| 21. |
- Damangir, Soheil, et al.
(författare)
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Multispectral MRI segmentation of age related white matter changes using a cascade of support vector machines
- 2012
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Ingår i: Journal of the Neurological Sciences. - : Elsevier BV. - 0022-510X .- 1878-5883. ; 322:1-2, s. 211-216
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Tidskriftsartikel (refereegranskat)abstract
- White matter changes (WMC) are the focus of intensive research and have been linked to cognitive impairment and depression in the elderly. Cumbersome manual outlining procedures make research on WMC labor intensive and prone to subjective bias. We present a fast, fully automated method for WMC segmentation using a cascade of reduced support vector machines (SVMs) with active learning. Data of 102 subjects was used in this study. Two MRI sequences (T1-weighted and FLAIR) and masks of manually outlined WMC from each subject were used for the image analysis. The segmentation framework comprises pre-processing, classification (training and core segmentation) and post-processing. After pre-processing, the model was trained on two subjects and tested on the remaining 100 subjects. The effectiveness and robustness of the classification was assessed using the receiver operating curve technique. The cascade of SVMs segmentation framework outputted accurate results with high sensitivity (90%) and specificity (99.5%) values, with the manually outlined WMC as reference. An algorithm for the segmentation of WMC is proposed. This is a completely competitive and fast automatic segmentation framework, capable of using different input sequences, without changes or restrictions of the image analysis algorithm.
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| 22. |
- Dartora, Caroline, et al.
(författare)
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A deep learning model for brain age prediction using minimally preprocessed T1w images as input
- 2023
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Ingår i: Frontiers in Aging Neuroscience. - : Frontiers Media SA. - 1663-4365. ; 15
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Tidskriftsartikel (refereegranskat)abstract
- Introduction: In the last few years, several models trying to calculate the biological brain age have been proposed based on structural magnetic resonance imaging scans (T1-weighted MRIs, T1w) using multivariate methods and machine learning. We developed and validated a convolutional neural network (CNN)-based biological brain age prediction model that uses one T1w MRI preprocessing step when applying the model to external datasets to simplify implementation and increase accessibility in research settings. Our model only requires rigid image registration to the MNI space, which is an advantage compared to previous methods that require more preprocessing steps, such as feature extraction. Methods: We used a multicohort dataset of cognitively healthy individuals (age range = 32.0–95.7 years) comprising 17,296 MRIs for training and evaluation. We compared our model using hold-out (CNN1) and cross-validation (CNN2–4) approaches. To verify generalisability, we used two external datasets with different populations and MRI scan characteristics to evaluate the model. To demonstrate its usability, we included the external dataset’s images in the cross-validation training (CNN3). To ensure that our model used only the brain signal on the image, we also predicted brain age using skull-stripped images (CNN4). Results: The trained models achieved a mean absolute error of 2.99, 2.67, 2.67, and 3.08 years for CNN1–4, respectively. The model’s performance in the external dataset was in the typical range of mean absolute error (MAE) found in the literature for testing sets. Adding the external dataset to the training set (CNN3), overall, MAE is unaffected, but individual cohort MAE improves (5.63–2.25 years). Salience maps of predictions reveal that periventricular, temporal, and insular regions are the most important for age prediction. Discussion: We provide indicators for using biological (predicted) brain age as a metric for age correction in neuroimaging studies as an alternative to the traditional chronological age. In conclusion, using different approaches, our CNN-based model showed good performance using one T1w brain MRI preprocessing step. The proposed CNN model is made publicly available for the research community to be easily implemented and used to study ageing and age-related disorders.
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| 23. |
- Dittrich, Anna, 1972, et al.
(författare)
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Association of Chronic Kidney Disease With Plasma NfL and Other Biomarkers of Neurodegeneration: The H70 Birth Cohort Study in Gothenburg.
