Sie befinden Sich nicht im Netzwerk der Universität Paderborn. Der Zugriff auf elektronische Ressourcen ist gegebenenfalls nur via VPN oder Shibboleth (DFN-AAI) möglich. mehr Informationen...
Ergebnis 6 von 83

Details

Autor(en) / Beteiligte
Titel
Diagnostic utility of novel MRI-based biomarkers for Alzheimer's disease: diffusion tensor imaging and deformation-based morphometry
Ist Teil von
  • Journal of Alzheimer's disease, 2010-01, Vol.20 (2), p.477
Ort / Verlag
Netherlands
Erscheinungsjahr
2010
Link zum Volltext
Quelle
MEDLINE
Beschreibungen/Notizen
  • We report evidence that multivariate analyses of deformation-based morphometry and diffusion tensor imaging (DTI) data can be used to discriminate between healthy participants and patients with Alzheimer's disease (AD) with comparable diagnostic accuracy. In contrast to other studies on MRI-based biomarkers which usually only focus on a single modality, we derived deformation maps from high-dimensional normalization of T1-weighted images, as well as mean diffusivity maps and fractional anisotropy maps from DTI of the same group of 21 patients with AD and 20 healthy controls. Using an automated multivariate analysis of the entire brain volume, widespread decreased white matter integrity and atrophy effects were found in cortical and subcortical regions of AD patients. Mean diffusivity maps and deformation maps were equally effective in discriminating between AD patients and controls (AUC =0.88 vs. AUC=0.85) while fractional anisotropy maps performed slightly inferior. Combining the maps from different modalities in a logistic regression model resulted in a classification accuracy of AUC=0.86 after leave-one-out cross-validation. It remains to be shown if this automated multivariate analysis of DTI-measures can improve early diagnosis of AD in predementia stages.
Sprache
Englisch
Identifikatoren
eISSN: 1875-8908
DOI: 10.3233/JAD-2010-1386
Titel-ID: cdi_pubmed_primary_20164559

Weiterführende Literatur

Empfehlungen zum selben Thema automatisch vorgeschlagen von bX