The DOI matches its Crossref record; 118 of the 118 references it cites were found in a registry or an index.
Neural correlates of Alzheimer's disease and mild cognitive impairment: A systematic and quantitative meta-analysis involving 1351 patients
Open accessAbstract
Alzheimer's disease is the most common form of dementia. Its prodromal stage amnestic mild cognitive impairment is characterized by deficits of anterograde episodic memory. The development of standardized imaging inclusion criteria has to be regarded as a prerequisite for future diagnostic systems. Moreover, successful treatment requires isolating imaging markers predicting the disease. Accordingly, we conducted a systematic and quantitative meta-analysis to reveal the prototypical neural correlates of Alzheimer's disease and its prodromal stage. To prevent any a priori assumptions and enable a data-driven approach only studies applying quantitative automated whole brain analysis were included. Finally, 40 studies were identified involving 1,351 patients and 1,097 healthy control subjects reporting either atrophy or decreases in glucose utilization and perfusion. The currently most sophisticated and best-validated of coordinate-based voxel-wise meta-analyses was applied (anatomical likelihood estimates). The meta-analysis reveals that early Alzheimer's disease affects structurally the (trans-)entorhinal and hippocampal region, functionally the inferior parietal lobules and precuneus. Results further may suggest that atrophy in the (trans-)entorhinal area/hippocampus and hypometabolism/hypoperfusion in the inferior parietal lobules predict most reliably the progression from amnestic mild cognitive impairment to Alzheimer's disease, whereas changes in the posterior cingulate cortex and precuneus are unspecific. Fully developed Alzheimer's disease involved additionally a frontomedian-thalamic network. In conclusion, the meta-analysis characterizes the prototypical neural substrates of Alzheimer's disease and its prodromal stage amnestic mild cognitive impairment. By isolating predictive markers it enables successful treatment strategies in the future and contributes to standardized imaging inclusion criteria for Alzheimer's disease as suggested for future diagnostic systems.
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Cited by
Latent feature representation with stacked auto-encoder for AD/MCI diagnosis
Initiative, T. A. D. N., Suk, H.-I., Lee, S.-W., & Shen, D. (2015) · Brain Structure and Function · doi:10.1007/s00429-013-0687-3 · Cited by 526
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Sacher, J., Neumann, J., Fünfstück, T., Soliman, A., Villringer, A., & Schroeter, M. L. (2012) · Journal of Affective Disorders · doi:10.1016/j.jad.2011.08.001 · Cited by 411
Self-citationHinrichs, C., Singh, V., Xu, G., & Johnson, S. C. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2010.10.081 · Cited by 405
La Joie, R., Perrotin, A., Barré, L., Hommet, C., Mézenge, F., Ibazizene, M., Camus, V., Abbas, A., Landeau, B., Guilloteau, D., et al. (2012) · The Journal of Neuroscience · doi:10.1523/jneurosci.2170-12.2012 · Cited by 374
Metadata
- Authors
- Schroeter, M. L., Stein, T., Maslowski, N., & Neumann, J.
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2009-10
- Volume
- 47
- Issue
- 4
- Pages
- 1196-1206
- ISSN
- 1053-8119 (ISSN-L)
- OpenAlex
- W2128058309
- Cited by
- 323
- References
- 118
- FWCI
- 14.58
- Type
- journal article
- Language
- en
- Open access
- green
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- Schroeter, M. L., Stein, T., Maslowski, N., & Neumann, J. (2009). Neural correlates of Alzheimer's disease and mild cognitive impairment: A systematic and quantitative meta-analysis involving 1351 patients. NeuroImage. https://doi.org/10.1016/j.neuroimage.2009.05.037
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