an initiative aimed to assess the development of biomarkers of tau pathology, we revised this methodology consistently with progress in AD research. METHODS We critically appraised the adequacy of the 2017 Biomarker Roadmap within current diagnostic frameworks, discussed updates at a workshop convening the Alzheimer's Association and 8 leading AD biomarker research groups, and detailed the methods to allow consistent assessment of aims achievement for tau and other AD diagnostic biomarkers. RESULTS The 2020 update applies to all AD diagnostic biomarkers. In Phases 2-3, we admitted a greater variety of study designs (e.g., cross-sectional in addition to longitudinal) and reference standards (e.g., biomarker confirmation in addition to clinical progression) based on construct (in addition to criterion) validity. We structured a systematic data extraction to enable transparent and formal evidence assessment procedures. Finally, we have clarified issues that need to be addressed to generate data eligible to evidence-to-decision procedures. DISCUSSION This revision allows for more versatile and precise assessment of existing evidence, keeps up with theoretical developments, and helps clinical researchers in producing evidence suitable for evidence-to-decision procedures. Compliance with this methodology is essential to implement AD biomarkers efficiently in clinical research and diagnostics.
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Affiliation(s)
- Marina Boccardi
- German Center for Neurodegenerative Diseases DZNE-Standort Rostock/Greifswald, Gehlsheimer Str. 20, 18147, Rostock, Germany.
- LANVIE - Laboratory of Neuroimaging of Aging, University of Geneva, Geneva, Switzerland.
| | - Alessandra Dodich
- Center for Neurocognitive Rehabilitation (CeRiN), CIMeC, University of Trento, Trento, Italy
- NIMTlab - Neuroimaging and Innovative Molecular Tracers Laboratory, University of Geneva, Geneva, Switzerland
| | - Emiliano Albanese
- USI - Università della Svizzera Italiana, Institute of Public Health (IPH), Lugano, Switzerland
| | - Angèle Gayet-Ageron
- Division of Clinical Epidemiology, Department of Health and Community Medicine, University of Geneva & University Hospitals of Geneva, Geneva, Switzerland
| | - Cristina Festari
- LANE - Laboratory of Alzheimer's Neuroimaging and Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Nicholas J Ashton
- Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, Gothenburg, Sweden
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, The Sahlgrenska Academy at The University of Gothenburg, Molndal, Sweden
- NIHR Biomedical Research Centre for Mental Health and Biomedical Research Unit for Dementia at South London and Maudsley NHS Foundation, London, UK
- Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Gérard N Bischof
- Department of Nuclear Medicine, University Hospital Cologne, Cologne, Germany
| | - Konstantinos Chiotis
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
- Theme Neurology, Karolinska University Hospital, Stockholm, Sweden
| | - Antoine Leuzy
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - Emma E Wolters
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, Netherlands
| | - Martin A Walter
- Nuclear Medicine and Molecular Division, Geneva Medical Hospital, Geneva, Switzerland
| | - Gil D Rabinovici
- Departments of Neurology, Radiology & Biomedical Imaging, University of California, San Francisco, CA, USA
| | | | - Alexander Drzezga
- Faculty of Medicine, University of Cologne, Cologne, Germany
- German Center for Neurodegenerative Diseases (DZNE), Bonn/Cologne, Germany
- Molecular Organization of the Brain, Research Center Jülich, Institute of Neuroscience and Medicine (INM-2), Julich, Germany
| | - Oskar Hansson
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, Malmo, Sweden
| | - Agneta Nordberg
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
- Karolinska University Hospital, Theme Aging, Geriatric Clinic, Huddinge, Sweden
| | - Rik Ossenkoppele
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, Netherlands
- Department of Clinical Memory Research, Lund University, Lund, Sweden
| | - Victor L Villemagne
- Department of Molecular Imaging & Therapy, Austin Health, Melbourne, VIC, Australia
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsilvania, USA
| | - Bengt Winblad
- Karolinska University Hospital, Theme Aging, Geriatric Clinic, Huddinge, Sweden
- Department of Neurobiology, Care Sciences and Society, Division of Neurogeriatrics, Karolinska Institutet, Stockholm, Sweden
| | - Giovanni B Frisoni
- LANVIE - Laboratory of Neuroimaging of Aging, University of Geneva, Geneva, Switzerland
- Memory Clinic, University Hospital, Geneva, Switzerland
| | - Valentina Garibotto
- NIMTlab - Neuroimaging and Innovative Molecular Tracers Laboratory, University of Geneva, Geneva, Switzerland
- Nuclear Medicine and Molecular Division, Geneva Medical Hospital, Geneva, Switzerland
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Clinical validity of increased cortical binding of tau ligands of the THK family and PBB3 on PET as biomarkers for Alzheimer's disease in the context of a structured 5-phase development framework. Eur J Nucl Med Mol Imaging 2021; 48:2086-2096. [PMID: 33723628 PMCID: PMC8175292 DOI: 10.1007/s00259-021-05277-4] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2020] [Accepted: 02/21/2021] [Indexed: 12/28/2022]
Abstract
PURPOSE The research community has focused on defining reliable biomarkers for the early detection of the pathological hallmarks of Alzheimer's disease (AD). In 2017, the Geneva AD Biomarker Roadmap initiative adapted the framework for the systematic validation of oncological biomarkers to AD, with the aim to accelerate their development and implementation in clinical practice. The aim of this work was to assess the validation status of tau PET ligands of the THK family and PBB3 as imaging biomarkers for AD, based on the Biomarker Roadmap methodology. METHODS A panel of experts in AD biomarkers convened in November 2019 at a 2-day workshop in Geneva. The level of clinical validity of tau PET ligands of the THK family and PBB3 was assessed based on the 5-phase development framework before the meeting and discussed during the workshop. RESULTS PET radioligands of the THK family discriminate well between healthy controls and patients with AD dementia (phase 2; partly achieved) and recent evidence suggests an accurate diagnostic accuracy at the mild cognitive impairment (MCI) stage of the disease (phase 3; partly achieved). The phases 2 and 3 were considered not achieved for PBB3 since no evidence exists about the ligand's diagnostic accuracy. Preliminary evidence exists about the secondary aims of each phase for all ligands. CONCLUSION Much work remains for completing the aims of phases 2 and 3 and replicating the available evidence. However, it is unlikely that the validation process for these tracers will be completed, given the presence of off-target binding and the development of second-generation tracers with improved binding and pharmacokinetic properties.
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2020 update on the clinical validity of cerebrospinal fluid amyloid, tau, and phospho-tau as biomarkers for Alzheimer's disease in the context of a structured 5-phase development framework. Eur J Nucl Med Mol Imaging 2021; 48:2121-2139. [PMID: 33674895 PMCID: PMC8175301 DOI: 10.1007/s00259-021-05258-7] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2020] [Accepted: 02/11/2021] [Indexed: 12/15/2022]
Abstract
Purpose In the last decade, the research community has focused on defining reliable biomarkers for the early detection of Alzheimer’s disease (AD) pathology. In 2017, the Geneva AD Biomarker Roadmap Initiative adapted a framework for the systematic validation of oncological biomarkers to cerebrospinal fluid (CSF) AD biomarkers—encompassing the 42 amino-acid isoform of amyloid-β (Aβ42), phosphorylated-tau (P-tau), and Total-tau (T-tau)—with the aim to accelerate their development and clinical implementation. The aim of this work is to update the current validation status of CSF AD biomarkers based on the Biomarker Roadmap methodology. Methods A panel of experts in AD biomarkers convened in November 2019 at a 2-day workshop in Geneva. The level of maturity (fully achieved, partly achieved, preliminary evidence, not achieved, unsuccessful) of CSF AD biomarkers was assessed based on the Biomarker Roadmap methodology before the meeting and presented and discussed during the workshop. Results By comparison to the previous 2017 Geneva Roadmap meeting, the primary advances in CSF AD biomarkers have been in the area of a unified protocol for CSF sampling, handling and storage, the introduction of certified reference methods and materials for Aβ42, and the introduction of fully automated assays. Additional advances have occurred in the form of defining thresholds for biomarker positivity and assessing the impact of covariates on their discriminatory ability. Conclusions Though much has been achieved for phases one through three, much work remains in phases four (real world performance) and five (assessment of impact/cost). To a large degree, this will depend on the availability of disease-modifying treatments for AD, given these will make accurate and generally available diagnostic tools key to initiate therapy. Supplementary Information The online version contains supplementary material available at 10.1007/s00259-021-05258-7.
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Zhang Q, Wang Q, He C, Fan D, Zhu Y, Zang F, Tan C, Zhang S, Shu H, Zhang Z, Feng H, Wang Z, Xie C. Altered Regional Cerebral Blood Flow and Brain Function Across the Alzheimer's Disease Spectrum: A Potential Biomarker. Front Aging Neurosci 2021; 13:630382. [PMID: 33692680 PMCID: PMC7937726 DOI: 10.3389/fnagi.2021.630382] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2020] [Accepted: 01/20/2021] [Indexed: 12/14/2022] Open
Abstract
Objective: To investigate variation in the characteristics of regional cerebral blood flow (rCBF), brain activity, and intrinsic functional connectivity (FC) across the Alzheimer's disease spectrum (ADS). Methods: The study recruited 20 individuals in each of the following categories: Alzheimer's disease (AD), mild cognitive impairment (MCI), subjective cognitive decline (SCD), and healthy control (HC). All participants completed the 3.0T resting-state functional MRI (rs-fMRI) and arterial spin labeling scans in addition to neuropsychological tests. Additionally, the normalized CBF, regional homogeneity (ReHo), and amplitude of low-frequency fluctuation (ALFF) of individual subjects were compared in the ADS. Moreover, the changes in intrinsic FC were investigated across the ADS using the abnormal rCBF regions as seeds and behavioral correlations. Finally, a support-vector classifier model of machine learning was used to distinguish individuals with ADS from HC. Results: Compared to the HC subjects, patients with AD showed the poorest level of rCBF in the left precuneus (LPCUN) and right middle frontal gyrus (RMFG) among all participants. In addition, there was a significant decrease in the ALFF in the bilateral posterior cingulate cortex (PCC) and ReHo in the right PCC. Moreover, RMFG- and LPCUN-based FC analysis revealed that the altered FCs were primarily located in the posterior brain regions. Finally, a combination of altered rCBF, ALFF, and ReHo in posterior cingulate cortex/precuneus (PCC/PCUN) showed a better ability to differentiate ADS from HC, AD from SCD and MCI, but not MCI from SCD. Conclusions: The study demonstrated the significance of an altered rCBF and brain activity in the early stages of ADS. These findings, therefore, present a potential diagnostic neuroimaging-based biomarker in ADS. Additionally, the study provides a better understanding of the pathophysiology of AD.
