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Concordance and discordance between brain perfusion and atrophy in frontotemporal dementia.

Brain imaging and behavior | 2010

The aim of this study was to determine if a dissociation between reduced cerebral perfusion and gray matter (GM) atrophy exists in frontotemporal dementia (FTD). The study included 28 patients with FTD and 29 cognitive normal (CN) subjects. All subjects had MRI at 1.5 T, including T1-weighted structural and arterial spin labeling (ASL) perfusion imaging. Non-parametric concordance/discordance tests revealed that GM atrophy without hypoperfusion occurs in the premotor cortex in FTD whereas concordant GM atrophy and hypoperfusion changes are found in the right prefrontal cortex and bilateral medial frontal lobe. The results suggest that damage of brain function in FTD, assessed by ASL perfusion, can vary regionally despite widespread atrophy. Detection of discordance between brain perfusion and structure in FTD might aid diagnosis and staging of the disease.

Pubmed ID: 20503113 RIS Download

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Associated grants

  • Agency: NIA NIH HHS, United States
    Id: P01 AG019724
  • Agency: NCRR NIH HHS, United States
    Id: P41 RR023953
  • Agency: NIA NIH HHS, United States
    Id: P01AG019724

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Statistical non-Parametric Mapping (tool)

RRID:SCR_002092

A toolbox for Statistical Parametric Mapping (SPM) that provides an extensible framework for voxel level non-parametric permutation/randomization tests of functional Neuroimaging experiments with independent observations. SnPM uses the General Linear Model to construct pseudo t-statistic images, which are then assessed for significance using a standard non-parametric multiple comparisons procedure based on randomization/permutation testing. It is most suitable for single subject PET/SPECT analyses, or designs with low degrees of freedom available for variance estimation. In these situations the freedom to use weighted locally pooled variance estimates, or variance smoothing, makes the non-parametric approach considerably more powerful than conventional parametric approaches, as are implemented in SPM. Further, the non-parametric approach is always valid, given only minimal assumptions. The SnPM toolbox provides an alternative to the Statistics section of SPM.

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