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Rueda O. , A. del P. ., & Enríquez S. , L. F. . (2018). A review of basic neuroimaging techniques in diagnosis of neurodegenerative diseases. Biosalud, 17(2), 59–90. https://doi.org/10.17151/biosa.2018.17.2.5
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Abstract
Currently, neurodegenerative disorders represent a serious public health problem, with an increasing prevalence worldwide. Even though there has been an attempt to harmonize the diagnostic criteria for these disorders, there are still obstacles that hinder their correct differentiation, leading to subsequent errors in therapeutic stages. This review aims to demonstrate the potential of three neuroimaging techniques (positron emission tomography, diffusion-weighted magnetic resonance, and structural magnetic resonance) in the identification of discriminating biomarkers that support the diagnostic process in three of the most common neurodegenerative disorders (Alzheimer’s disease, Mild Cognitive Impairment, frontotemporal dementia). A review was done via an electronic literature search. The use of ScienceDirect, PubMed, SciELO, and IEEE databases to find information on representative structural and functional findings, as well as the diagnostic power of these techniques, is highlighted. As the studies confirm, neuroimages show their potential to establish patterns in the differentiation of neurodegenerative disorders. The structural magnetic resonance remains as a central tool in the identification of cortical and subcortical atrophy patterns. On the other hand, advances in positron emission tomography have enabled not only antemortem diagnosis but also early preclinical identification. Likewise, the recent approach of diffusion magnetic resonance allows to characterizing the microstructural integrity of the cerebral white matter and its relationship with cognitive deterioration in the context of the neurodegenerative disorder. By integrating information from different domains, the clinically accepted tools are supported, guaranteeing better diagnostic accuracy and the prediction of the onset of the disorder. The results show that through multimodal approaches, multicenter collaborations, harmonization of methodologies and acquisition parameters it is possible to include these tools in the clinical repertoire for the identification of these disorders.
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References
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15. Xia C, Dickerson BC. Multimodal PET Imaging of Amyloid and Tau Pathology in Alzheimer Disease and Non–Alzheimer Disease Dementias. PET Clin. 1 de julio de 2017; 12(3):351-9.
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24. Forsberg A, Almkvist O, Engler H, Wall A, Nordberg BL and A. High PIB Retention in Alzheimers
Disease is an Early Event with Complex Relationship with CSF Biomarkers and Functional Parameters [Internet]. Current Alzheimer Research. 2010 [citado 10 de agosto de 2018]. Disponible en: http://www.eurekaselect.com/85618/article
25. Villemagne VL, Okamura N. Tau imaging in the study of ageing, Alzheimer’s disease, and other neurodegenerative conditions. Curr Opin Neurobiol. febrero de 2016; 36:43-51.
26. Misra C, Fan Y, Davatzikos C. Baseline and longitudinal patterns of brain atrophy in MCI patients, and their use in prediction of short-term conversion to AD: Results from ADNI. NeuroImage. 15 de febrero de 2009; 44(4):1415-22.
27. Brier MR, Gordon B, Friedrichsen K, McCarthy J, Stern A, Christensen J, et al. Tau and Aβ imaging, CSF measures, and cognition in Alzheimer’s disease. Sci Transl Med. 11 de mayo de 2016; 8(338):338ra66- 338ra66.
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30. Gray KR, Wolz R, Heckemann RA, Aljabar P, Hammers A, Rueckert D. Multi-region analysis of longitudinal FDG-PET for the classification of Alzheimer’s disease. NeuroImage. 1 de marzo de 2012; 60(1):221-9.
31. Vanhoutte M, Semah F, Rollin Sillaire A, Jaillard A, Petyt G, Kuchcinski G, et al. 18F-FDG PET hypometabolism patterns reflect clinical heterogeneity in sporadic forms of early-onset Alzheimer’s disease. Neurobiol Aging. 1 de noviembre de 2017; 59:184-96.
32. Mosconi L, Tsui WH, Herholz K, Pupi A, Drzezga A, Lucignani G, et al. Multicenter Standardized 18F-FDG PET Diagnosis of Mild Cognitive Impairment, Alzheimer’s Disease, and Other Dementias. J Nucl Med Off Publ Soc Nucl Med. marzo de 2008; 49(3):390-8.
33. Goveas J, O’Dwyer L, Mascalchi M, Cosottini M, Diciotti S, De Santis S, et al. Diffusion-MRI in neurodegenerative disorders. Magn Reson Imaging. 1 de septiembre de 2015; 33(7):853-76.
34. Acosta-Cabronero J, Alley S, Williams GB, Pengas G, Nestor PJ. Diffusion Tensor Metrics as Biomarkers in Alzheimer’s Disease. PLOS ONE. 7 de noviembre de 2012; 7(11):e49072.
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36. Acosta-Cabronero J, Williams GB, Pengas G, Nestor PJ. Absolute diffusivities define the landscape of white matter degeneration in Alzheimer’s disease. Brain. 1 de febrero de 2010; 133(2):529-39.
37. Douaud G, Jbabdi S, Behrens TEJ, Menke RA, Gass A, Monsch AU, et al. DTI measures in crossingfibre areas: Increased diffusion anisotropy reveals early white matter alteration in MCI and mild Alzheimer’s disease. NeuroImage. 1 de abril de 2011; 55(3):880-90.
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