Magnetic resonance imaging studies have identified hippocampal volume reductions in schizophrenia and amygdala volume enlargements in bipolar disorder, suggesting different medial temporal lobe abnormalities in these conditions. These studies have been limited by small samples and the absence of patients early in the course of illness.
To investigate hippocampal and amygdala volumes in a large sample of patients with chronic schizophrenia, patients with first-episode psychosis, and patients at ultra-high risk for psychosis compared with control subjects.
Cross-sectional comparison between patient groups and controls.
Individuals with chronic schizophrenia were recruited from a mental health rehabilitation service, and individuals with first-episode psychosis and ultra-high risk were recruited from the ORYGEN Youth Health Service. Control subjects were recruited from the community.
The study population of 473 individuals included 89 with chronic schizophrenia, 162 with first-episode psychosis, 135 at ultra-high risk for psychosis (of whom 39 subsequently developed a psychotic illness), and 87 controls.
Hippocampal, amygdala, whole-brain, and intracranial volumes were estimated on high-resolution magnetic resonance images and compared across groups, including first-episode subgroups. We used 1- and 2-way analysis of variance designs to compare hippocampal and amygdala volumes across groups, correcting for intracranial volume and covarying for age and sex. We investigated the effects of medication and illness duration on structural volumes.
Patients with chronic schizophrenia displayed bilateral hippocampal volume reduction. Patients with first-episode schizophrenia but not schizophreniform psychosis displayed left hippocampal volume reduction. The remaining first-episode subgroups had normal hippocampal volumes compared with controls. Amygdala volume enlargement was identified only in first-episode patients with nonschizophrenic psychoses. Patients at ultra-high risk for psychosis had normal baseline hippocampal and amygdala volumes whether or not they subsequently developed a psychotic illness. Structural volumes did not differ between patients taking atypical vs typical antipsychotic medications, and they remained unchanged when patients treated with lithium were excluded from the analysis.
Medial temporal structural changes are not seen until after the onset of a psychotic illness, and the pattern of structural change differs according to the type of psychosis. These findings have important implications for future neurobiological studies of psychotic disorders and emphasize the importance of longitudinal studies examining patients before and after the onset of a psychotic illness.
"Twin, family and sibling studies have found that structural brain abnormalities are to some extent shared between affected and unaffected family members, leading researchers to suggest that subcortical abnormalities reflect a risk factor mediated by genetic components (Lawrie et al., 1999; Seidman et al., 1999; Staal et al., 2000; Cannon et al., 2002; Job et al., 2003). However, studies have also reported no differences in hippocampal and amygdalar volumes in healthy relatives of patients (Arnold et al., 2015) or in individuals at high clinical risk of the disorder (Velakoulis et al., 2006). By focusing on the extent to which brain alterations form predictive markers of the disorder, researchers aim to facilitate pre-onset/first-episode interventions (Pantelis et al., 2005), as early diagnosis has been associated with an improved clinical outcome. "
[Show abstract][Hide abstract] ABSTRACT: It is unknown whether brain changes occur prior to onset of schizophrenia or after it develops. Prospective familial high risk studies provide a good method to investigate this. In the Edinburgh High Risk Study, structural MRI scans of 150 young individuals at familial high risk of schizophrenia, 34 patients with first-episode schizophrenia and 36 matched controls were obtained. Of the high risk participants with scans suitable for analysis, 17 developed schizophrenia after the scans were taken, whilst 57 experienced isolated or sub-clinical psychotic symptoms, and 70 remained well. We used Freesurfer to extract volumetric measurements of the hippocampus, amygdala and nucleus accumbens with the aim of assessing whether any alterations found were present in all those at high risk, or selectively in the high risk cohort based on future clinical outcome, or only in those experiencing their first-episode of psychosis. We found no significant differences in any examined regions between controls and those at high risk, or between those at high risk who later developed schizophrenia and those who remained well. However, patients with first-episode schizophrenia demonstrated significant volumetric reductions in the bilateral hippocampus, left amygdala, and right nucleus accumbens compared to high risk individuals and healthy controls, which were not significantly associated with the intake of anti-psychotic medication or duration of illness. We found that patients had significantly smaller left amygdalae and bilateral hippocampus compared to HR[ill]. Our findings suggest that volumetric reductions of the hippocampus, amygdala and nucleus accumbens occur early in the first-episode of psychosis. The apparent absence of high risk versus control differences we found using Freesurfer is at odds with our previous studies conducted on the same sample, and possible methodological reasons for these apparent discrepancies are discussed.
