title: Structural MRI in frontotemporal dementia: comparisons between hippocampal volumetry, tensor-based morphometry and voxel-based morphometry.
abstract: BACKGROUND
  MRI is an important clinical tool for diagnosing dementia-like diseases such as Frontemporal Dementia (FTD). However there is a need to develop more accurate and standardized MRI analysis methods.
  
  
  OBJECTIVE
  To compare FTD with Alzheimer's Disease (AD) and Mild Cognitive Impairment (MCI) with three automatic MRI analysis methods - Hippocampal Volumetry (HV), Tensor-based Morphometry (TBM) and Voxel-based Morphometry (VBM), in specific regions of interest in order to determine the highest classification accuracy.
  
  
  METHODS
  Thirty-seven patients with FTD, 46 patients with AD, 26 control subjects, 16 patients with progressive MCI (PMCI) and 48 patients with stable MCI (SMCI) were examined with HV, TBM for shape change, and VBM for gray matter density. We calculated the Correct Classification Rate (CCR), sensitivity (SS) and specificity (SP) between the study groups.
  
  
  RESULTS
  We found unequivocal results differentiating controls from FTD with HV (hippocampus left side) (CCR = 0.83; SS = 0.84; SP = 0.80), with TBM (hippocampus and amygdala (CCR = 0.80/SS = 0.71/SP = 0.94), and with VBM (all the regions studied, especially in lateral ventricle frontal horn, central part and occipital horn) (CCR = 0.87/SS = 0.81/SP = 0.96). VBM achieved the highest accuracy in differentiating AD and FTD (CCR = 0.72/SS = 0.67/SP = 0.76), particularly in lateral ventricle (frontal horn, central part and occipital horn) (CCR = 0.73), whereas TBM in superior frontal gyrus also achieved a high accuracy (CCR = 0.71/SS = 0.68/SP = 0.73). TBM resulted in low accuracy (CCR = 0.62) in the differentiation of AD from FTD using all regions of interest, with similar results for HV (CCR = 0.55).
  
  
  CONCLUSIONS
  Hippocampal atrophy is present not only in AD but also in FTD. Of the methods used, VBM achieved the highest accuracy in its ability to differentiate between FTD and AD.
authors.affiliation: Institute of Clinical Medicine, Neurology, University of Eastern Finland, Kuopio, Finland.
authors.forename: Miguel Ángel
authors.initials: MÁ
authors.lastname: Muñoz-Ruiz
authors.forename: Päivi
authors.initials: P
authors.lastname: Hartikainen
authors.forename: Juha
authors.initials: J
authors.lastname: Koikkalainen
authors.forename: Robin
authors.initials: R
authors.lastname: Wolz
authors.forename: Valtteri
authors.initials: V
authors.lastname: Julkunen
authors.forename: Eini
authors.initials: E
authors.lastname: Niskanen
authors.forename: Sanna-Kaisa
authors.initials: SK
authors.lastname: Herukka
authors.forename: Miia
authors.initials: M
authors.lastname: Kivipelto
authors.forename: Ritva
authors.initials: R
authors.lastname: Vanninen
authors.forename: Daniel
authors.initials: D
authors.lastname: Rueckert
authors.forename: Yawu
authors.initials: Y
authors.lastname: Liu
authors.forename: Jyrki
authors.initials: J
authors.lastname: Lötjönen
authors.forename: Hilkka
authors.initials: H
authors.lastname: Soininen
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D003710:Demography; D056324:Diffusion Tensor Imaging; D005260:Female; D057180:Frontotemporal Dementia / Q000473:pathology*; D006624:Hippocampus / Q000473:pathology*; D006801:Humans; D008279:Magnetic Resonance Imaging; D008297:Male; D008875:Middle Aged