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Affiliation(s)
- Qianqian Zhang
- Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, China
| | - Qing Wang
- Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, China
| | - Cancan He
- Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, China
| | - Dandan Fan
- Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, China
| | - Yao Zhu
- Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, China
| | - Feifei Zang
- Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, China
| | - Chang Tan
- Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, China
| | - Shaoke Zhang
- Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, China
| | - Hao Shu
- Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, China
| | - Zhijun Zhang
- Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, China.,Neuropsychiatric Institute, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, China.,The Key Laboratory of Developmental Genes and Human Disease, Southeast University, Nanjing, China
| | - Haixia Feng
- Department of Nursing, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, China
| | - Zan Wang
- Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, China
| | - Chunming Xie
- Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, China.,Neuropsychiatric Institute, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, China.,The Key Laboratory of Developmental Genes and Human Disease, Southeast University, Nanjing, China
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Treyer V, Meyer RS, Buchmann A, Crameri GAG, Studer S, Saake A, Gruber E, Unschuld PG, Nitsch RM, Hock C, Gietl AF. Physical activity is associated with lower cerebral beta-amyloid and cognitive function benefits from lifetime experience-a study in exceptional aging. PLoS One 2021; 16:e0247225. [PMID: 33606797 PMCID: PMC7895362 DOI: 10.1371/journal.pone.0247225] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2020] [Accepted: 02/03/2021] [Indexed: 01/10/2023] Open
Abstract
BACKGROUND Exceptional agers (85+ years) are characterized by preserved cognition presumably due to high cognitive reserve. In the current study, we examined whether personality, risk and protective factors for dementia as well as quality of life are associated with core features of Alzheimer's disease (amyloid-deposition and hippocampal volume) as well as cognition in exceptional aging. METHODS We studied 49 exceptional agers (average 87.8 years, range 84-94 years), with preserved activities of daily living and absence of dementia. All participants received a detailed clinical and neuropsychological examination. We used established questionnaires to measure lifetime experience, personality, recent physical and cognitive activity as well as quality of life. Cerebral amyloid-deposition was estimated by 18-[F]-Flutemetamol-PET and manual hippocampal volumetry was performed on 3D T1 MRI images. RESULTS In this sample of exceptional agers with preserved activities of daily living, we found intact cognitive performance in the subjects with the highest amyloid-load in the brain, but a lower quality of life with respect to autonomy as well as higher neuroticism. Higher self-reported physical activity in the last twelve months went with a lower amyloid load. Higher self-reported leisure-time/ not work-related activity went with better executive functioning at older age. CONCLUSION Even in exceptional aging, high amyloid load may subtly influence personality and quality of life. Our findings support a close relationship between high physical activity and low amyloid-deposition and underscore the importance of extracurricular activities for executive functions. As executive functions are known to be a central resource for everyday functioning in fostering extracurricular activities may be effective in delaying the onset of dementia.
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Affiliation(s)
- Valerie Treyer
- Institute for Regenerative Medicine (IREM), University of Zurich, Zurich, Switzerland
- Department of Nuclear Medicine, University Hospital of Zurich, University of Zurich, Zurich, Switzerland
| | - Rafael S. Meyer
- Institute for Regenerative Medicine (IREM), University of Zurich, Zurich, Switzerland
| | - Andreas Buchmann
- Institute for Regenerative Medicine (IREM), University of Zurich, Zurich, Switzerland
| | | | - Sandro Studer
- Institute for Regenerative Medicine (IREM), University of Zurich, Zurich, Switzerland
| | - Antje Saake
- Institute for Regenerative Medicine (IREM), University of Zurich, Zurich, Switzerland
| | - Esmeralda Gruber
- Institute for Regenerative Medicine (IREM), University of Zurich, Zurich, Switzerland
| | - Paul G. Unschuld
- Institute for Regenerative Medicine (IREM), University of Zurich, Zurich, Switzerland
- Hospital for Psychogeriatric Medicine, Psychiatric University Hospital Zurich, Zurich, Switzerland
| | - Roger M. Nitsch
- Institute for Regenerative Medicine (IREM), University of Zurich, Zurich, Switzerland
- Neurimmune, Schlieren-Zurich, Switzerland
| | - Christoph Hock
- Institute for Regenerative Medicine (IREM), University of Zurich, Zurich, Switzerland
- Neurimmune, Schlieren-Zurich, Switzerland
| | - Anton F. Gietl
- Institute for Regenerative Medicine (IREM), University of Zurich, Zurich, Switzerland
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Different Patterns of Gray Matter Volume Reduction in Early-onset and Late-onset Alzheimer Disease. Cogn Behav Neurol 2021; 33:253-258. [PMID: 33264152 DOI: 10.1097/wnn.0000000000000245] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
BACKGROUND Individuals with early-onset Alzheimer disease (EOAD) differ from those with late-onset Alzheimer disease (LOAD) not only in genetics and age at onset but also in their clinical symptoms. OBJECTIVE To differentiate the neuropathological and neurocognitive features of EOAD and LOAD by comparing the pattern of regional gray matter volume (GMV) reduction and its symptomatic correlates. METHOD Three-dimensional T1-weighted MRIs and Mini-Mental State Examination (MMSE) scores were obtained from 12 individuals with EOAD, 65 with LOAD, and 49 healthy controls (HC). Regional GMV reduction between the three groups was assessed using voxel-based morphometry. Multiple regression analyses were conducted with MMSE total score as an independent variable. RESULTS Compared to the HC, both AD groups showed a significant GMV reduction in the bilateral hippocampus and the left temporoparietal junction; in addition, the LOAD group showed one in the bilateral anterior temporal lobes. Multiple regression analyses revealed a positive correlation between MMSE total score and GMV in the left anterior temporal lobe in both AD groups; that is, lower scores were associated with reduced GMV. Interestingly, a positive correlation in hippocampal GMV was revealed only in the LOAD group. CONCLUSION MMSE total score is associated with the anterior temporal lobe volume in individuals with AD. Hippocampal volume and its relationship with MMSE total score are associated with LOAD pathophysiology but not EOAD pathophysiology. The hippocampal volume reduction and low MMSE scores are hallmarks of LOAD but are less specific to EOAD, which may cause a delay in diagnosis.
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Hernes SS, Flak MM, Løhaugen GCC, Skranes J, Hol HR, Madsen BO, Knapskog AB, Engvig A, Pripp A, Ulstein I, Lona T, Zhang X, Chang L. Working Memory Training in Amnestic and Non-amnestic Patients With Mild Cognitive Impairment: Preliminary Findings From Genotype Variants on Training Effects. Front Aging Neurosci 2021; 13:624253. [PMID: 33658917 PMCID: PMC7917210 DOI: 10.3389/fnagi.2021.624253] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2020] [Accepted: 01/12/2021] [Indexed: 11/13/2022] Open
Abstract
Working memory training (WMT) effects may be modulated by mild cognitive impairment (MCI) subtypes, and variations in APOE-epsilon (APOE-ε) and LMX1A genotypes. Sixty-one individuals (41 men/20 women, mean age 66 years) diagnosed with MCI (31 amnestic/30 non-amnestic) and genotyped for APOE-ε and LMX1A completed 4 weeks/20-25 sessions of WMT. Cognitive functions were assessed before, 4 weeks and 16 weeks after WMT. Except for Processing Speed, the non-amnestic MCI group (naMCI) outperformed the amnestic MCI (aMCI) group in all cognitive domains across all time-points. At 4 weeks, working memory function improved in both groups (p < 0.0001), but at 16 weeks the effects only remained in the naMCI group. Better performance was found after training for the naMCI patients with LMX1A-AA genotype and for the APOE-ε4 carriers. Only the naMCI-APOE-ε4 group showed improved Executive Function at 16 weeks. WMT improved working memory and some non-trained cognitive functions in individuals with MCI. The naMCI group had greater training gain than aMCI group, especially in those with LMX1A-AA genotype and among APOE-ε4-carriers. Further research with larger sample sizes for the subgroups and longer follow-up evaluations is warranted.
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Affiliation(s)
- Susanne S Hernes
- Department of Geriatric and Internal Medicine, Sørlandet Hospital, Arendal, Norway.,Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Marianne M Flak
- Department of Clinical and Molecular Medicine, Norwegian University of Science and Technology, Trondheim, Norway.,Department of Pediatrics, Sørlandet Hospital HF, Arendal, Norway
| | - Gro C C Løhaugen
- Department of Pediatrics, Sørlandet Hospital HF, Arendal, Norway
| | - Jon Skranes
- Department of Clinical and Molecular Medicine, Norwegian University of Science and Technology, Trondheim, Norway.,Department of Pediatrics, Sørlandet Hospital HF, Arendal, Norway
| | - Haakon R Hol
- Department of Clinical Science, University of Bergen, Bergen, Norway.,Department of Radiology, Sørlandet Hospital HF, Arendal, Norway
| | - Bengt-Ove Madsen
- Department of Geriatric and Internal Medicine, Sørlandet Hospital, Arendal, Norway
| | - Anne-Brita Knapskog
- Department of Geriatric Medicine, The Memory Clinic, Oslo University Hospital, Oslo, Norway
| | - Andreas Engvig
- Department of Medicine, Diakonhjemmet Hospital, Oslo, Norway
| | - Are Pripp
- Oslo Centre of Biostatistics and Epidemiology Research Support Services, Oslo University Hospital, Oslo, Norway
| | - Ingun Ulstein
- Department of Geriatric Medicine, The Memory Clinic, Oslo University Hospital, Oslo, Norway
| | - Trine Lona
- Department of Psychiatry, Age Psychiatry, The Hospital of Telemark, Skien, Norway
| | - Xin Zhang
- Department of Diagnostic Radiology and Nuclear Medicine, and Department of Neurology, University of Maryland School of Medicine, Baltimore, MD, United States
| | - Linda Chang
- Department of Diagnostic Radiology and Nuclear Medicine, and Department of Neurology, University of Maryland School of Medicine, Baltimore, MD, United States.,Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, United States.,Department of Medicine, John A. Burns School of Medicine, The University of Hawai'i at Mānoa, Honolulu, HI, United States
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31
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Villemagne VL, Barkhof F, Garibotto V, Landau SM, Nordberg A, van Berckel BNM. Molecular Imaging Approaches in Dementia. Radiology 2021; 298:517-530. [PMID: 33464184 DOI: 10.1148/radiol.2020200028] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
The increasing prevalence of dementia worldwide places a high demand on healthcare providers to perform a diagnostic work-up in relatively early stages of the disease, given that the pathologic process usually begins decades before symptoms are evident. Structural imaging is recommended to rule out other disorders and can only provide diagnosis in a late stage with limited specificity. Where PET imaging previously focused on the spatial pattern of hypometabolism, the past decade has seen the development of novel tracers to demonstrate characteristic protein abnormalities. Molecular imaging using PET/SPECT is able to show amyloid and tau deposition in Alzheimer disease and dopamine depletion in parkinsonian disorders starting decades before symptom onset. Novel tracers for neuroinflammation and synaptic density are being developed to further unravel the molecular pathologic characteristics of dementia disorders. In this article, the authors review the current status of established and emerging PET tracers in a diagnostic setting and also their value as prognostic markers in research studies and outcome measures for clinical trials in Alzheimer disease.
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Affiliation(s)
- Victor L Villemagne
- From the Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pa (V.L.V.); Department of Medicine, the University of Melbourne, Melbourne, Australia (V.L.V.); Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, VU University Medical Center, Amsterdam, the Netherlands (F.B., B.N.M.v.B.); UCL institutes of Neurology and Healthcare Engineering, London, England (F.B.); Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospitals and Laboratory of Neuroimaging and Innovative Molecular Tracers, Geneva University, Geneva, Switzerland (V.G.); Helen Wills Neuroscience Institute, University of California, Berkeley, Calif (S.M.L.); Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, Calif (S.M.L.); Department of Neurobiology, Care Sciences and Society, Center for Alzheimer Research, Karolinska Institutet, Stockholm, Sweden (A.N.); and Theme Aging, Karolinska University Hospital, Stockholm, Sweden (A.N.)
| | - Frederik Barkhof
- From the Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pa (V.L.V.); Department of Medicine, the University of Melbourne, Melbourne, Australia (V.L.V.); Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, VU University Medical Center, Amsterdam, the Netherlands (F.B., B.N.M.v.B.); UCL institutes of Neurology and Healthcare Engineering, London, England (F.B.); Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospitals and Laboratory of Neuroimaging and Innovative Molecular Tracers, Geneva University, Geneva, Switzerland (V.G.); Helen Wills Neuroscience Institute, University of California, Berkeley, Calif (S.M.L.); Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, Calif (S.M.L.); Department of Neurobiology, Care Sciences and Society, Center for Alzheimer Research, Karolinska Institutet, Stockholm, Sweden (A.N.); and Theme Aging, Karolinska University Hospital, Stockholm, Sweden (A.N.)