- 2023
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Ingår i: Neurology. - 1526-632X. ; 101:3
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Tidskriftsartikel (refereegranskat)abstract
- Studies associate chronic kidney disease (CKD) with neurodegeneration. This study investigated the relationship between kidney function, blood, CSF, and structural brain MRI markers of neurodegeneration in a sample including individuals with and without CKD.Participants from the Gothenburg H70 Birth Cohort Study, with data on plasma neurofilament light (P-NfL), estimated glomerular filtration rate (eGFR), and structural brain MRI were included. Participants were invited to also have the CSF collected. The primary endpoint of this study was to determine any association between CKD and P-NfL. Secondary endpoints included cross-sectional associations between CKD, eGFR, and CSF-derived and MRI-derived markers of neurodegeneration and Alzheimer disease (AD) pathology (MRI: cortical thickness, hippocampal volume, lateral ventricle volume, and white matter lesion volume; CSF: β-amyloid (Aβ) 42, Aβ42/40, Aβ42/p-tau, t-tau, p-tau, and NfL). Participants with P-NfL and eGFR at baseline were re-examined on eGFR, 5.5 (5.3-6.1) years (median; IQR) after the first visit, and the predictive value of P-NfL levels on incident CKD was estimated longitudinally, using a Cox proportional hazards model.We included 744 participants, 668 without CKD (age 71 [70-71] years, 50% males) and 76 with CKD (age 71 [70-71] years, 39% males). Biomarkers from the CSF were analyzed in 313 participants. A total of 558 individuals returned for a re-examination of eGFR (75% response rate, age 76 [76; 77] years, 48% males, 76 new cases of CKD). Participants with CKD had higher P-NfL levels than those with normal kidney function (median; 18.8 vs 14.1 pg/mL, p < 0.001), while MRI and CSF markers were similar between the groups. P-NfL was independently associated with CKD after adjustment for confounding variables, including hypertension and diabetes (OR; 3.231, p < 0.001), in a logistic regression model. eGFR and CSF Aβ 42/40: R = 0.23, p = 0.004 correlated in participants with Aβ42 pathology. P-NfL levels in the highest quartile were associated with incident CKD at follow-up (HR; 2.39 [1.21: 4.72]).In a community-based cohort of 70-year olds, P-NfL was associated with both prevalent and incident CKD, while CSF and/or imaging measures did not differ by CKD status. Participants with CKD and dementia presented similar levels of P-NfL.
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| 24. |
- Dittrich, Anna, 1972, et al.
(författare)
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Proportion of Community-Dwelling Individuals Older Than 70 Years Eligible for Lecanemab Initiation: The Gothenburg H70 Birth Cohort Study.
- 2024
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Ingår i: Neurology. - 0028-3878 .- 1526-632X. ; 102:9
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Tidskriftsartikel (refereegranskat)abstract
- To determine the prevalence of individuals with Alzheimer disease (AD) eligible for treatment with the recently FDA-approved lecanemab based on data from a population-based sample of 70-year-olds and extrapolate an estimation of individuals eligible in Europe and the United States.Participants from the Gothenburg H70 Birth Cohort Study with clinical data, CSF-amyloid beta 42, and brain MRI analysis were evaluated for eligibility to receive lecanemab treatment according to FDA-approved recommendations, noting factors requiring special consideration. Results were used to extrapolate the number of eligible individuals in Europe and the United States using public demographic data.Thirty (10.3%) of 290 participants met the indication for treatment of whom 18 (6.2%) were eligible and did not present factors requiring special consideration. Our estimate that 6.2% of all 70-year-olds in the full cohort are eligible for treatment extrapolates to an approximation that around 5.9 million Europeans and 2.2 million US residents could be eligible.Information on proportion of individuals eligible for AD treatment with lecanemab in the general public is limited. We provide information on 70-year-olds in Sweden and extrapolate these data to Europe and the United States. This study opens for larger studies on this proportion and implementation of lecanemab treatment.
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| 25. |
- Ekman, Urban, et al.
