Localizing gray matter deficits in late-onset depression using computational cortical pattern matching methods

Martina Ballmaier, Anand Kumar, Paul M. Thompson, Katherine L. Narr, Helen Lavretsky, Laverne Estanol, Heather DeLuca, Arthur W. Toga

Research output: Contribution to journalArticlepeer-review

53 Scopus citations

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). Method: Seventeen patients with lateonset 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.

Original languageEnglish
Pages (from-to)2091-2099
Number of pages9
JournalAmerican Journal of Psychiatry
Volume161
Issue number11
DOIs
StatePublished - Nov 2004
Externally publishedYes

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