Regional change in brain morphometry in schizophrenia associated with antipsychotic treatment.
ABSTRACT The purpose of this pilot study was to: (1) determine if regional brain volume change occurs in schizophrenia patients during very short periods of withdrawal from, or stable treatment with, antipsychotics, and; (2) compare results of region-of-interest (ROI) to voxel-based morphometry (VBM) methods. In two small groups of schizophrenic inpatients, magnetic resonance imaging was performed before and after antipsychotic withdrawal, and at two time points during stable chronic antipsychotic treatment. Regional brain volumes were measured using ROI methods. Grey matter volume was measured with VBM. The medication withdrawal group showed no effect of treatment state or antipsychotic type on regional brain volumes with ROI analysis, but effects of both treatment state and antipsychotic type on grey matter volume were observed with VBM in right middle frontal, right medial frontal, right and left superior frontal, right cingulate, and right superior temporal gyrii as well as in the right and left hippocampal gyrii. The chronic stable treatment group showed an effect of time on right caudate, left hippocampal, and total cerebrospinal fluid volumes with ROI analysis, while effects of both time and antipsychotic type were observed with VBM on grey matter volume in the left superior temporal lobe. No findings survived correction for multiple comparisons. A positive correlation between regional volume change and emerging psychopathology was demonstrated using ROI methods in the medication withdrawal group. Treatment state and emergent symptoms in schizophrenia patients were associated with regional volume change over very short time periods. Longitudinal regional brain volume change in schizophrenia patients is likely physiologic and therefore potentially reversible.
- SourceAvailable from: Renata Smieskova
- [Show abstract] [Hide abstract]
ABSTRACT: Although a wide range of approaches have been developed to automatically assess the volume of brain regions from MRI, the reproducibility of these algorithms across different scanners and pulse sequences, their accuracy in different clinical populations and sensitivity to real changes in brain volume have not always been comprehensively examined. Firstly we present a comprehensive testing protocol which comprises 312 freely available MR images to assess the accuracy, reproducibility and sensitivity of automated brain segmentation techniques. Accuracy is assessed in infants, young adults and patients with Alzheimer's disease in comparison to gold standard measures by expert observers using a manual technique based on Cavalieri's principle. The protocol determines the reliability of segmentation between scanning sessions, different MRI pulse sequences and 1.5T and 3T field strengths and examines their sensitivity to small changes in volume using a large longitudinal dataset. Secondly we apply this testing protocol to a novel algorithm for segmenting the lateral ventricles and compare its performance to the widely used FSL FIRST and FreeSurfer methods. The testing protocol produced quantitative measures of accuracy, reliability and sensitivity of lateral ventricle volume estimates for each segmentation method. The novel algorithm showed high accuracy in all populations (intraclass correlation coefficient, ICC>0.95), good reproducibility between MRI pulse sequences (ICC>0.99) and was sensitive to age related changes in longitudinal data. FreeSurfer demonstrated high accuracy (ICC>0.95), good reproducibility (ICC>0.99) and sensitivity whilst FSL FIRST showed good accuracy in young adults and infants (ICC>0.90) and good reproducibility (ICC=0.98), but was unable to segment ventricular volume in patients with Alzheimer's disease or healthy subjects with large ventricles. Using the same computer system, the novel algorithm and FSL FIRST processed a single MRI image in less than 10min while FreeSurfer took approximately 7h. The testing protocol presented enables the accuracy, reproducibility and sensitivity of different algorithms to be compared. We also demonstrate that the novel segmentation algorithm and FreeSurfer are both effective in determining lateral ventricular volume and are well suited for multicentre and longitudinal MRI studies.NeuroImage 07/2011; 58(4):1051-9. DOI:10.1016/j.neuroimage.2011.06.080 · 6.13 Impact Factor
- [Show abstract] [Hide abstract]
ABSTRACT: Introduction. Second-generation antipsychotics treatment is associated with weight gain and metabolic disturbances. Although much research has been done on the topic, the precise mechanisms underlying such side effects are still not well understood. Method. We followed over 16 weeks a group of 17 schizophrenia patients who were treated with olanzapine and monitored biometric, clinical, and metabolic data, including ghrelin and leptin levels. All patients had a structural cerebral magnetic resonance imaging examination during the first week of their followup and at the end of the study. Results. We found positive and negative significant correlations between grey matter volumes of several brain regions and variations of body weight as well as of ghrelin and leptin levels. The right frontal operculum, bilateral precuneus, and bilateral hippocampal regions were found to be significantly associated with those changes. Conclusion. Our results suggest associations between brain structure and metabolic variations in schizophrenia patients taking olanzapine.05/2011; 2011:862350. DOI:10.1155/2011/862350