| | - Valentina Garibotto
- From the Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pa (V.L.V.); Department of Medicine, the University of Melbourne, Melbourne, Australia (V.L.V.); Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, VU University Medical Center, Amsterdam, the Netherlands (F.B., B.N.M.v.B.); UCL institutes of Neurology and Healthcare Engineering, London, England (F.B.); Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospitals and Laboratory of Neuroimaging and Innovative Molecular Tracers, Geneva University, Geneva, Switzerland (V.G.); Helen Wills Neuroscience Institute, University of California, Berkeley, Calif (S.M.L.); Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, Calif (S.M.L.); Department of Neurobiology, Care Sciences and Society, Center for Alzheimer Research, Karolinska Institutet, Stockholm, Sweden (A.N.); and Theme Aging, Karolinska University Hospital, Stockholm, Sweden (A.N.)
| | - Susan M Landau
- From the Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pa (V.L.V.); Department of Medicine, the University of Melbourne, Melbourne, Australia (V.L.V.); Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, VU University Medical Center, Amsterdam, the Netherlands (F.B., B.N.M.v.B.); UCL institutes of Neurology and Healthcare Engineering, London, England (F.B.); Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospitals and Laboratory of Neuroimaging and Innovative Molecular Tracers, Geneva University, Geneva, Switzerland (V.G.); Helen Wills Neuroscience Institute, University of California, Berkeley, Calif (S.M.L.); Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, Calif (S.M.L.); Department of Neurobiology, Care Sciences and Society, Center for Alzheimer Research, Karolinska Institutet, Stockholm, Sweden (A.N.); and Theme Aging, Karolinska University Hospital, Stockholm, Sweden (A.N.)
| | - Agneta Nordberg
- From the Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pa (V.L.V.); Department of Medicine, the University of Melbourne, Melbourne, Australia (V.L.V.); Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, VU University Medical Center, Amsterdam, the Netherlands (F.B., B.N.M.v.B.); UCL institutes of Neurology and Healthcare Engineering, London, England (F.B.); Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospitals and Laboratory of Neuroimaging and Innovative Molecular Tracers, Geneva University, Geneva, Switzerland (V.G.); Helen Wills Neuroscience Institute, University of California, Berkeley, Calif (S.M.L.); Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, Calif (S.M.L.); Department of Neurobiology, Care Sciences and Society, Center for Alzheimer Research, Karolinska Institutet, Stockholm, Sweden (A.N.); and Theme Aging, Karolinska University Hospital, Stockholm, Sweden (A.N.)
| | - Bart N M van Berckel
- From the Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pa (V.L.V.); Department of Medicine, the University of Melbourne, Melbourne, Australia (V.L.V.); Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, VU University Medical Center, Amsterdam, the Netherlands (F.B., B.N.M.v.B.); UCL institutes of Neurology and Healthcare Engineering, London, England (F.B.); Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospitals and Laboratory of Neuroimaging and Innovative Molecular Tracers, Geneva University, Geneva, Switzerland (V.G.); Helen Wills Neuroscience Institute, University of California, Berkeley, Calif (S.M.L.); Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, Calif (S.M.L.); Department of Neurobiology, Care Sciences and Society, Center for Alzheimer Research, Karolinska Institutet, Stockholm, Sweden (A.N.); and Theme Aging, Karolinska University Hospital, Stockholm, Sweden (A.N.)
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Pemberton HG, Goodkin O, Prados F, Das RK, Vos SB, Moggridge J, Coath W, Gordon E, Barrett R, Schmitt A, Whiteley-Jones H, Burd C, Wattjes MP, Haller S, Vernooij MW, Harper L, Fox NC, Paterson RW, Schott JM, Bisdas S, White M, Ourselin S, Thornton JS, Yousry TA, Cardoso MJ, Barkhof F. Automated quantitative MRI volumetry reports support diagnostic interpretation in dementia: a multi-rater, clinical accuracy study. Eur Radiol 2021; 31:5312-5323. [PMID: 33452627 PMCID: PMC8213665 DOI: 10.1007/s00330-020-07455-8] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2020] [Revised: 10/01/2020] [Accepted: 11/02/2020] [Indexed: 12/13/2022]
Abstract
Objectives We examined whether providing a quantitative report (QReport) of regional brain volumes improves radiologists’ accuracy and confidence in detecting volume loss, and in differentiating Alzheimer’s disease (AD) and frontotemporal dementia (FTD), compared with visual assessment alone. Methods Our forced-choice multi-rater clinical accuracy study used MRI from 16 AD patients, 14 FTD patients, and 15 healthy controls; age range 52–81. Our QReport was presented to raters with regional grey matter volumes plotted as percentiles against data from a normative population (n = 461). Nine raters with varying radiological experience (3 each: consultants, registrars, ‘non-clinical image analysts’) assessed each case twice (with and without the QReport). Raters were blinded to clinical and demographic information; they classified scans as ‘normal’ or ‘abnormal’ and if ‘abnormal’ as ‘AD’ or ‘FTD’. Results The QReport improved sensitivity for detecting volume loss and AD across all raters combined (p = 0.015* and p = 0.002*, respectively). Only the consultant group’s accuracy increased significantly when using the QReport (p = 0.02*). Overall, raters’ agreement (Cohen’s κ) with the ‘gold standard’ was not significantly affected by the QReport; only the consultant group improved significantly (κs 0.41➔0.55, p = 0.04*). Cronbach’s alpha for interrater agreement improved from 0.886 to 0.925, corresponding to an improvement from ‘good’ to ‘excellent’. Conclusion Our QReport referencing single-subject results to normative data alongside visual assessment improved sensitivity, accuracy, and interrater agreement for detecting volume loss. The QReport was most effective in the consultants, suggesting that experience is needed to fully benefit from the additional information provided by quantitative analyses. Key Points • The use of quantitative report alongside routine visual MRI assessment improves sensitivity and accuracy for detecting volume loss and AD vs visual assessment alone. • Consultant neuroradiologists’ assessment accuracy and agreement (kappa scores) significantly improved with the use of quantitative atrophy reports. • First multi-rater radiological clinical evaluation of visual quantitative MRI atrophy report for use as a diagnostic aid in dementia. Supplementary Information The online version contains supplementary material available at 10.1007/s00330-020-07455-8.
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Affiliation(s)
- Hugh G Pemberton
- Centre for Medical Image Computing (CMIC), Department of Medical Physics and Bioengineering, University College London, London, UK. .,Neuroradiological Academic Unit, UCL Queen Square Institute of Neurology, University College London, London, UK. .,Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK.
| | - Olivia Goodkin
- Centre for Medical Image Computing (CMIC), Department of Medical Physics and Bioengineering, University College London, London, UK.,Neuroradiological Academic Unit, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Ferran Prados
- Centre for Medical Image Computing (CMIC), Department of Medical Physics and Bioengineering, University College London, London, UK.,Universitat Oberta de Catalunya, Barcelona, Spain
| | - Ravi K Das
- Clinical, Educational and Health Psychology, University College London, London, UK
| | - Sjoerd B Vos
- Centre for Medical Image Computing (CMIC), Department of Medical Physics and Bioengineering, University College London, London, UK.,Neuroradiological Academic Unit, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - James Moggridge
- Neuroradiological Academic Unit, UCL Queen Square Institute of Neurology, University College London, London, UK.,Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, UCLH NHS Foundation Trust, London, UK
| | - William Coath
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Elizabeth Gordon
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Ryan Barrett
- Department of Neuroradiology, Brighton and Sussex University Hospitals, Brighton, UK
| | - Anne Schmitt
- Neuroradiological Academic Unit, UCL Queen Square Institute of Neurology, University College London, London, UK.,Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, UCLH NHS Foundation Trust, London, UK
| | - Hefina Whiteley-Jones
- Department of Neuroradiology, Brighton and Sussex University Hospitals, Brighton, UK
| | | | - Mike P Wattjes
- Department of Diagnostic and Interventional Neuroradiology, Hannover Medical School, Hannover, Germany
| | - Sven Haller
- Department of Surgical Sciences, Radiology, Uppsala University, Uppsala, Sweden
| | - Meike W Vernooij
- Department of Radiology and Nuclear Medicine, Erasmus MC University Medical Center, Rotterdam, the Netherlands.,Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, the Netherlands
| | - Lorna Harper
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Nick C Fox
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Ross W Paterson
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Jonathan M Schott
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Sotirios Bisdas
- Neuroradiological Academic Unit, UCL Queen Square Institute of Neurology, University College London, London, UK.,Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, UCLH NHS Foundation Trust, London, UK
| | - Mark White
- Digital Services, University College London Hospital, London, UK
| | - Sebastien Ourselin
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - John S Thornton
- Neuroradiological Academic Unit, UCL Queen Square Institute of Neurology, University College London, London, UK.,Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, UCLH NHS Foundation Trust, London, UK
| | - Tarek A Yousry
- Neuroradiological Academic Unit, UCL Queen Square Institute of Neurology, University College London, London, UK.,Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, UCLH NHS Foundation Trust, London, UK
| | - M Jorge Cardoso
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Frederik Barkhof
- Centre for Medical Image Computing (CMIC), Department of Medical Physics and Bioengineering, University College London, London, UK.,Neuroradiological Academic Unit, UCL Queen Square Institute of Neurology, University College London, London, UK.,Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, UCLH NHS Foundation Trust, London, UK.,Radiology & Nuclear Medicine, VU University Medical Center, Amsterdam, the Netherlands
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Hu S, Li CSR. Age-Related Structural and Functional Changes of the Hippocampus and the Relationship with Inhibitory Control. Brain Sci 2020; 10:brainsci10121013. [PMID: 33352718 PMCID: PMC7766783 DOI: 10.3390/brainsci10121013] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2020] [Revised: 12/11/2020] [Accepted: 12/16/2020] [Indexed: 12/24/2022] Open
Abstract
Aging is associated with structural and functional changes in the hippocampus, and hippocampal dysfunction represents a risk marker of Alzheimer’s disease. Previously, we demonstrated age-related changes in reactive and proactive control in the stop signal task, each quantified by the stop signal reaction time (SSRT) and sequential effect computed as the correlation between the estimated stop signal probability and go trial reaction time. Age was positively correlated with the SSRT, but not with the sequential effect. Here, we explored hippocampal gray matter volume (GMV) and activation to response inhibition and to p(Stop) in healthy adults 18 to 72 years of age. The results showed age-related reduction of right anterior hippocampal activation during stop success vs. go trials, and the hippocampal activities correlated negatively with the SSRT. In contrast, the right posterior hippocampus showed higher age-related responses to p(Stop), but the activities did not correlate with the sequential effect. Further, we observed diminished GMVs of the anterior and posterior hippocampus. However, the GMVs were not related to behavioral performance or regional activities. Together, these findings suggest that hippocampal GMVs and regional activities represent distinct neural markers of cognitive aging, and distinguish the roles of the anterior and posterior hippocampus in age-related changes in cognitive control.
