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Fractional Anisotropy changes in Parahippocampal Cingulum due to Alzheimer's Disease.

  • Dalboni da Rocha JL Faculté de psychologie et des sciences de l'éducation, University of Geneva, Geneva, Switzerland. Josue.Dalboni@unige.ch.
  • Bramati I D'Or Institute for Research and Education, Rio de Janeiro, Brazil.
  • Coutinho G D'Or Institute for Research and Education, Rio de Janeiro, Brazil.
  • Tovar Moll F D'Or Institute for Research and Education, Rio de Janeiro, Brazil.
  • Sitaram R Institute for Biological and Medical Engineering, Department of Psychiatry, and Section of Neuroscience, Pontificia Universidad Católica de Chile, Santiago, Chile. rasitaram@uc.cl.
  • 2020-02-16
Published in:
  • Scientific reports. - 2020
Aged
Alzheimer Disease
Anisotropy
Case-Control Studies
Female
Hippocampus
Humans
Male
Organ Specificity
Support Vector Machine
English Current treatments for Alzheimer's disease are only symptomatic and limited to reduce the progression rate of the mental deterioration. Mild Cognitive Impairment, a transitional stage in which the patient is not cognitively normal but do not meet the criteria for specific dementia, is associated with high risk for development of Alzheimer's disease. Thus, non-invasive techniques to predict the individual's risk to develop Alzheimer's disease can be very helpful, considering the possibility of early treatment. Diffusion Tensor Imaging, as an indicator of cerebral white matter integrity, may detect and track earlier evidence of white matter abnormalities in patients developing Alzheimer's disease. Here we performed a voxel-based analysis of fractional anisotropy in three classes of subjects: Alzheimer's disease patients, Mild Cognitive Impairment patients, and healthy controls. We performed Support Vector Machine classification between the three groups, using Fisher Score feature selection and Leave-one-out cross-validation. Bilateral intersection of hippocampal cingulum and parahippocampal gyrus (referred as parahippocampal cingulum) is the region that best discriminates Alzheimer's disease fractional anisotropy values, resulting in an accuracy of 93% for discriminating between Alzheimer's disease and controls, and 90% between Alzheimer's disease and Mild Cognitive Impairment. These results suggest that pattern classification of Diffusion Tensor Imaging can help diagnosis of Alzheimer's disease, specially when focusing on the parahippocampal cingulum.
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  • English
Open access status
gold
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Persistent URL
https://sonar.ch/global/documents/169631
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