(författare)
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Evaluation of a Novel Psychological Intervention Tailored for Patients With Early Cognitive Impairment (PIPCI) : Study Protocol of a Randomized Controlled Trial
- 2020
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Ingår i: Frontiers in Psychology. - : Frontiers Media SA. - 1664-1078. ; 11
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Tidskriftsartikel (refereegranskat)abstract
- Background: Individuals with early phase cognitive impairment are frequently affected by existential distress, social avoidance and associated health issues (including symptoms of stress, anxiety, and depression). The demand for efficient psychological support is crucial from both an individual and a societal perspective. We have developed a novel psychological intervention (Psychological Intervention tailored for Patients with Cognitive Impairment, PIPCI) manual for providing a non-medical path to enhanced psychological health in the cognitively impaired population. The current article provides specific information on the randomized controlled trial (RCT)-design and methods. The main hypothesis is that participants receiving PIPCI will increase their psychological flexibility (the ability to notice and accept interfering thoughts, emotions, and bodily sensations without acting on them, when this serves action in line with personal values) compared to participants in the active control (cognitive training) group and the waiting list control group. The secondary hypotheses are that participants receiving PIPCI will improve psychological health (stress measures, quality of life, depression, and general health) compared to participants in the active control group and the waiting list control group.Materials and Methods: This three-arm RCT will recruit participants from the cognitive centers at Karolinska University Hospital in Stockholm and randomize approximately 120 individuals in the early phase of cognitive impairment to either an experimental group (psychological intervention once a week for 10 weeks), an active control group (cognitive training once a week for 10 weeks) or a waiting list control group. Intervention outcome will be evaluated with self-report questionnaires on physical and psychological aspects of health, cognitive assessment, biological markers (obtained from blood and saliva) and health care costs. Assessments will be performed at pre- (1 week before the interventions) and post-intervention (1 week after the interventions), as well as at a 6-month follow-up.Discussion: The development of a potentially feasible and effective psychological intervention tailored for early phase cognitive impairment (PIPCI) has the potential to advance the non-pharmacological intervention field. This is especially important given the extensive burden for many affected individuals and their families and the current lack of effective treatments. If the psychological intervention discussed here shows feasibility and efficacy, there is potential for far-reaching healthcare implications for patients with early cognitive impairment at risk of developing dementia.
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| 26. |
- Ekman, Urban, et al.
(författare)
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The MemClin project : a prospective multi memory clinics study targeting early stages of cognitive impairment
- 2020
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Ingår i: BMC Geriatrics. - : BMC. - 1471-2318. ; 20
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Tidskriftsartikel (refereegranskat)abstract
- Background: There remains a lack of large-scale clinical studies of cognitive impairment that aim to increase diagnostic and prognostic accuracy as well as validate previous research findings. The MemClin project will amass large quantities of cross-disciplinary data allowing for the construction of robust models to improve diagnostic accuracy, expand our knowledge on differential diagnostics, strengthen longitudinal prognosis, and harmonise examination protocols across centres. The current article describes the Memory Clinic (MemClin) project's study-design, materials and methods, and patient characteristics. In addition, we present preliminary descriptive data from the ongoing data collection.Methods: Nine out of ten memory clinics in the greater Stockholm area, which largely use the same examination methods, are included. The data collection of patients with different stages of cognitive impairment and dementia is coordinated centrally allowing for efficient and secure large-scale database construction. The MemClin project rest directly on the memory clinics examinations with cognitive measures, health parameters, and biomarkers.Results: Currently, the MemClin project has informed consent from 1543 patients. Herein, we present preliminary data from 835 patients with confirmed cognitive diagnosis and neuropsychological test data available. Of those, 239 had dementia, 487 mild cognitive impairment (MCI), and 104 subjective cognitive impairment (SCI). In addition, we present descriptive data on visual ratings of brain atrophy and cerebrospinal fluid markers.Conclusions: Based on our current progress and preliminary data, the MemClin project has a high potential to provide a large-scale database of 1200-1500 new patients annually. This coordinated data collection will allow for the construction of improved diagnostic and prognostic models for neurodegenerative disorders and other cognitive conditions in their naturalistic setting.
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| 27. |
- Ferreira, Daniel, et al.