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Affiliation(s)
- Sien Hu
- Department of Psychology, State University of New York at Oswego, Oswego, NY 13126, USA
- Correspondence:
| | - Chiang-shan R. Li
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT 06519, USA;
- Department of Neuroscience, Yale University School of Medicine, New Haven, CT 06520, USA
- Interdepartmental Neuroscience Program, Yale University School of Medicine, New Haven, CT 06520, USA
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Yuan Q, Yang J, Xian YF, Liu R, Chan CW, Wu W, Lin ZX. The Effect of Spinal Cord Injury on Beta-Amyloid Plaque Pathology in TgCRND8 Mouse Model of Alzheimer's Disease. Curr Alzheimer Res 2020; 17:576-586. [PMID: 32851942 DOI: 10.2174/1567205017666200807191447] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2020] [Revised: 06/16/2020] [Accepted: 06/17/2020] [Indexed: 11/22/2022]
Abstract
BACKGROUND The accumulation and aggregation of Aβ as amyloid plaques, the hallmark pathology of the Alzheimer's disease, has been found in other neurological disorders, such as traumatic brain injury. The axonal injury may contribute to the formation of Aβ plaques. Studies to date have focused on the brain, with no investigations of spinal cord, although brain and cord share the same cellular components. OBJECTIVE We utilized a spinal cord transection model to examine whether spinal cord injury acutely induced the onset or promote the progression of Aβ plaque 3 days after injury in TgCRND8 transgenic model of AD. METHODS Spinal cord transection was performed in TgCRND8 mice and its littermate control wild type mice at the age of 3 and 20 months. Immunohistochemical reactions/ELISA assay were used to determine the extent of axonal damage and occurrence/alteration of Aβ plaques or levels of Aβ at different ages in the spinal cord of TgCRND8 mice. RESULTS After injury, widespread axonal pathology indicated by intra-axonal co-accumulations of APP and its product, Aβ, was observed in perilesional region of the spinal cord in the TgCRND8 mice at the age of 3 and 20 months, as compared to age-matched non-TgCRND8 mice. However, no Aβ plaques were found in the TgCRND8 mice at the age of 3 months. The 20-month-old TgCRND8 mice with established amyloidosis in spinal cord had a reduction rather than increase in plaque burden at the lesion site compared to the tissue adjacent to the injured area and corresponding area in sham mice following spinal cord transection. The lesion site of spinal cord area was occupied by CD68 positive macrophages/ activated microglia in injured mice compared to sham animals. These results indicate that spinal cord injury does not induce the acute onset and progression of Aβ plaque deposition in the spinal cord of TgCRND8 mice. Conversely, it induces the regression of Aβ plaque deposition in TgCRND8 mice. CONCLUSION The findings underscore the dependence of traumatic axonal injury in governing acute Aβ plaque formation and provide evidence that Aβ plaque pathology may not play a role in secondary injury cascades following spinal cord injury.
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Affiliation(s)
- Qiuju Yuan
- Faculty of Medicine, School of Chinese Medicine, The Chinese University of Hong Kong, China
| | - Jian Yang
- School of Biomedical Sciences, Li Ka Shing Faculty of Medicine, The University of Hong Kong, N.T, Hong Kong SAR, China
| | - Yan-Fang Xian
- Faculty of Medicine, School of Chinese Medicine, The Chinese University of Hong Kong, China
| | - Rong Liu
- School of Biomedical Sciences, Li Ka Shing Faculty of Medicine, The University of Hong Kong, N.T, Hong Kong SAR, China
| | - Chun W Chan
- Faculty of Medicine, School of Chinese Medicine, The Chinese University of Hong Kong, China
| | - Wutian Wu
- School of Biomedical Sciences, Li Ka Shing Faculty of Medicine, The University of Hong Kong, N.T, Hong Kong SAR, China
| | - Zhi-Xiu Lin
- Faculty of Medicine, School of Chinese Medicine, The Chinese University of Hong Kong, China
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Silhan D, Bartos A, Mrzilkova J, Pashkovska O, Ibrahim I, Tintera J. The Parietal Atrophy Score on Brain Magnetic Resonance Imaging is a Reliable Visual Scale. Curr Alzheimer Res 2020; 17:534-539. [PMID: 32851946 PMCID: PMC7569282 DOI: 10.2174/1567205017666200807193957] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2020] [Revised: 05/28/2020] [Accepted: 06/28/2020] [Indexed: 11/22/2022]
Abstract
Aims The purpose of the study was to evaluate the reliability of our new visual scale for a quick atrophy assessment of parietal lobes on brain Magnetic Resonance Imaging (MRI) among different professionals. A good agreement would justify its use for differential diagnosis of neurodegenerative dementias, especially early-onset Alzheimer’s Disease (AD), in clinical settings. Methods The visual scale named the Parietal Atrophy Score (PAS) is based on a semi-quantitative assessment ranging from 0 (no atrophy) to 2 (prominent atrophy) in three parietal structures (sulcus cingularis posterior, precuneus, parietal gyri) on T1-weighted MRI coronal slices through the whole parietal lobes. We used kappa statistics to evaluate intra-rater and inter-rater agreement among four raters who independently scored parietal atrophy using PAS. Rater 1 was a neuroanatomist (JM), rater 2 was an expert in MRI acquisition and analysis (II), rater 3 was a medical student (OP) and rater 4 was a neurologist (DS) who evaluated parietal atrophy twice in a 3-month interval to assess intra-rater agreement. All raters evaluated the same 50 parietal lobes on brain MRI of 25 cognitively normal individuals with even distribution across all atrophy degrees from none to prominent according to the neurologist’s rating. Results Intra-rater agreement was almost perfect with the kappa value of 0.90. Inter-rater agreement was moderate to substantial with kappa values ranging from 0.43-0.86. Conclusion The Parietal Atrophy Score is the reliable visual scale among raters of different professions for a quick evaluation of parietal lobes on brain MRI within 1-2 minutes. We believe it could be used as an adjunct measure in differential diagnosis of dementias, especially early-onset AD.
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Affiliation(s)
- David Silhan
- Department of Neurology, Charles University, Third Faculty of Medicine, Prague, Czech Republic
| | - Ales Bartos
- Department of Neurology, Charles University, Third Faculty of Medicine, Prague, Czech Republic
| | - Jana Mrzilkova
- Department of Anatomy, Charles University, Third Faculty of Medicine, Prague, Czech Republic
| | - Olga Pashkovska
- Department of Neurology, Charles University, Third Faculty of Medicine, Prague, Czech Republic
| | - Ibrahim Ibrahim
- Institute for Clinical and Experimental Medicine, Prague, Czech Republic
| | - Jaroslav Tintera
- Institute for Clinical and Experimental Medicine, Prague, Czech Republic
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Ke J, Foley LM, Hitchens TK, Richardson RM, Modo M. Ex vivo mesoscopic diffusion MRI correlates with seizure frequency in patients with uncontrolled mesial temporal lobe epilepsy. Hum Brain Mapp 2020; 41:4529-4548. [PMID: 32691978 PMCID: PMC7555080 DOI: 10.1002/hbm.25139] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2020] [Revised: 06/08/2020] [Accepted: 07/05/2020] [Indexed: 12/28/2022] Open
Abstract
The role of hippocampal connectivity in mesial temporal lobe epilepsy (mTLE) remains poorly understood. The use of ex vivo hippocampal samples excised from patients with mTLE affords mesoscale diffusion magnetic resonance imaging (MRI) to identify individual cell layers, such as the pyramidal (PCL) and granule cell layers (GCL), which are thought to be impacted by seizure activity. Diffusion tensor imaging (DTI) of control (n = 3) and mTLE (n = 7) hippocampi on an 11.7 T MRI scanner allowed us to reveal intra‐hippocampal connectivity and evaluate how epilepsy affected mean (MD), axial (AD), and radial diffusivity (RD), as well as fractional anisotropy (FA). Regional measurements indicated a volume loss in the PCL of the cornu ammonis (CA) 1 subfield in mTLE patients compared to controls, which provided anatomical context. Diffusion measurements, as well as streamline density, were generally higher in mTLE patients compared to controls, potentially reflecting differences due to tissue fixation. mTLE measurements were more variable than controls. This variability was associated with disease severity, as indicated by a strong correlation (r = 0.87) between FA in the stratum radiatum and the frequency of seizures in patients. MD and RD of the PCL in subfields CA3 and CA4 also correlated strongly with disease severity. No correlation of MR measures with disease duration was evident. These results reveal the potential of mesoscale diffusion MRI to examine layer‐specific diffusion changes and connectivity to determine how these relate to clinical measures. Improving the visualization of intra‐hippocampal connectivity will advance the development of novel hypotheses about seizure networks.
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Affiliation(s)
- Justin Ke
- Department of Radiology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.,Department of Bioengineering, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Lesley M Foley
- Animal Imaging Center, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - T Kevin Hitchens
- Animal Imaging Center, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.,Department of Neurobiology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - R Mark Richardson
- Centre for the Neural Basis of Cognition, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.,Department of Neurological Surgery, Massachusetts General Hospital, Boston, Massachusetts, USA.,Harvard Medical School, Boston, Massachusetts, USA
| | - Michel Modo
- Department of Radiology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.,Department of Bioengineering, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.,Centre for the Neural Basis of Cognition, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.,McGowan Institute for Regenerative Medicine, Pittsburgh, Pennsylvania, USA
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Montandon ML, Haller S, Scheffler M, Giannakopoulos P, Herrmann FR, Gold G, Kövari E. Medial temporal lobe volume is associated with neuronal loss but not with hippocampal microinfarcts despite their high frequency in aging brains. Neurobiol Aging 2020; 95:9-14. [PMID: 32739558 DOI: 10.1016/j.neurobiolaging.2020.06.008] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2019] [Revised: 06/05/2020] [Accepted: 06/10/2020] [Indexed: 10/24/2022]
Abstract
Medial temporal lobe (MTL) atrophy is an important marker for the clinical diagnosis of Alzheimer's disease at its prodromal stages. Several brain lesions have been associated with MTL atrophy including hippocampal sclerosis, neurodegenerative neuronal loss, and vascular pathology. To better explore the relationship between MTL volume on MRI and age-related degenerative and microvascular hippocampal pathology, we compared MTL volume on postmortem whole brain MRI and stereological estimates of the total number of neurons, cortical microinfarcts (CMIs), and neurofibrillary tangles (NFTs) in a consecutive autopsy series of 21 older individuals (11 females and 10 males, mean age 83.3 ± 5.8; range: 74-93 years, 7 demented and 14 nondemented). Our results revealed a very high percentage of cases with hippocampal CMIs (52%), particularly in the CA1 field. MTL volume was closely related to neuronal loss in both the CA1 area of the hippocampus (p = 0.0109) and the entorhinal cortex (p = 0.0272). MTL volume was not related to total CMI volume or to the total number of NFTs in our sample. In conclusion, hippocampal CMIs are very common in old age. MTL volume is determined essentially by the number of neurons in the hippocampus and does not appear to be related to the presence of NFTs or CMIs in this region.
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Affiliation(s)
- Marie-Louise Montandon
- Department of Rehabilitation and Geriatrics, Geneva University Hospitals and University of Geneva, Thônex, Switzerland; Department of Psychiatry, Geneva University Hospitals and University of Geneva, Chêne-Bourg, Switzerland
| | - Sven Haller
- CIRD Centre d'Imagerie Rive Droite, Geneva, Switzerland; Department of Surgical Sciences, Radiology, Uppsala University, Sweden
| | - Max Scheffler
- Department of Radiology, Geneva University Hospitals and University of Geneva, Geneva, Switzerland
| | - Panteleimon Giannakopoulos
- Department of Psychiatry, Geneva University Hospitals and University of Geneva, Chêne-Bourg, Switzerland; Division of Institutional Measures, Geneva University Hospitals and University of Geneva, Geneva, Switzerland
| | - François R Herrmann
- Department of Rehabilitation and Geriatrics, Geneva University Hospitals and University of Geneva, Thônex, Switzerland
| | - Gabriel Gold
- Department of Rehabilitation and Geriatrics, Geneva University Hospitals and University of Geneva, Thônex, Switzerland
| | - Enikö Kövari
- Department of Psychiatry, Geneva University Hospitals and University of Geneva, Chêne-Bourg, Switzerland.
