title: Localizing gray matter deficits in late-onset depression using computational cortical pattern matching methods.
abstract: OBJECTIVE
  The authors used magnetic resonance imaging and an image analysis technique known as cortical pattern matching to map cortical gray matter deficits in elderly depressed patients with an illness onset after age 60 (late-onset depression).
  
  
  METHODS
  Seventeen patients with late-onset depression (11 women and six men; mean age=75.24, SD=8.52) and 17 group-matched comparison subjects (11 women and six men; mean age=73.88, SD=7.61) were included. Detailed spatial analyses of gray matter were conducted across the entire cortex by measuring local proportions of gray matter at thousands of homologous cortical surface locations in each subject, and these patterns were matched across subjects by using elastic transformations to align sulcal topography. To visualize regional changes, statistical differences were mapped at each cortical surface location in three dimensions.
  
  
  RESULTS
  The late-onset depression group exhibited significant gray matter deficits in the right lateral temporal cortex and the right parietal cortex, where decreases were most pronounced in sensorimotor regions. The statistical maps also showed gray matter deficits in the same regions of the left hemisphere that approached significance after permutation testing. No significant group differences were detected in frontal cortices or any other anatomical region.
  
  
  CONCLUSIONS
  Regionally specific decreases of gray matter occur in late-onset depression, supporting the hypothesis that this subset of elderly patients with major depression presents with certain unique neuroanatomical abnormalities that may differ from patients with an earlier onset of illness.
authors.affiliation: Laboratory of Neuro Imaging, Department of Neurology, Rm. 4238, Reed Neurological Research Center, David Geffen UCLA School of Medicine, 710 Westwood Plaza, Los Angeles, CA 90095-1769, USA.
authors.forename: Martina
authors.initials: M
authors.lastname: Ballmaier
authors.forename: Anand
authors.initials: A
authors.lastname: Kumar
authors.forename: Paul M
authors.initials: PM
authors.lastname: Thompson
authors.forename: Katherine L
authors.initials: KL
authors.lastname: Narr
authors.forename: Helen
authors.initials: H
authors.lastname: Lavretsky
authors.forename: Laverne
authors.initials: L
authors.lastname: Estanol
authors.forename: Heather
authors.initials: H
authors.lastname: Deluca
authors.forename: Arthur W
authors.initials: AW
authors.lastname: Toga
mesh_terms: D017668:Age of Onset; D000368:Aged; D001921:Brain / Q000033:anatomy & histology*; D001931:Brain Mapping / Q000379:methods*; D002555:Cerebrospinal Fluid / Q000502:physiology; D003865:Major Depressive Disorder / Q000175:diagnosis*; D005260:Female; D005625:Frontal Lobe; D007839:Functional Laterality; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000706:statistics & numerical data*; D008279:Magnetic Resonance Imaging / Q000706:statistics & numerical data*; D008297:Male; D009778:Occipital Lobe / Q000033:anatomy & histology; D010296:Parietal Lobe / Q000033:anatomy & histology; D011569:Psychiatric Status Rating Scales; D013702:Temporal Lobe / Q000033:anatomy & histology