Stijn Michielse

Maastricht Universitair Medisch Centrum, Maestricht, Limburg, Netherlands

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Publications (6)27.67 Total impact

  • Schizophrenia Research 04/2014; 153:S55-S56. DOI:10.1016/S0920-9964(14)70181-1 · 3.92 Impact Factor
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    ABSTRACT: Background: Bone mineral density (BMD), as an indicator of cumulative estrogen exposure, may be reduced in female patients with psychotic disorder (van der Leeuw et al., 2013), possibly reflecting reduced cerebral exposure to estrogen and alterations in neuroprotective effects. To the degree that BMD is a marker of cumulative (endogenous) estrogen exposure, we hypothesized that BMD would be positively associated with cerebral gray and white matter indices. Methods: Dual X-ray absorptiometry (DEXA) and magnetic resonance (MRI) scans were acquired in fourteen female patients diagnosed with a psychotic disorder. BMD was expressed in total BMD (g/cm(2)), Z- and T-scores. Cerebral cortical thickness (CT) (as indicator of gray matter status) and fractional anisotropy (FA) (as indicator of white matter integrity) were measured and served as the dependent variables in multilevel random regression models. BMD measures were the independent variables. Results: Femoral BMD measures were positively associated with CT at trend significance (total BMD: B=0.266, 95% CI: -0.019-0.552, p=0.067; Z-score: B=0.034, 95% CI: 0.001-0.067, p=0.046; T-score: B=0.034, 95% CI: 0.000-0.068, p=0.052). There were no significant associations between femoral BMD measures and FA. Conclusions: The data suggest that in women with psychotic disorder, alterations in the neuroprotective effect of estrogen (as measured by BMD) impact cortical gray matter, but not white matter integrity. These findings merit further investigation and, if replicated, would lend support to the estrogen hypothesis of schizophrenia.
    Schizophrenia Research 10/2013; 150(1-1):114-20. DOI:10.1016/j.schres.2013.07.033 · 3.92 Impact Factor
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    ABSTRACT: Background: There is evidence for microstructural white matter alterations in patients with psychotic disorder, suggesting altered interregional connectivity. Less is known about the presence and role of white matter alterations in well individuals at higher than average genetic risk for psychotic disorder. Methods: 85 patients with psychotic disorder, 93 non-psychotic siblings of patients with psychotic disorder and 80 healthy controls underwent a diffusion tensor imaging (DTI) scanning protocol. In a whole brain voxel-based analysis using Tract Based Spatial Statistics (TBSS), fractional anisotropy (FA) values were compared between the three groups. Effects of antipsychotic medication and drug use were examined. Results: The patients displayed significantly lower mean FA than the controls in the following regions: corpus callosum (genu, body, splenium), forceps major and minor, external capsule bilaterally, corona radiata (anterior, posterior) bilaterally, left superior corona radiata and posterior thalamic radiation bilaterally. Similar FA differences existed between the patients and siblings; the siblings did not differ from the controls. Conclusion: Profound microstructural white matter alterations were found in the corpus callosum and other tracti and fasciculi in the patients with psychotic disorder, but not in siblings and the controls. These alterations may reflect brain pathology associated with the illness, illness-related environmental risk factors, or its treatment, rather than genetic risk.
    Schizophrenia Research 03/2013; 146(1-3). DOI:10.1016/j.schres.2013.03.002 · 3.92 Impact Factor

  • Schizophrenia Research 04/2012; 136:S87-S88. DOI:10.1016/S0920-9964(12)70310-9 · 3.92 Impact Factor
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    ABSTRACT: Previous diffusion tensor imaging (DTI) studies confirmed the vulnerability of frontal callosal fibers to normal aging. The present study extended this examination systematically to other prefrontal white matter regions. Structural magnetic resonance imaging and DTI datasets were acquired from 69 healthy subjects aged 22-84 years. The prefrontal white matter was parcellated into several anatomical sub-regions: medial and lateral orbitofrontal white matter, dorsolateral prefrontal white matter, and medial prefrontal white matter, using reliable DTI-tractography protocols. Tract-specific characteristics were calculated using Matlab. Regression models were used to determine the relationship between age and structural integrity of white matter tracts. The results of our study demonstrate regional age-related changes in the prefrontal white matter tracts of the human brain. This study was cross-sectional and therefore additional longitudinal studies are needed to confirm our findings.
    Brain Structure and Function 05/2011; 216(4):417-31. DOI:10.1007/s00429-011-0321-1 · 5.62 Impact Factor
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    ABSTRACT: We examined age-related changes in the cerebral white matter. Structural magnetic resonance images (MRIs) and diffusion tensor images (DTIs) were acquired from 69 healthy subjects aged 22-84 years. Quantitative DTI tractography was performed for nine different white matter tracts to determine tract volume, fractional anisotropy (FA), mean diffusivity (MD), axial, and radial diffusivities. We used automated and manual segmentation to determine volumes of gray matter (GM), white mater (WM), cerebrospinal fluid (CSF), and intracranial space. The results showed significant effects of aging on WM, GM, CSF volumes, and selective effects of aging on structural integrity of different white matter tracts. WM of the prefrontal region was the most vulnerable to aging, while temporal lobe connections, cingulum, and parieto-occipital commissural connections showed relative preservation with age. This study was cross-sectional, and therefore, additional longitudinal studies are needed to confirm our findings.
    NeuroImage 10/2010; 52(4):1190-201. DOI:10.1016/j.neuroimage.2010.05.019 · 6.36 Impact Factor

Publication Stats

76 Citations
27.67 Total Impact Points


  • 2013
    • Maastricht Universitair Medisch Centrum
      • Central Diagnostic Laboratory
      Maestricht, Limburg, Netherlands
    • Maastricht University
      Maestricht, Limburg, Netherlands
  • 2010-2011
    • University of Alberta
      • Department of Biomedical Engineering
      Edmonton, Alberta, Canada