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Lombardi G, Crescioli G, Cavedo E, Lucenteforte E, Casazza G, Bellatorre A, Lista C, Costantino G, Frisoni G, Virgili G, Filippini G. Structural magnetic resonance imaging for the early diagnosis of dementia due to Alzheimer's disease in people with mild cognitive impairment. Cochrane Database Syst Rev 2020; 3:CD009628. [PMID: 32119112 PMCID: PMC7059964 DOI: 10.1002/14651858.cd009628.pub2] [Citation(s) in RCA: 56] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
BACKGROUND Mild cognitive impairment (MCI) due to Alzheimer's disease is the symptomatic predementia phase of Alzheimer's disease dementia, characterised by cognitive and functional impairment not severe enough to fulfil the criteria for dementia. In clinical samples, people with amnestic MCI are at high risk of developing Alzheimer's disease dementia, with annual rates of progression from MCI to Alzheimer's disease estimated at approximately 10% to 15% compared with the base incidence rates of Alzheimer's disease dementia of 1% to 2% per year. OBJECTIVES To assess the diagnostic accuracy of structural magnetic resonance imaging (MRI) for the early diagnosis of dementia due to Alzheimer's disease in people with MCI versus the clinical follow-up diagnosis of Alzheimer's disease dementia as a reference standard (delayed verification). To investigate sources of heterogeneity in accuracy, such as the use of qualitative visual assessment or quantitative volumetric measurements, including manual or automatic (MRI) techniques, or the length of follow-up, and age of participants. MRI was evaluated as an add-on test in addition to clinical diagnosis of MCI to improve early diagnosis of dementia due to Alzheimer's disease in people with MCI. SEARCH METHODS On 29 January 2019 we searched Cochrane Dementia and Cognitive Improvement's Specialised Register and the databases, MEDLINE, Embase, BIOSIS Previews, Science Citation Index, PsycINFO, and LILACS. We also searched the reference lists of all eligible studies identified by the electronic searches. SELECTION CRITERIA We considered cohort studies of any size that included prospectively recruited people of any age with a diagnosis of MCI. We included studies that compared the diagnostic test accuracy of baseline structural MRI versus the clinical follow-up diagnosis of Alzheimer's disease dementia (delayed verification). We did not exclude studies on the basis of length of follow-up. We included studies that used either qualitative visual assessment or quantitative volumetric measurements of MRI to detect atrophy in the whole brain or in specific brain regions, such as the hippocampus, medial temporal lobe, lateral ventricles, entorhinal cortex, medial temporal gyrus, lateral temporal lobe, amygdala, and cortical grey matter. DATA COLLECTION AND ANALYSIS Four teams of two review authors each independently reviewed titles and abstracts of articles identified by the search strategy. Two teams of two review authors each independently assessed the selected full-text articles for eligibility, extracted data and solved disagreements by consensus. Two review authors independently assessed the quality of studies using the QUADAS-2 tool. We used the hierarchical summary receiver operating characteristic (HSROC) model to fit summary ROC curves and to obtain overall measures of relative accuracy in subgroup analyses. We also used these models to obtain pooled estimates of sensitivity and specificity when sufficient data sets were available. MAIN RESULTS We included 33 studies, published from 1999 to 2019, with 3935 participants of whom 1341 (34%) progressed to Alzheimer's disease dementia and 2594 (66%) did not. Of the participants who did not progress to Alzheimer's disease dementia, 2561 (99%) remained stable MCI and 33 (1%) progressed to other types of dementia. The median proportion of women was 53% and the mean age of participants ranged from 63 to 87 years (median 73 years). The mean length of clinical follow-up ranged from 1 to 7.6 years (median 2 years). Most studies were of poor methodological quality due to risk of bias for participant selection or the index test, or both. Most of the included studies reported data on the volume of the total hippocampus (pooled mean sensitivity 0.73 (95% confidence interval (CI) 0.64 to 0.80); pooled mean specificity 0.71 (95% CI 0.65 to 0.77); 22 studies, 2209 participants). This evidence was of low certainty due to risk of bias and inconsistency. Seven studies reported data on the atrophy of the medial temporal lobe (mean sensitivity 0.64 (95% CI 0.53 to 0.73); mean specificity 0.65 (95% CI 0.51 to 0.76); 1077 participants) and five studies on the volume of the lateral ventricles (mean sensitivity 0.57 (95% CI 0.49 to 0.65); mean specificity 0.64 (95% CI 0.59 to 0.70); 1077 participants). This evidence was of moderate certainty due to risk of bias. Four studies with 529 participants analysed the volume of the total entorhinal cortex and four studies with 424 participants analysed the volume of the whole brain. We did not estimate pooled sensitivity and specificity for the volume of these two regions because available data were sparse and heterogeneous. We could not statistically evaluate the volumes of the lateral temporal lobe, amygdala, medial temporal gyrus, or cortical grey matter assessed in small individual studies. We found no evidence of a difference between studies in the accuracy of the total hippocampal volume with regards to duration of follow-up or age of participants, but the manual MRI technique was superior to automatic techniques in mixed (mostly indirect) comparisons. We did not assess the relative accuracy of the volumes of different brain regions measured by MRI because only indirect comparisons were available, studies were heterogeneous, and the overall accuracy of all regions was moderate. AUTHORS' CONCLUSIONS The volume of hippocampus or medial temporal lobe, the most studied brain regions, showed low sensitivity and specificity and did not qualify structural MRI as a stand-alone add-on test for an early diagnosis of dementia due to Alzheimer's disease in people with MCI. This is consistent with international guidelines, which recommend imaging to exclude non-degenerative or surgical causes of cognitive impairment and not to diagnose dementia due to Alzheimer's disease. In view of the low quality of most of the included studies, the findings of this review should be interpreted with caution. Future research should not focus on a single biomarker, but rather on combinations of biomarkers to improve an early diagnosis of Alzheimer's disease dementia.
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Affiliation(s)
- Gemma Lombardi
- University of FlorenceDepartment of Neurosciences, Psychology, Drug Research and Child Health (NEUROFARBA)Largo Brambilla, 3FlorenceItaly50134
| | - Giada Crescioli
- University of FlorenceDepartment of Neurosciences, Psychology, Drug Research and Child Health (NEUROFARBA)Largo Brambilla, 3FlorenceItaly50134
| | - Enrica Cavedo
- Pitie‐Salpetriere Hospital, Sorbonne UniversityAlzheimer Precision Medicine (APM), AP‐HP47 boulevard de l'HopitalParisFrance75013
| | - Ersilia Lucenteforte
- University of PisaDepartment of Clinical and Experimental MedicineVia Savi 10PisaItaly56126
| | - Giovanni Casazza
- Università degli Studi di MilanoDipartimento di Scienze Biomediche e Cliniche "L. Sacco"via GB Grassi 74MilanItaly20157
| | | | - Chiara Lista
- Fondazione I.R.C.C.S. Istituto Neurologico Carlo BestaNeuroepidemiology UnitVia Celoria, 11MilanoItaly20133
| | - Giorgio Costantino
- Ospedale Maggiore Policlinico, Università degli Studi di MilanoUOC Pronto Soccorso e Medicina D'Urgenza, Fondazione IRCCS Ca' GrandaMilanItaly
| | | | - Gianni Virgili
- University of FlorenceDepartment of Neurosciences, Psychology, Drug Research and Child Health (NEUROFARBA)Largo Brambilla, 3FlorenceItaly50134
| | - Graziella Filippini
- Carlo Besta Foundation and Neurological InstituteScientific Director’s Officevia Celoria, 11MilanItaly20133
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Falgàs N, Balasa M, Bargalló N, Borrego-Écija S, Ramos-Campoy O, Fernández-Villullas G, Bosch B, Olives J, Tort-Merino A, Antonell A, Castellví M, Allen IE, Sánchez-Valle R, Lladó A. Diagnostic Accuracy of MRI Visual Rating Scales in the Diagnosis of Early Onset Cognitive Impairment. J Alzheimers Dis 2020; 73:1575-1583. [DOI: 10.3233/jad-191167] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Affiliation(s)
- Neus Falgàs
- Alzheimer’s Disease and Other Cognitive Disorders Unit, Hospital Clínic, Fundació Clínic per a la Recerca Biomèdica, Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Universitat de Barcelona, Barcelona, Spain
- Atlantic Fellow for Equity in Brain Health, Global Brain Health Institute, University of California, San Francisco, CA, USA
| | - Mircea Balasa
- Alzheimer’s Disease and Other Cognitive Disorders Unit, Hospital Clínic, Fundació Clínic per a la Recerca Biomèdica, Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Universitat de Barcelona, Barcelona, Spain
- Senior Atlantic Fellow for Equity in Brain Health, Global Brain Health Institute, Trinity College, Dublin, Ireland
| | - Núria Bargalló
- Imaging Diagnostic Center, Hospital Clínic, Barcelona, Spain
- Magnetic Resonance Image Core Facility, IDIBAPS, Spain
| | - Sergi Borrego-Écija
- Alzheimer’s Disease and Other Cognitive Disorders Unit, Hospital Clínic, Fundació Clínic per a la Recerca Biomèdica, Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Universitat de Barcelona, Barcelona, Spain
| | - Oscar Ramos-Campoy
- Alzheimer’s Disease and Other Cognitive Disorders Unit, Hospital Clínic, Fundació Clínic per a la Recerca Biomèdica, Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Universitat de Barcelona, Barcelona, Spain
| | - Guadalupe Fernández-Villullas
- Alzheimer’s Disease and Other Cognitive Disorders Unit, Hospital Clínic, Fundació Clínic per a la Recerca Biomèdica, Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Universitat de Barcelona, Barcelona, Spain
| | - Beatriz Bosch
- Alzheimer’s Disease and Other Cognitive Disorders Unit, Hospital Clínic, Fundació Clínic per a la Recerca Biomèdica, Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Universitat de Barcelona, Barcelona, Spain
| | - Jaume Olives
- Alzheimer’s Disease and Other Cognitive Disorders Unit, Hospital Clínic, Fundació Clínic per a la Recerca Biomèdica, Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Universitat de Barcelona, Barcelona, Spain
| | - Adrià Tort-Merino
- Alzheimer’s Disease and Other Cognitive Disorders Unit, Hospital Clínic, Fundació Clínic per a la Recerca Biomèdica, Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Universitat de Barcelona, Barcelona, Spain
| | - Anna Antonell
- Alzheimer’s Disease and Other Cognitive Disorders Unit, Hospital Clínic, Fundació Clínic per a la Recerca Biomèdica, Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Universitat de Barcelona, Barcelona, Spain
| | - Magdalena Castellví
- Alzheimer’s Disease and Other Cognitive Disorders Unit, Hospital Clínic, Fundació Clínic per a la Recerca Biomèdica, Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Universitat de Barcelona, Barcelona, Spain
| | - Isabel E. Allen
- Department of Epidemiology and Biostatistics, University of California, San Francisco, CA, USA
| | - Raquel Sánchez-Valle
- Alzheimer’s Disease and Other Cognitive Disorders Unit, Hospital Clínic, Fundació Clínic per a la Recerca Biomèdica, Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Universitat de Barcelona, Barcelona, Spain
| | - Albert Lladó
- Alzheimer’s Disease and Other Cognitive Disorders Unit, Hospital Clínic, Fundació Clínic per a la Recerca Biomèdica, Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Universitat de Barcelona, Barcelona, Spain
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Kaipainen A, Jääskeläinen O, Liu Y, Haapalinna F, Nykänen N, Vanninen R, Koivisto AM, Julkunen V, Remes AM, Herukka SK. Cerebrospinal Fluid and MRI Biomarkers in Neurodegenerative Diseases: A Retrospective Memory Clinic-Based Study. J Alzheimers Dis 2020; 75:751-765. [PMID: 32310181 PMCID: PMC7369056 DOI: 10.3233/jad-200175] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/13/2020] [Indexed: 01/04/2023]
Abstract
BACKGROUND Cerebrospinal fluid (CSF) and magnetic resonance imaging (MRI) biomarkers of neurodegenerative diseases are relatively sensitive and specific in highly curated research cohorts, but proper validation for clinical use is mostly missing. OBJECTIVE We studied these biomarkers in a novel memory clinic cohort with a variety of different neurodegenerative diseases. METHODS This study consisted of 191 patients with subjective or objective cognitive impairment who underwent neurological, CSF biomarker (Aβ42, p-tau, and tau) and T1-weighted MRI examinations at Kuopio University Hospital. We assessed CSF and imaging biomarkers, including structural MRI focused on volumetric and cortical thickness analyses, across groups stratified based on different clinical diagnoses, including Alzheimer's disease (AD), frontotemporal dementia, dementia with Lewy bodies, Parkinson's disease, vascular dementia, and mild cognitive impairment (MCI), and subjects with no evidence of neurodegenerative disease underlying the cognitive symptoms. Imaging biomarkers were also studied by profiling subjects according to the novel amyloid, tau, and, neurodegeneration (AT(N)) classification. RESULTS Numerous imaging variables differed by clinical diagnosis, including hippocampal, amygdalar and inferior lateral ventricular volumes and entorhinal, lingual, inferior parietal and isthmus cingulate cortical thicknesses, at a false discovery rate (FDR)-corrected threshold for significance (analysis of covariance; p < 0.005). In volumetric comparisons by AT(N) profile, hippocampal volume significantly differed (p < 0.001) between patients with normal AD biomarkers and patients with amyloid pathology. CONCLUSION Our analysis suggests that CSF and MRI biomarkers function well also in clinical practice across multiple clinical diagnostic groups in addition to AD, MCI, and cognitively normal groups.
