Metabolic connectivity for differential diagnosis of dementing disorders

Dmitry Titov, Janine Diehl-Schmid, Kuangyu Shi, Robert Perneczky, Na Zou, Timo Grimmer, Jing Li, Alexander Drzezga, Igor Yakushev

Research output: Contribution to journalArticle

20 Scopus citations

Abstract

Presently, visual and quantitative approaches for image-supported diagnosis of dementing disorders rely on regional intensity rather than on connectivity measurements. Here, we test metabolic connectivity for differentiation between Alzheimer's disease and frontotemporal lobar degeneration. Positron emission tomography with 18F-fluorodeoxyglucose was conducted in 47 patients with mild Alzheimer's disease, 52 patients with mild frontotemporal lobar degeneration, and 45 healthy elderly subjects. Sparse inverse covariance estimation and selection were used to identify patterns of metabolic, inter-subject covariance on the basis of 60 regional values. Relative to healthy subjects, significantly more pathological within-lobe connections were found in the parietal lobe of patients with Alzheimer's disease, and in the frontal and temporal lobes of subjects with frontotemporal lobar degeneration. Relative to the frontotemporal lobar degeneration group, more pathological connections between the parietal and temporal lobe were found in the Alzheimer's disease group. The obtained connectivity patterns differentiated between two patients groups with an overall accuracy of 83%. Linear discriminant analysis and univariate methods provided an accuracy of 74% and 69%, respectively. There are characteristic patterns of abnormal metabolic connectivity in mild Alzheimer's disease and frontotemporal lobar degeneration. Such patterns can be utilized for single-subject analyses and might be more accurate in the differential diagnosis of dementing disorders than traditional intensity-based analyses.

Original languageEnglish (US)
Pages (from-to)252-262
Number of pages11
JournalJournal of Cerebral Blood Flow and Metabolism
Volume37
Issue number1
DOIs
StatePublished - Jan 1 2017

Keywords

  • Alzheimer's disease
  • FDG PET
  • frontotemporal lobar degeneration
  • multivariate analysis
  • positron emission tomography

ASJC Scopus subject areas

  • Neurology
  • Clinical Neurology
  • Cardiology and Cardiovascular Medicine

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  • Cite this

    Titov, D., Diehl-Schmid, J., Shi, K., Perneczky, R., Zou, N., Grimmer, T., Li, J., Drzezga, A., & Yakushev, I. (2017). Metabolic connectivity for differential diagnosis of dementing disorders. Journal of Cerebral Blood Flow and Metabolism, 37(1), 252-262. https://doi.org/10.1177/0271678X15622465