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Subcortical Alignment Precision in Patients with Schizophrenia

Overview
Journal Schizophr Res
Specialty Psychiatry
Date 2010 Jan 26
PMID 20097545
Citations 4
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Abstract

Previous work has demonstrated less accurate alignment of cortical structures for patients with schizophrenia than for matched control subjects when using affine registration techniques. Such a mismatch presents a potential confound for functional neuroimaging studies conducting between-group comparisons. Critically, the same issues may be present for subcortical structures. However, to date no study has explicitly investigated alignment precision for major subcortical structures in patients with schizophrenia. Thus, to address this question we used methods previously validated for assessment of cortical alignment precision to examine alignment precision of subcortical structures. In contrasts to our results with cortex, we found that major subcortical structures (i.e. amygdala, caudate, hippocampus, pallidum, putamen and thalamus) showed similar alignment precision for schizophrenia (N=48) and control subjects (N=45) regardless of the template used (other individuals with schizophrenia or healthy controls). Taken together, the present results show that, unlike cortex, alignment for six major subcortical structures is not compromised in patients with schizophrenia and as such is unlikely to confound between-group functional neuroimaging investigations.

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References
1.
Velakoulis D, Pantelis C, McGorry P, Dudgeon P, Brewer W, Cook M . Hippocampal volume in first-episode psychoses and chronic schizophrenia: a high-resolution magnetic resonance imaging study. Arch Gen Psychiatry. 1999; 56(2):133-41. DOI: 10.1001/archpsyc.56.2.133. View

2.
Wang L, Mamah D, Harms M, Karnik M, Price J, Gado M . Progressive deformation of deep brain nuclei and hippocampal-amygdala formation in schizophrenia. Biol Psychiatry. 2008; 64(12):1060-8. PMC: 2855119. DOI: 10.1016/j.biopsych.2008.08.007. View

3.
Desai R, Liebenthal E, Possing E, Waldron E, Binder J . Volumetric vs. surface-based alignment for localization of auditory cortex activation. Neuroimage. 2005; 26(4):1019-29. DOI: 10.1016/j.neuroimage.2005.03.024. View

4.
Woods R, Grafton S, Watson J, Sicotte N, Mazziotta J . Automated image registration: II. Intersubject validation of linear and nonlinear models. J Comput Assist Tomogr. 1998; 22(1):153-65. DOI: 10.1097/00004728-199801000-00028. View

5.
Cox R . AFNI: software for analysis and visualization of functional magnetic resonance neuroimages. Comput Biomed Res. 1996; 29(3):162-73. DOI: 10.1006/cbmr.1996.0014. View