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Affiliation(s)
- Aku Kaipainen
- University of Eastern Finland, Institute of Clinical Medicine/Neurology, Kuopio, Finland
| | - Olli Jääskeläinen
- University of Eastern Finland, Institute of Clinical Medicine/Neurology, Kuopio, Finland
| | - Yawu Liu
- University of Eastern Finland, Institute of Clinical Medicine/Neurology, Kuopio, Finland
- Department of Radiology, Kuopio University Hospital, Kuopio, Finland
| | - Fanni Haapalinna
- University of Eastern Finland, Institute of Clinical Medicine/Neurology, Kuopio, Finland
| | - Niko Nykänen
- University of Eastern Finland, Institute of Clinical Medicine/Neurology, Kuopio, Finland
| | - Ritva Vanninen
- Department of Radiology, Kuopio University Hospital, Kuopio, Finland
| | - Anne M. Koivisto
- University of Eastern Finland, Institute of Clinical Medicine/Neurology, Kuopio, Finland
- Department of Neurology, Kuopio University Hospital, Kuopio, Finland
| | - Valtteri Julkunen
- Department of Neurology, Kuopio University Hospital, Kuopio, Finland
| | - Anne M. Remes
- Research Unit of Clinical Neuroscience, Neurology, University of Oulu, Oulu, Finland
- MRC, Oulu University Hospital, Oulu, Finland
| | - Sanna-Kaisa Herukka
- University of Eastern Finland, Institute of Clinical Medicine/Neurology, Kuopio, Finland
- Department of Neurology, Kuopio University Hospital, Kuopio, Finland
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Schneider LS, Geffen Y, Rabinowitz J, Thomas RG, Schmidt R, Ropele S, Weinstock M. Low-dose ladostigil for mild cognitive impairment: A phase 2 placebo-controlled clinical trial. Neurology 2019; 93:e1474-e1484. [PMID: 31492718 DOI: 10.1212/wnl.0000000000008239] [Citation(s) in RCA: 33] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2019] [Accepted: 05/10/2019] [Indexed: 01/10/2023] Open
Abstract
OBJECTIVE Ladostigil reduces oxidative stress and microglial activation in aging rats. We assessed its safety and potential efficacy in a 3-year, randomized, double-blind, placebo-controlled phase 2 clinical trial in patients with mild cognitive impairment (MCI) and medial temporal lobe atrophy. METHODS Patients 55 to 85 years of age with MCI, Clinical Dementia Rating (CDR) score of 0.5, Mini-Mental State Examination (MMSE) score >24, Wechsler Memory Scale-Revised Verbal Paired Associates I score ≤18, and Medial Temporal Lobe Atrophy Scale score >1 were stratified by APOE ε4 genotype and randomly assigned (1:1) to ladostigil 10 mg/d or placebo. Primary outcomes were safety and onset of Alzheimer disease dementia. Secondary endpoints were Neuropsychological Test Battery (NTB) composite, Disability Assessment in Dementia (DAD), and Geriatric Depression Scale (GDS) scores. Exploratory outcomes were NTB component, CDR, and MMSE scores. Biomarkers included MRI-derived whole-brain, hippocampus, and entorhinal cortex volumes. RESULTS Two hundred ten patients from 15 sites in Austria, Germany, and Israel were randomly allocated to placebo (107 patients) or ladostigil (103 patients). After 36 months, 21 of 103 patients on placebo and 14 of 99 patients receiving ladostigil progressed to Alzheimer disease (log-rank test p = 0.162). There were no significant effects on the NTB composite, DAD, or GDS score. Whole-brain and hippocampus volumes decreased more in the placebo than in the ladostigil group (whole brain, p = 0.025, Cohen d = 0.43; hippocampus, p = 0.043, d = 0.43). Serious adverse events were reported by 28 of 107 patients treated with placebo and 26 of 103 with ladostigil. CONCLUSION Ladostigil was safe and well tolerated but did not delay progression to dementia. Its association with reduced brain and hippocampus volume loss suggests a potential effect on atrophy. CLINICALTRIALSGOV IDENTIFIER NCT01429623. CLASSIFICATION OF EVIDENCE This study provides Class II evidence that for patients with MCI and medial temporal lobe atrophy, ladostigil did not significantly decrease the risk of the development of Alzheimer disease.
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Affiliation(s)
- Lon S Schneider
- From the Keck School of Medicine of the University of Southern California (L.S.S.), Los Angeles; Avraham Pharmaceuticals, Ltd (Y.G.), Yavne; Bar Ilan University (J.R.), Ramat Gan, Israel; University of California (R.G.T.), San Diego; Department of Neurology (R.S., S.R.), Medical University, Graz, Austria; and Hebrew University (M.W.), Jerusalem, Israel.
| | - Yona Geffen
- From the Keck School of Medicine of the University of Southern California (L.S.S.), Los Angeles; Avraham Pharmaceuticals, Ltd (Y.G.), Yavne; Bar Ilan University (J.R.), Ramat Gan, Israel; University of California (R.G.T.), San Diego; Department of Neurology (R.S., S.R.), Medical University, Graz, Austria; and Hebrew University (M.W.), Jerusalem, Israel
| | - Jonathan Rabinowitz
- From the Keck School of Medicine of the University of Southern California (L.S.S.), Los Angeles; Avraham Pharmaceuticals, Ltd (Y.G.), Yavne; Bar Ilan University (J.R.), Ramat Gan, Israel; University of California (R.G.T.), San Diego; Department of Neurology (R.S., S.R.), Medical University, Graz, Austria; and Hebrew University (M.W.), Jerusalem, Israel
| | - Ronald G Thomas
- From the Keck School of Medicine of the University of Southern California (L.S.S.), Los Angeles; Avraham Pharmaceuticals, Ltd (Y.G.), Yavne; Bar Ilan University (J.R.), Ramat Gan, Israel; University of California (R.G.T.), San Diego; Department of Neurology (R.S., S.R.), Medical University, Graz, Austria; and Hebrew University (M.W.), Jerusalem, Israel
| | - Reinhold Schmidt
- From the Keck School of Medicine of the University of Southern California (L.S.S.), Los Angeles; Avraham Pharmaceuticals, Ltd (Y.G.), Yavne; Bar Ilan University (J.R.), Ramat Gan, Israel; University of California (R.G.T.), San Diego; Department of Neurology (R.S., S.R.), Medical University, Graz, Austria; and Hebrew University (M.W.), Jerusalem, Israel
| | - Stefan Ropele
- From the Keck School of Medicine of the University of Southern California (L.S.S.), Los Angeles; Avraham Pharmaceuticals, Ltd (Y.G.), Yavne; Bar Ilan University (J.R.), Ramat Gan, Israel; University of California (R.G.T.), San Diego; Department of Neurology (R.S., S.R.), Medical University, Graz, Austria; and Hebrew University (M.W.), Jerusalem, Israel
| | - Marta Weinstock
- From the Keck School of Medicine of the University of Southern California (L.S.S.), Los Angeles; Avraham Pharmaceuticals, Ltd (Y.G.), Yavne; Bar Ilan University (J.R.), Ramat Gan, Israel; University of California (R.G.T.), San Diego; Department of Neurology (R.S., S.R.), Medical University, Graz, Austria; and Hebrew University (M.W.), Jerusalem, Israel
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Protective effect of potassium 2-(l-hydroxypentyl)-benzoate on hippocampal neurons, synapses and dystrophic axons in APP/PS1 mice. Psychopharmacology (Berl) 2019; 236:2761-2771. [PMID: 31165206 DOI: 10.1007/s00213-019-05251-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/17/2019] [Accepted: 04/18/2019] [Indexed: 10/26/2022]
Abstract
RATIONALE As the hub of memory and space, hippocampus is very sensitive to a wide variety of injuries and is one of the earliest brain structures to develop neurodegenerative changes in AD. Previous research has showed a protective effect of potassium 2-(l-hydroxypentyl)-benzoate (PHPB) on cognitive deficits in animal models of AD. However, it is unclear whether this protective effect is associated with hippocampal alterations. OBJECTIVES The present study was conducted to evaluate the protective effect of PHPB on hippocampal neurodegenerative changes in middle-aged APP/PS1 mice. METHODS Ten-month-old male APP/PS1 transgenic mice and age-matched wild-type mice were randomly divided into three groups. PHPB-treated APP/PS1 group received 30 mg/kg PHPB by oral gavage once daily for 12 weeks. Wild-type group and APP/PS1 group received the same volume of water alone. Twelve weeks later, mice (13-month-old) were tested for in vivo 1H-MRS examination and then sacrificed for subsequent biochemical and pathological examinations using transmission electron microscopy, Golgi staining, immunohistochemistry, and western blotting. RESULTS We found that PHPB treatment significantly improved the micromorphology of hippocampal neurons and subcellular organelles, ameliorated synapse loss and presynaptic axonal dystrophy, increased hippocampal dendritic spine density and dendritic complexity, enhanced the expression of hippocampal synapse-associated proteins, and improved hippocampal metabolism in middle-aged APP/PS1 mice. CONCLUSIONS Our study showed for the first time the protective effect of PHPB on hippocampal neurons, synapses, and dystrophic axons in APP/PS1 mice, which to some extent revealed the possible mechanism for its ability to improve cognition in animal models of AD.
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Goodkin O, Pemberton H, Vos SB, Prados F, Sudre CH, Moggridge J, Cardoso MJ, Ourselin S, Bisdas S, White M, Yousry T, Thornton J, Barkhof F. The quantitative neuroradiology initiative framework: application to dementia. Br J Radiol 2019; 92:20190365. [PMID: 31368776 DOI: 10.1259/bjr.20190365] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022] Open
Abstract
There are numerous challenges to identifying, developing and implementing quantitative techniques for use in clinical radiology, suggesting the need for a common translational pathway. We developed the quantitative neuroradiology initiative (QNI), as a model framework for the technical and clinical validation necessary to embed automated segmentation and other image quantification software into the clinical neuroradiology workflow. We hypothesize that quantification will support reporters with clinically relevant measures contextualized with normative data, increase the precision of longitudinal comparisons, and generate more consistent reporting across levels of radiologists' experience. The QNI framework comprises the following steps: (1) establishing an area of clinical need and identifying the appropriate proven imaging biomarker(s) for the disease in question; (2) developing a method for automated analysis of these biomarkers, by designing an algorithm and compiling reference data; (3) communicating the results via an intuitive and accessible quantitative report; (4) technically and clinically validating the proposed tool pre-use; (5) integrating the developed analysis pipeline into the clinical reporting workflow; and (6) performing in-use evaluation. We will use current radiology practice in dementia as an example, where radiologists have established visual rating scales to describe the degree and pattern of atrophy they detect. These can be helpful, but are somewhat subjective and coarse classifiers, suffering from floor and ceiling limitations. Meanwhile, several imaging biomarkers relevant to dementia diagnosis and management have been proposed in the literature; some clinically approved radiology software tools exist but in general, these have not undergone rigorous clinical validation in high volume or in tertiary dementia centres. The QNI framework aims to address this need. Quantitative image analysis is developing apace within the research domain. Translating quantitative techniques into the clinical setting presents significant challenges, which must be addressed to meet the increasing demand for accurate, timely and impactful clinical imaging services.