(författare)
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Brain changes in Alzheimer's disease patients with implanted encapsulated cells releasing nerve growth factor
- 2015
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Ingår i: Journal of Alzheimer's Disease. - 1387-2877 .- 1875-8908. ; 43, s. 1059-1072
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Tidskriftsartikel (refereegranskat)abstract
- © 2015-IOS Press and the authors. New therapies with disease-modifying effects are urgently needed for treating Alzheimer's disease (AD). Nerve growth factor (NGF) protein has demonstrated regenerative and neuroprotective effects on basal forebrain cholinergic neurons in animal studies. In addition, AD patients treated with NGF have previously shown improved cognition, EEG activity, nicotinic binding, and glucose metabolism. However, no study to date has analyzed brain atrophy in patients treated with NGF producing cells. In this study we present MRI results of the first clinical trial in patients with AD using encapsulated NGF biodelivery to the basal forebrain. Six AD patients received the treatment during twelve months. Patients were grouped as responders and non-responders according to their twelve-months change in MMSE. Normative values were created from 131 AD patients from ADNI, selecting 36 age-and MMSE-matched patients for interpreting the longitudinal changes in MMSE and brain atrophy. Results at baseline indicated that responders showed better clinical status and less pathological levels of cerebrospinal fluid (CSF) Aβ1-42. However, they showed more brain atrophy, and neuronal degeneration as evidenced by higher CSF levels of T-tau and neurofilaments. At follow-up, responders showed less brain shrinkage and better progression in the clinical variables and CSF biomarkers. Noteworthy, two responders showed less brain shrinkage than the normative ADNI group. These results together with previous evidence supports the idea that encapsulated biodelivery of NGF might have the potential to become a new treatment strategy for AD with both symptomatic and disease-modifying effects.
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| 28. |
- Ferreira, Daniel, et al.
(författare)
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The interactive effect of demographic and clinical factors on hippocampal volume : A multicohort study on 1958 cognitively normal individuals
- 2017
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Ingår i: Hippocampus. - : Wiley. - 1050-9631 .- 1098-1063. ; 27:6, s. 653-667
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Tidskriftsartikel (refereegranskat)abstract
- Alzheimer's disease is characterized by hippocampal atrophy. Other factors also influence the hippocampal volume, but their interactive effect has not been investigated before in cognitively healthy individuals. The aim of this study is to evaluate the interactive effect of key demographic and clinical factors on hippocampal volume, in contrast to previous studies frequently investigating these factors in a separate manner. Also, to investigate how comparable the control groups from ADNI, AIBL, and AddNeuroMed are with five population-based cohorts. In this study, 1958 participants were included (100 AddNeuroMed, 226 ADNI, 155 AIBL, 59 BRC, 295 GENIC, 279 BioFiNDER, 398 PIVUS, and 446 SNAC-K). ANOVA and random forest were used for testing between-cohort differences in demographic-clinical variables. Multiple regression was used to study the influence of demographic-clinical variables on hippocampal volume. ANCOVA was used to analyze whether between-cohort differences in demographic-clinical variables explained between-cohort differences in hippocampal volume. Age and global brain atrophy were the most important variables in explaining variability in hippocampal volume. These variables were not only important themselves but also in interaction with gender, education, MMSE, and total intracranial volume. AddNeuroMed, ADNI, and AIBL differed from the population-based cohorts in several demographic-clinical variables that had a significant effect on hippocampal volume. Variability in hippocampal volume in individuals with normal cognition is high. Differences that previously tended to be related to disease mechanisms could also be partly explained by demographic and clinical factors independent from the disease. Furthermore, cognitively normal individuals especially from ADNI and AIBL are not representative of the general population. These findings may have important implications for future research and clinical trials, translating imaging biomarkers to the general population, and validating current diagnostic criteria for Alzheimer's disease and predementia stages.
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| 29. |
- Ferreira, Daniel, et al.