Schizophrenia Research 04/2015; 165(1). DOI:10.1016/j.schres.2015.03.024 · 3.92 Impact Factor
"In this regard, image segmentation plays a vital role to analyze the tasks, for instance, quantification of tissue volume , computer aided surgery , treatment planning , anatomical structure study , and disease diagnosis  . Previously, many approaches for medical image segmentation have been proposed      , but not a single method is able to efficiently handle these problems (partial volume effects, noise, and low quality imaging etc.). "
[Show abstract][Hide abstract] ABSTRACT: In this paper, a robust image segmentation and intelligent decision making system for carotid artery ultrasound images is proposed. Medical images may have various types of inherent degradations due to imaging equipments, operating environment, etc. For instance, carotid artery ultrasound images are affected by low resolution, speckle noise, and wave interferences. Hence, robust medical image clustering technique is inevitable for obtaining accurate results in the subsequent stages. In this context, a robust fuzzy radial basis function network (RFRBFN) technique is proposed. The proposed technique modified fuzzy RBF algorithm by incorporating spatial information and a smoothing parameter into its objective function, consequently, the proposed technique is able to cope with noise related variations. To assess the effectiveness, the RFRBFN technique is applied to segment carotid artery ultrasound images and its performance has been evaluated against impulse, and Gaussian noises of various intensities. Performance comparison with existing methods shows that the proposed RFRBFN outperforms the existing fuzzy based c-means and RBF techniques in case of both noisy and noise-free images. Experiments on 200 real carotid artery ultrasound images reveal the proposed technique offers effective segmentation results. Finally, intima-media thickness is measured from the obtained segmented images and multi-layer backpropagation neural network is employed to classify the segmented images into normal or diseased subjects. The proposed intelligent decision making system can thus be used as a secondary observer for identification of plaque in the carotid artery.
"hippocampal volumes have been found to be smaller in schizophrenia (DeLisi et al., 2004; Honea et al., 2005; Steen et al., 2006; Velakoulis et al., 2006; Vita et al., 2006; Vita and de Peri, 2007). Reductions of hippocampal volumes have been linked to impaired declarative memory function, which is considered a core clinical feature of schizophrenia (Tamminga et al., 2010; Hasan et al., 2013). "
[Show abstract][Hide abstract] ABSTRACT: The objective of this longitudinal magnetic resonance (MR) imaging study was to examine the effects of endurance training on hippocampal and grey matter volumes in schizophrenia patients and healthy controls.
20 chronic schizophrenia patients and 21 age- and gender-matched healthy controls underwent 3months of endurance training (30 min, 3 times perweek). 19 additionally recruited schizophrenia patients played table soccer (“foosball” in the USA) over the same period. MR imaging with 3D-volumetric T1-weighted sequences was performed on a 3 T MR scanner at baseline, after 6 weeks and after the 3-month intervention and 3 additional training-free months. In addition to voxel-based morphometry (VBM), we performed manual and automatic delineation of the hippocampus and its substructures. Endurance capacity and psychopathological symptoms were measured as secondary endpoints. No significant increases in the volumes of the hippocampus or hippocampal substructures were observed in schizophrenia patients or healthy controls. However, VBM analyses displayed an increased volume of the left superior, middle and inferior anterior temporal gyri compared to baseline in schizophrenia patients after the endurance training, whereas patients playing table soccer showed increased volumes in the motor and anterior cingulate cortices. After the additional training-free period, the differenceswere no longer present.While endurance capacity improved in exercising patients and healthy controls, psychopathological symptoms did not significantly change. The subtle changes in the left temporal cortex indicate an impact of exercise on brain volumes in schizophrenia.
Subsequent studies in larger cohorts are warranted to address the question of response variability of endurance training.
Schizophrenia Research 02/2015; DOI:10.1016/j.schres.2015.01.005 · 3.92 Impact Factor
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