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Affiliation(s)
- Olivia Goodkin
- 1Centre for Medical Image Computing (CMIC), Department of Medical Physics and Bioengineering, University College London, London, United Kingdom.,2Neuroradiological Academic Unit, Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Hugh Pemberton
- 1Centre for Medical Image Computing (CMIC), Department of Medical Physics and Bioengineering, University College London, London, United Kingdom.,2Neuroradiological Academic Unit, Queen Square Institute of Neurology, University College London, London, United Kingdom.,3Dementia Research Centre, Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Sjoerd B Vos
- 1Centre for Medical Image Computing (CMIC), Department of Medical Physics and Bioengineering, University College London, London, United Kingdom.,2Neuroradiological Academic Unit, Queen Square Institute of Neurology, University College London, London, United Kingdom.,4Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, UCLH NHS Foundation Trust, London, United Kingdom.,5Department of Clinical and Experimental Epilepsy, University College London, London, United Kingdom
| | - Ferran Prados
- 1Centre for Medical Image Computing (CMIC), Department of Medical Physics and Bioengineering, University College London, London, United Kingdom.,6Queen Square MS Centre, Department of Neuroinflammation, Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom.,7Universitat Oberta de Catalunya, Barcelona, Spain
| | - Carole H Sudre
- 8School of Biomedical Engineering and Imaging Sciences, King's College London.,9Department of Medical Physics and Biomedical Engineering, University College London
| | - James Moggridge
- 2Neuroradiological Academic Unit, Queen Square Institute of Neurology, University College London, London, United Kingdom.,4Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, UCLH NHS Foundation Trust, London, United Kingdom
| | - M Jorge Cardoso
- 8School of Biomedical Engineering and Imaging Sciences, King's College London
| | - Sebastien Ourselin
- 8School of Biomedical Engineering and Imaging Sciences, King's College London
| | - Sotirios Bisdas
- 2Neuroradiological Academic Unit, Queen Square Institute of Neurology, University College London, London, United Kingdom.,4Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, UCLH NHS Foundation Trust, London, United Kingdom
| | - Mark White
- 10Digital Services, University College London Hospital, London United Kingdom
| | - Tarek Yousry
- 2Neuroradiological Academic Unit, Queen Square Institute of Neurology, University College London, London, United Kingdom.,4Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, UCLH NHS Foundation Trust, London, United Kingdom
| | - John Thornton
- 2Neuroradiological Academic Unit, Queen Square Institute of Neurology, University College London, London, United Kingdom.,4Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, UCLH NHS Foundation Trust, London, United Kingdom
| | - Frederik Barkhof
- 1Centre for Medical Image Computing (CMIC), Department of Medical Physics and Bioengineering, University College London, London, United Kingdom.,2Neuroradiological Academic Unit, Queen Square Institute of Neurology, University College London, London, United Kingdom.,4Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, UCLH NHS Foundation Trust, London, United Kingdom.,6Queen Square MS Centre, Department of Neuroinflammation, Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom.,11Department of Radiology and Nuclear Medicine, VU University Medical Centre, Amsterdam, The Netherlands
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van Maurik IS, Visser LN, Pel-Littel RE, van Buchem MM, Zwan MD, Kunneman M, Pelkmans W, Bouwman FH, Minkman M, Schoonenboom N, Scheltens P, Smets EM, van der Flier WM. Development and Usability of ADappt: Web-Based Tool to Support Clinicians, Patients, and Caregivers in the Diagnosis of Mild Cognitive Impairment and Alzheimer Disease. JMIR Form Res 2019; 3:e13417. [PMID: 31287061 PMCID: PMC6643768 DOI: 10.2196/13417] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2019] [Revised: 04/30/2019] [Accepted: 04/30/2019] [Indexed: 12/31/2022] Open
Abstract
Background As a result of advances in diagnostic testing in the field of Alzheimer disease (AD), patients are diagnosed in earlier stages of the disease, for example, in the stage of mild cognitive impairment (MCI). This poses novel challenges for a clinician during the diagnostic workup with regard to diagnostic testing itself, namely, which tests are to be performed, but also on how to engage patients in this decision and how to communicate test results. As a result, tools to support decision making and improve risk communication could be valuable for clinicians and patients. Objective The aim of this study was to present the design, development, and testing of a Web-based tool for clinicians in a memory clinic setting and to ascertain whether this tool can (1) facilitate the interpretation of biomarker results in individual patients with MCI regarding their risk of progression to dementia, (2) support clinicians in communicating biomarker test results and risks to MCI patients and their caregivers, and (3) support clinicians in a process of shared decision making regarding the diagnostic workup of AD. Methods A multiphase mixed-methods approach was used. Phase 1 consisted of a qualitative needs assessment among professionals, patients, and caregivers; phase 2, consisted of an iterative process of development and the design of the tool (ADappt); and phase 3 consisted of a quantitative and qualitative assessment of usability and acceptability of ADappt. Across these phases, co-creation was realized via a user-centered qualitative approach with clinicians, patients, and caregivers. Results In phase 1, clinicians indicated the need for risk calculation tools and visual aids to communicate test results to patients. Patients and caregivers expressed their needs for more specific information on their risk for developing AD and related consequences. In phase 2, we developed the content and graphical design of ADappt encompassing 3 modules: a risk calculation tool, a risk communication tool including a summary sheet for patients and caregivers, and a conversation starter to support shared decision making regarding the diagnostic workup. In phase 3, ADappt was considered to be clear and user-friendly. Conclusions Clinicians in a memory clinic setting can use ADappt, a Web-based tool, developed using multiphase design and co-creation, for support that includes an individually tailored interpretation of biomarker test results, communication of test results and risks to patients and their caregivers, and shared decision making on diagnostic testing.
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Affiliation(s)
- Ingrid S van Maurik
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, Netherlands.,Department of Epidemiology and Biostatistics, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, Netherlands
| | - Leonie Nc Visser
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, Netherlands.,Department of Medical Psychology, Amsterdam Public Health Research Insitute, University of Amsterdam, Amsterdam UMC, Amsterdam, Netherlands
| | | | - Marieke M van Buchem
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, Netherlands
| | - Marissa D Zwan
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, Netherlands
| | - Marleen Kunneman
- Department of Medical Psychology, Amsterdam Public Health Research Insitute, University of Amsterdam, Amsterdam UMC, Amsterdam, Netherlands.,Medical Decision Making, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, Netherlands
| | - Wiesje Pelkmans
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, Netherlands
| | - Femke H Bouwman
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, Netherlands
| | - Mirella Minkman
- Vilans Center of Expertise for Long Term Care, Utrecht, Netherlands.,Tilburg University, TIAS School for Business and Society, Tilburg, Netherlands
| | | | - Philip Scheltens
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, Netherlands
| | - Ellen Ma Smets
- Department of Medical Psychology, Amsterdam Public Health Research Insitute, University of Amsterdam, Amsterdam UMC, Amsterdam, Netherlands
| | - Wiesje M van der Flier
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, Netherlands.,Department of Epidemiology and Biostatistics, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, Netherlands
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Vernooij MW, Pizzini FB, Schmidt R, Smits M, Yousry TA, Bargallo N, Frisoni GB, Haller S, Barkhof F. Dementia imaging in clinical practice: a European-wide survey of 193 centres and conclusions by the ESNR working group. Neuroradiology 2019; 61:633-642. [PMID: 30852630 PMCID: PMC6511357 DOI: 10.1007/s00234-019-02188-y] [Citation(s) in RCA: 41] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2019] [Accepted: 02/12/2019] [Indexed: 12/11/2022]
Abstract
PURPOSE Through a European-wide survey, we assessed the current clinical practice of imaging in the primary evaluation of dementia, with respect to standardised imaging, evaluation and reporting. METHODS An online questionnaire was emailed to all European Society of Neuroradiology (ESNR) members (n = 1662) and non-members who had expressed their interest in ESNR activities in the past (n = 6400). The questionnaire featured 42 individual items, divided into multiple choice, single best choice and free text answers. Information was gathered on the context of the practices, available and preferred imaging modalities, applied imaging protocols and standards for interpretation, reporting and communication. RESULTS A total of 193 unique (non-duplicate) entries from the European academic and non-academic institutions were received from a total of 28 countries. Of these, 75% were neuroradiologists, 12% general radiologists and 11% (neuro) radiologists in training. Of responding centres, 38% performed more than five scans/week for suspected dementia. MRI was primarily used in 72% of centres. Over 90% of centres acquired a combination of T2w, FLAIR, T1w, DWI and T2*w sequences. Visual rating scales were used in 75% of centres, most often the Fazekas and medial temporal atrophy scale; 32% of respondents lacked full confidence in their use. Only 23% of centres performed volumetric analysis. A minority of centres (28%) used structured reports. CONCLUSIONS Current practice in dementia imaging is fairly homogeneous across Europe, in terms of image acquisition and image interpretation. Hurdles identified include training on the use of visual rating scales, implementation of volumetric assessment and structured reporting.
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Affiliation(s)
- M W Vernooij
- Department of Radiology & Nuclear Medicine, Erasmus MC University Medical Center, Rotterdam, The Netherlands.
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands.
| | - F B Pizzini
- Neuroradiology, Department of Diagnostics and Pathology, Verona University Hospital, Verona, Italy
| | - R Schmidt
- Department of Neurology, Clinical Division of Neurogeriatrics, Medical University Graz, Graz, Austria
| | - M Smits
- Department of Radiology & Nuclear Medicine, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - T A Yousry
- Lysholm Department of Neuroradiology, UCL Institute of Neurology, London, UK
| | - N Bargallo
- Magnetic Resonance Image Core Facility, IDIBAPS and Center of Diagnostic Image (CDIC), Hospital Clinic, Barcelona, Spain
| | - G B Frisoni
- University Hospitals and University of Geneva, Geneva, Switzerland
| | - S Haller
- CIRD - Centre d'Imagerie Rive Droite|, Geneva, Switzerland
- Department of Surgical Sciences, Radiology, Uppsala University, Uppsala, Sweden
- Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - F Barkhof
- Lysholm Department of Neuroradiology, UCL Institute of Neurology, London, UK
- Department of Radiology and Nuclear Medicine, VU University Medical Centre, Amsterdam UMC, Amsterdam, The Netherlands
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Ryan B, Williams JM, Curtis MA. Plasma MicroRNAs Are Altered Early and Consistently in a Mouse Model of Tauopathy. Neuroscience 2019; 411:164-176. [PMID: 31152932 DOI: 10.1016/j.neuroscience.2019.05.036] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2019] [Revised: 05/16/2019] [Accepted: 05/20/2019] [Indexed: 01/06/2023]
Abstract
Pathological accumulation of tau protein in brain cells is the hallmark of a group of neurodegenerative diseases called tauopathies. Accumulation of tau protein begins years before the onset of symptoms, which include deficits in cognition, behavior and movement. The pre-symptomatic phase of tauopathy may be the best time to deliver disease-modifying treatments, but this is only possible if prognostic, pre-symptomatic biomarkers are identified. Here we describe the profiling of blood plasma microRNAs in a mouse model of tauopathy, in order to identify biomarkers of pre-symptomatic tauopathy. Circulating RNAs were isolated from blood plasma of 16-week-old and 53-week-old hTau mice and age-matched wild type controls (n = 28). Global microRNA profiling was performed using small RNA sequencing (Illumina) and selected microRNAs were validated using individual TaqMan RT-qPCR. The area under the receiver operating characteristic curve (AUC) was used to evaluate discriminative accuracy. We identified three microRNAs (miR-150-5p, miR-155-5p, miR-375-3p) that were down-regulated in 16-week-old hTau mice, which do not yet exhibit a behavioral phenotype and therefore represent pre-symptomatic tauopathy. The discriminative accuracy was AUC 0.98, 0.95 and 1, respectively. Down-regulation of these microRNAs persisted at 53 weeks of age, when hTau mice exhibit cognitive deficits and advanced neuropathology. Bioinformatic analysis showed that these three microRNAs converge on pathways associated with neuronal signaling and phosphorylation of tau. Thus, these circulating microRNAs appear to reflect neuropathological change and are promising candidates in the development of biomarkers of pre-symptomatic tauopathy.
