Alzheimer's disease neuroimaging
By Jennifer L. Whitwell. Current Opinion in Neurology, 2018
751 citations recorded by the source corpus.
Purpose of review The aim of this study was to discuss the contribution of neuroimaging studies to our understanding of Alzheimer's disease. We now have the capability of measuring both tau and beta-amyloid (A&bgr;) proteins in the brain, which together with more traditional neuroimaging modalities, has led the field to focus on using neuroimaging to better characterize disease mechanisms underlying Alzheimer's disease. Recent findings Studies have utilized tau and A&bgr; PET, as well as [18F]fluorodeoxyglucose PET, and structural and functional MRI, to investigate the following topics: phenotypic variability in Alzheimer's disease , including how neuroimaging findings are related to clinical phenotype and age; multimodality analyses to investigate the relationships between different neuroimaging modalities and what that teaches us about disease mechanisms; disease staging by assessing neuroimaging changes in the very earliest phases of the disease in cognitively normal individuals and individuals carrying an autosomal dominant Alzheimer's disease mutation; and influence of other comorbidities and proteins to the disease process. Summary The findings shed light on the role of tau and A&bgr;, as well as age and other comorbidities, in the neurodegenerative process in Alzheimer's disease. This knowledge will be crucial in the development of better disease biomarkers and targeted therapeutic approaches.
Subfields: Cognitive Neuroscience, Physiology, Psychiatry and Mental health
View Paper: https://www.semanticscholar.org/paper/e41bfc4708f0389c70833bc0e2f17b5f5c365272
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- Armin Biller
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- Jens Kleesiek
- Martin Bendszus
Citations in the corpus
- Deep MRI brain extraction: A 3D convolutional neural network for skull stripping (2016, positive): “…measures already utilized in several studies (FennemaNotestine et al., 2006; Galdames et al., 2012; Iglesias et al., 2011; Rex et al., 2004; Wang et al., 2014) were used to compare a predicted brain segmentation Pwith the associated referencemask R. TheDice coefficient (Dice, 1945) is…”
- Different Partial Volume Correction Methods Lead to Different Conclusions: an 18F-FDG PET Study of Aging (2016, methodology): “Pons was chosen because it is commonly used (Ewers et al., 2014; Kantarci et al., 2001; Knopman et al., 2014; Landau et al., 2011), easy to identify, has small PVEs, and is thought to be resistant to atrophy, at least in AD (Minoshima et al., 1995).”