(författare)
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β-Amyloid and tau biomarkers and clinical phenotype in dementia with Lewy bodies
- 2020
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Ingår i: Neurology. - 1526-632X. ; 95:24, s. 3257-3268
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Tidskriftsartikel (refereegranskat)abstract
- OBJECTIVE: In a multicenter cohort of probable dementia with Lewy bodies (DLB), we tested the hypothesis that β-amyloid and tau biomarker positivity increases with age, which is modified by APOE genotype and sex, and that there are isolated and synergistic associations with the clinical phenotype. METHODS: We included 417 patients with DLB (age 45-93 years, 31% women). Positivity on β-amyloid (A+) and tau (T+) biomarkers was determined by CSF β-amyloid1-42 and phosphorylated tau in the European cohort and by Pittsburgh compound B and AV-1451 PET in the Mayo Clinic cohort. Patients were stratified into 4 groups: A-T-, A+T-, A-T+, and A+T+. RESULTS: A-T- was the largest group (39%), followed by A+T- (32%), A+T+ (15%), and A-T+ (13%). The percentage of A-T- decreased with age, and A+ and T+ increased with age in both women and men. A+ increased more in APOE ε4 carriers with age than in noncarriers. A+ was the main predictor of lower cognitive performance when considered together with T+. T+ was associated with a lower frequency of parkinsonism and probable REM sleep behavior disorder. There were no significant interactions between A+ and T+ in relation to the clinical phenotype. CONCLUSIONS: Alzheimer disease pathologic changes are common in DLB and are associated with the clinical phenotype. β-Amyloid is associated with cognitive impairment, and tau pathology is associated with lower frequency of clinical features of DLB. These findings have important implications for diagnosis, prognosis, and disease monitoring, as well as for clinical trials targeting disease-specific proteins in DLB. CLASSIFICATION OF EVIDENCE: This study provides Class II evidence that in patients with probable DLB, β-amyloid is associated with lower cognitive performance and tau pathology is associated with lower frequency of clinical features of DLB.
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| 30. |
- Fu, Jingru, et al.
(författare)
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Fast three-dimensional image generation for healthy brain aging using diffeomorphic registration
- 2023
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Ingår i: Human Brain Mapping. - : Wiley. - 1065-9471 .- 1097-0193. ; 44:4, s. 1289-1308
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Tidskriftsartikel (refereegranskat)abstract
- Predicting brain aging can help in the early detection and prognosis of neurodegenerative diseases. Longitudinal cohorts of healthy subjects scanned through magnetic resonance imaging (MRI) have been essential to understand the structural brain changes due to aging. However, these cohorts suffer from missing data due to logistic issues in the recruitment of subjects. This paper proposes a methodology for filling up missing data in longitudinal cohorts with anatomically plausible images that capture the subject-specific aging process. The proposed methodology is developed within the framework of diffeomorphic registration. First, two novel modules are introduced within Synthmorph, a fast, state-of-the-art deep learning-based diffeomorphic registration method, to simulate the aging process between the first and last available MRI scan for each subject in three-dimensional (3D). The use of image registration also makes the generated images plausible by construction. Second, we used six image similarity measurements to rearrange the generated images to the specific age range. Finally, we estimated the age of every generated image by using the assumption of linear brain decay in healthy subjects. The methodology was evaluated on 2662 T1-weighted MRI scans from 796 healthy participants from 3 different longitudinal cohorts: Alzheimer's Disease Neuroimaging Initiative, Open Access Series of Imaging Studies-3, and Group of Neuropsychological Studies of the Canary Islands (GENIC). In total, we generated 7548 images to simulate the access of a scan per subject every 6 months in these cohorts. We evaluated the quality of the synthetic images using six quantitative measurements and a qualitative assessment by an experienced neuroradiologist with state-of-the-art results. The assumption of linear brain decay was accurate in these cohorts (R2 ∈ [.924,.940]). The experimental results show that the proposed methodology can produce anatomically plausible aging predictions that can be used to enhance longitudinal datasets. Compared to deep learning-based generative methods, diffeomorphic registration is more likely to preserve the anatomy of the different structures of the brain, which makes it more appropriate for its use in clinical applications. The proposed methodology is able to efficiently simulate anatomically plausible 3D MRI scans of brain aging of healthy subjects from two images scanned at two different time points.
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