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Affiliation(s)
- Brigid Ryan
- Department of Anatomy and Medical Imaging, University of Auckland, Auckland, New Zealand; Brain Research, New Zealand - Rangahau Roro Aotearoa.
| | - Joanna M Williams
- Brain Research, New Zealand - Rangahau Roro Aotearoa; Department of Anatomy, University of Otago, Dunedin, New Zealand
| | - Maurice A Curtis
- Department of Anatomy and Medical Imaging, University of Auckland, Auckland, New Zealand; Brain Research, New Zealand - Rangahau Roro Aotearoa
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Koikkalainen JR, Rhodius-Meester HFM, Frederiksen KS, Bruun M, Hasselbalch SG, Baroni M, Mecocci P, Vanninen R, Remes A, Soininen H, van Gils M, van der Flier WM, Scheltens P, Barkhof F, Erkinjuntti T, Lötjönen JMP. Automatically computed rating scales from MRI for patients with cognitive disorders. Eur Radiol 2019; 29:4937-4947. [DOI: 10.1007/s00330-019-06067-1] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2018] [Revised: 01/09/2019] [Accepted: 02/04/2019] [Indexed: 01/09/2023]
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Johnson EL, Krauss GL, Lee AK, Schneider ALC, Kucharska-Newton AM, Huang J, Jack CR, Gottesman RF. Association between white matter hyperintensities, cortical volumes, and late-onset epilepsy. Neurology 2019; 92:e988-e995. [PMID: 30804067 DOI: 10.1212/wnl.0000000000007010] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2018] [Accepted: 10/25/2018] [Indexed: 12/12/2022] Open
Abstract
OBJECTIVE To identify the association between brain vascular changes and cortical volumes on MRI and late-onset epilepsy. METHODS In 1993-1995, 1,920 participants (median age 62.7, 59.9% female) in the community-based Atherosclerosis Risk in Communities (ARIC) Study underwent MRI, and white matter hyperintensities were measured. In addition, in 2011-2013, 1,964 ARIC participants (median age 72.4, 61.1% female) underwent MRI, and cortical volumes and white matter hyperintensities were measured. We identified cases of late-onset epilepsy (starting at age 60 or later) from ARIC hospitalization records and Medicare claims data. Using the 1993-1995 MRI, we evaluated the association between white matter hyperintensities and subsequent epilepsy using survival analysis. We used the 2011-2013 MRI to conduct cross-sectional logistic regression to examine the association of cortical volumes and white matter hyperintensities with late-onset epilepsy. All models were adjusted for demographics, hypertension, diabetes, smoking, and APOE ε4 allele status. RESULTS Ninety-seven ARIC participants developed epilepsy after having an MRI in 1993-1995 (incidence 3.34 per 1,000 person-years). The degree of white matter hyperintensities measured at ages 49-72 years was associated with the risk of late-onset epilepsy (hazard ratio 1.27 per age-adjusted SD, 95% confidence interval [CI] 1.06-1.54). Lower cortical volume scores were associated cross-sectionally with higher odds of late-onset epilepsy (odds ratio 1.87, 95% CI 1.16-3.02) per age-adjusted SD. CONCLUSIONS This study demonstrates associations between earlier-life white matter hyperintensities on MRI and later-life incident epilepsy, and between cortical volumes measured later in life and late-onset epilepsy. These findings may help illuminate the causes of late-onset epilepsy.
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Affiliation(s)
- Emily L Johnson
- From the Department of Neurology (E.L.J., G.L.K., A.L.C.S., R.F.G.), Johns Hopkins University School of Medicine; Department of Epidemiology (A.K.L., R.F.G.), Johns Hopkins School of Public Health, Baltimore, MD; Department of Epidemiology (A.M.K.-N.), University of North Carolina at Chapel Hill; Department of Neurology (J.H.), University of Mississippi Medical Center, Jackson; and Department of Radiology (C.R.J.), Mayo Clinic, Rochester, MN.
| | - Gregory L Krauss
- From the Department of Neurology (E.L.J., G.L.K., A.L.C.S., R.F.G.), Johns Hopkins University School of Medicine; Department of Epidemiology (A.K.L., R.F.G.), Johns Hopkins School of Public Health, Baltimore, MD; Department of Epidemiology (A.M.K.-N.), University of North Carolina at Chapel Hill; Department of Neurology (J.H.), University of Mississippi Medical Center, Jackson; and Department of Radiology (C.R.J.), Mayo Clinic, Rochester, MN
| | - Alexandra K Lee
- From the Department of Neurology (E.L.J., G.L.K., A.L.C.S., R.F.G.), Johns Hopkins University School of Medicine; Department of Epidemiology (A.K.L., R.F.G.), Johns Hopkins School of Public Health, Baltimore, MD; Department of Epidemiology (A.M.K.-N.), University of North Carolina at Chapel Hill; Department of Neurology (J.H.), University of Mississippi Medical Center, Jackson; and Department of Radiology (C.R.J.), Mayo Clinic, Rochester, MN
| | - Andrea L C Schneider
- From the Department of Neurology (E.L.J., G.L.K., A.L.C.S., R.F.G.), Johns Hopkins University School of Medicine; Department of Epidemiology (A.K.L., R.F.G.), Johns Hopkins School of Public Health, Baltimore, MD; Department of Epidemiology (A.M.K.-N.), University of North Carolina at Chapel Hill; Department of Neurology (J.H.), University of Mississippi Medical Center, Jackson; and Department of Radiology (C.R.J.), Mayo Clinic, Rochester, MN
| | - Anna M Kucharska-Newton
- From the Department of Neurology (E.L.J., G.L.K., A.L.C.S., R.F.G.), Johns Hopkins University School of Medicine; Department of Epidemiology (A.K.L., R.F.G.), Johns Hopkins School of Public Health, Baltimore, MD; Department of Epidemiology (A.M.K.-N.), University of North Carolina at Chapel Hill; Department of Neurology (J.H.), University of Mississippi Medical Center, Jackson; and Department of Radiology (C.R.J.), Mayo Clinic, Rochester, MN
| | - Juebin Huang
- From the Department of Neurology (E.L.J., G.L.K., A.L.C.S., R.F.G.), Johns Hopkins University School of Medicine; Department of Epidemiology (A.K.L., R.F.G.), Johns Hopkins School of Public Health, Baltimore, MD; Department of Epidemiology (A.M.K.-N.), University of North Carolina at Chapel Hill; Department of Neurology (J.H.), University of Mississippi Medical Center, Jackson; and Department of Radiology (C.R.J.), Mayo Clinic, Rochester, MN
| | - Clifford R Jack
- From the Department of Neurology (E.L.J., G.L.K., A.L.C.S., R.F.G.), Johns Hopkins University School of Medicine; Department of Epidemiology (A.K.L., R.F.G.), Johns Hopkins School of Public Health, Baltimore, MD; Department of Epidemiology (A.M.K.-N.), University of North Carolina at Chapel Hill; Department of Neurology (J.H.), University of Mississippi Medical Center, Jackson; and Department of Radiology (C.R.J.), Mayo Clinic, Rochester, MN
| | - Rebecca F Gottesman
- From the Department of Neurology (E.L.J., G.L.K., A.L.C.S., R.F.G.), Johns Hopkins University School of Medicine; Department of Epidemiology (A.K.L., R.F.G.), Johns Hopkins School of Public Health, Baltimore, MD; Department of Epidemiology (A.M.K.-N.), University of North Carolina at Chapel Hill; Department of Neurology (J.H.), University of Mississippi Medical Center, Jackson; and Department of Radiology (C.R.J.), Mayo Clinic, Rochester, MN
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Flak MM, Hol HR, Hernes SS, Chang L, Ernst T, Engvig A, Bjuland KJ, Madsen BO, Lindland EMS, Knapskog AB, Ulstein ID, Lona TEE, Skranes J, Løhaugen GCC. Cognitive Profiles and Atrophy Ratings on MRI in Senior Patients With Mild Cognitive Impairment. Front Aging Neurosci 2018; 10:384. [PMID: 30519185 PMCID: PMC6258794 DOI: 10.3389/fnagi.2018.00384] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2018] [Accepted: 11/01/2018] [Indexed: 12/12/2022] Open
Abstract
In this cross-sectional study, we sought to describe cognitive and neuroimaging profiles of Memory clinic patients with Mild Cognitive Impairment (MCI). 51 MCI patients and 51 controls, matched on age, sex, and socio-economic status (SES), were assessed with an extensive neuropsychological test battery that included a measure of intelligence (General Ability Index, "GAI," from WAIS-IV), and structural magnetic resonance imaging (MRI). MCI subtypes were determined after inclusion, and z-scores normalized to our control group were generated for each cognitive domain in each MCI participant. MR-images were scored by visual rating scales. MCI patients performed significantly worse than controls on 23 of 31 cognitive measures (Bonferroni corrected p = 0.001), and on 8 of 31 measures after covarying for intelligence (GAI). Compared to nonamnestic MCI patients, amnestic MCI patients had lower test results in 13 of 31 measures, and 5 of 31 measures after co-varying for GAI. Compared to controls, the MCI patients had greater atrophy on Schelten's Medial temporal lobe atrophy score (MTA), especially in those with amnestic MCI. The only structure-function correlation that remained significant after correction for multiple comparisons was the MTA-long delay recall domain. Intelligence operationalized as GAI appears to be an important moderator of the neuropsychological outcomes. Atrophy of the medial temporal lobe, based on MTA scores, may be a sensitive biomarker for the functional episodic memory deficits associated with MCI.
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Affiliation(s)
- Marianne M. Flak
- Department of Clinical and Molecular Medicine, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Pediatrics, Sørlandet Hospital HF, Arendal, Norway
| | - Haakon R. Hol
- Department of Radiology, Sørlandet Hospital HF, Arendal, Norway
- Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Susanne S. Hernes
- Department of Clinical Science, University of Bergen, Bergen, Norway
- The Memory Clinic Geriatric Unit, Department of Medicine, Sørlandet Hospital, Arendal, Norway
| | - Linda Chang
- Department of Diagnostic Radiology and Nuclear Medicine, and Department of Neurology, University of Maryland School of Medicine, Baltimore, MD, United States
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- Department of Medicine, John A. Burns School of Medicine, University of Hawaii at Manoa, Honolulu, HI, United States
| | - Thomas Ernst
- Department of Diagnostic Radiology and Nuclear Medicine, and Department of Neurology, University of Maryland School of Medicine, Baltimore, MD, United States
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- Department of Medicine, John A. Burns School of Medicine, University of Hawaii at Manoa, Honolulu, HI, United States
| | - Andreas Engvig
- Department of Medicine, Diakonhjemmet Hospital, Oslo, Norway
| | | | - Bengt-Ove Madsen
- The Memory Clinic Geriatric Unit, Department of Medicine, Sørlandet Hospital, Arendal, Norway
| | - Elisabeth M. S. Lindland
- Department of Radiology, Sørlandet Hospital HF, Arendal, Norway
- Department of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Anne-Brita Knapskog
- Department of Geriatric Medicine, The Memory Clinic, Oslo University Hospital, Oslo, Norway
| | - Ingun D. Ulstein
- Department of Geriatric Medicine, The Memory Clinic, Oslo University Hospital, Oslo, Norway
| | - Trine E. E. Lona
- Department of Psychiatry, Age Psychiatry, The Hospital of Telemark, Skien, Norway
| | - Jon Skranes
- Department of Clinical and Molecular Medicine, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Pediatrics, Sørlandet Hospital HF, Arendal, Norway
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50
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Hypermetabolism in the hippocampal formation of cognitively impaired patients indicates detrimental maladaptation. Neurobiol Aging 2018; 65:41-50. [DOI: 10.1016/j.neurobiolaging.2018.01.002] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2017] [Revised: 12/27/2017] [Accepted: 01/07/2018] [Indexed: 11/22/2022]
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