title: Combined evaluation of FDG-PET and MRI improves detection and differentiation of dementia.
abstract: BACKGROUND
  Various biomarkers have been reported in recent literature regarding imaging abnormalities in different types of dementia. These biomarkers have helped to significantly improve early detection and also differentiation of various dementia syndromes. In this study, we systematically applied whole-brain and region-of-interest (ROI) based support vector machine classification separately and on combined information from different imaging modalities to improve the detection and differentiation of different types of dementia.
  
  
  METHODS
  Patients with clinically diagnosed Alzheimer's disease (AD: n = 21), with frontotemporal lobar degeneration (FTLD: n = 14) and control subjects (n = 13) underwent both [F18]fluorodeoxyglucose positron emission tomography (FDG-PET) scanning and magnetic resonance imaging (MRI), together with clinical and behavioral assessment. FDG-PET and MRI data were commonly processed to get a precise overlap of all regions in both modalities. Support vector machine classification was applied with varying parameters separately for both modalities and to combined information obtained from MR and FDG-PET images. ROIs were extracted from comprehensive systematic and quantitative meta-analyses investigating both disorders.
  
  
  RESULTS
  Using single-modality whole-brain and ROI information FDG-PET provided highest accuracy rates for both, detection and differentiation of AD and FTLD compared to structural information from MRI. The ROI-based multimodal classification, combining FDG-PET and MRI information, was highly superior to the unimodal approach and to the whole-brain pattern classification. With this method, accuracy rate of up to 92% for the differentiation of the three groups and an accuracy of 94% for the differentiation of AD and FTLD patients was obtained.
  
  
  CONCLUSIONS
  Accuracy rate obtained using combined information from both imaging modalities is the highest reported up to now for differentiation of both types of dementia. Our results indicate a substantial gain in accuracy using combined FDG-PET and MRI information and suggest the incorporation of such approaches to clinical diagnosis and to differential diagnostic procedures of neurodegenerative disorders.
authors: Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany. dukart@cbs.mpg.de
authors: Juergen
authors: J
authors: Dukart
authors: Karsten
authors: K
authors: Mueller
authors: Annette
authors: A
authors: Horstmann
authors: Henryk
authors: H
authors: Barthel
authors: Harald E
authors: HE
authors: Möller
authors: Arno
authors: A
authors: Villringer
authors: Osama
authors: O
authors: Sabri
authors: Matthias L
authors: ML
authors: Schroeter
mesh_terms: D000465:Algorithms; D003704:Dementia / Q000000981:diagnostic imaging*; D003937:Diagnosis, Differential; D005260:Female; D019788:Fluorodeoxyglucose F18; D006801:Humans; D008279:Magnetic Resonance Imaging; D008297:Male; D008875:Middle Aged; D049268:Positron-Emission Tomography
chemical_list: D019788:Fluorodeoxyglucose F18