دورية أكاديمية
Brain age as a biomarker for pathological versus healthy ageing – a REMEMBER study
| العنوان: | Brain age as a biomarker for pathological versus healthy ageing – a REMEMBER study |
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| المؤلفون: | Mandy M.J. Wittens, Stijn Denissen, Diana M. Sima, Erik Fransen, Ellis Niemantsverdriet, Christine Bastin, Florence Benoit, Bruno Bergmans, Jean-Christophe Bier, Peter Paul de Deyn, Olivier Deryck, Bernard Hanseeuw, Adrian Ivanoiu, Gaëtane Picard, Annemie Ribbens, Eric Salmon, Kurt Segers, Anne Sieben, Hanne Struyfs, Evert Thiery, Jos Tournoy, Anne-Marie van Binst, Jan Versijpt, Dirk Smeets, Maria Bjerke, Guy Nagels, Sebastiaan Engelborghs |
| المصدر: | Alzheimer’s Research & Therapy, Vol 16, Iss 1, Pp 1-18 (2024) |
| بيانات النشر: | BMC, 2024. |
| سنة النشر: | 2024 |
| المجموعة: | LCC:Neurosciences. Biological psychiatry. Neuropsychiatry LCC:Neurology. Diseases of the nervous system |
| مصطلحات موضوعية: | Alzheimer’s disease, Magnetic resonance imaging, Biomarker, Brain predicted age difference, Brain age, Automated volumetry, Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571, Neurology. Diseases of the nervous system, RC346-429 |
| الوصف: | Abstract Objectives This study aimed to evaluate the potential clinical value of a new brain age prediction model as a single interpretable variable representing the condition of our brain. Among many clinical use cases, brain age could be a novel outcome measure to assess the preventive effect of life-style interventions. Methods The REMEMBER study population (N = 742) consisted of cognitively healthy (HC,N = 91), subjective cognitive decline (SCD,N = 65), mild cognitive impairment (MCI,N = 319) and AD dementia (ADD,N = 267) subjects. Automated brain volumetry of global, cortical, and subcortical brain structures computed by the CE-labeled and FDA-cleared software icobrain dm (dementia) was retrospectively extracted from T1-weighted MRI sequences that were acquired during clinical routine at participating memory clinics from the Belgian Dementia Council. The volumetric features, along with sex, were combined into a weighted sum using a linear model, and were used to predict ‘brain age’ and ‘brain predicted age difference’ (BPAD = brain age–chronological age) for every subject. Results MCI and ADD patients showed an increased brain age compared to their chronological age. Overall, brain age outperformed BPAD and chronological age in terms of classification accuracy across the AD spectrum. There was a weak-to-moderate correlation between total MMSE score and both brain age (r = -0.38,p |
| نوع الوثيقة: | article |
| وصف الملف: | electronic resource |
| اللغة: | English |
| تدمد: | 1758-9193 |
| Relation: | https://doaj.org/toc/1758-9193 |
| DOI: | 10.1186/s13195-024-01491-y |
| URL الوصول: | https://doaj.org/article/31dd8603773e4eab883fb41094f7a697 |
| رقم الأكسشن: | edsdoj.31dd8603773e4eab883fb41094f7a697 |
| قاعدة البيانات: | Directory of Open Access Journals |
Find this article in full text from Springer Verlag. 
Full Text Finder | تدمد: | 17589193 |
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| DOI: | 10.1186/s13195-024-01491-y |