Volume 14, Issue 3 (May & Jun 2023)                   BCN 2023, 14(3): 355-364 | Back to browse issues page

XML Print

Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Heidari Z, Mahmoudzadeh-Sagheb H, Shakiba M, Charkhat Gorgich E A. Brain Structural Changes in Schizophrenia Patients Compared to the Control: An MRI-based Cavalieri’s Method. BCN 2023; 14 (3) :355-364
URL: http://bcn.iums.ac.ir/article-1-2187-en.html
1- Infectious Diseases and Tropical Medicine Research Center, Research Institute of Cellular and Molecular Sciences in Infectious Diseases, Zahedan University of Medical Sciences, Zahedan, Iran.
2- Department of Neurology, School of Medicine, Zahedan University of Medical Sciences, Zahedan, Iran.
3- Department of Anatomy, School of Medicine, Iranshahr University of Medical Sciences, Iranshahr, Iran.
Full-Text [PDF 646 kb]       |   Abstract (HTML) 
1. Introduction
Schizophrenia is a progressive, debilitating, and severe neuropsychiatric disorder that affects approximately 0.5%-1% of the population worldwide (Kim et al., 2015; Van Os & Kapur). Schizophrenia typically emerges in the adolescent years or early adulthood, between 18 and 25 years old, and it is frequently recognized as a chronic and lifelong disease (Insel, 2010). It is characterized by positive symptoms (hallucinations, delusions, and paranoia), negative symptoms (anhedonia, social withdrawal, and behavioral disorders), and cognitive dysfunction (memory impairment, inability to maintain attention, and disruption in executive functions) (Meyer, 2013; Tandon et al., 2009). Thus far, several factors have been suggested to be involved in the development and progression of the disease, such as alternations and disconnection in myelin; genetic factors; the number of dopaminergic neurons and oligodendrocytes; volumetric changes in different areas of the brain; and neurodegenerative, neuroinflammation, and neurodevelopmental deficiencies. All these factors can lead to structural and functional changes in the brain of patients with schizophrenia (Jaaro-Peled et al., 2010; Roussos & Haroutunian, 2014). Despite extensive studies and substantial advances in genetic, neurochemical, and neurobiological theories presented on schizophrenia (Insel, 2010; Jaaro-Peled et al., 2009), the exact development, progression, and underlying pathogeneses of this complex psychological disorder are unknown and challenging for most researchers and clinicians (Murray & Lewis, 1987). As mentioned above, one of the contributing factors in the pathology of schizophrenia is volumetric changes, which can lead to structural disconnection and neurophysiological alternations in the brain of patients (Tepest et al., 2013). 
In numerous investigations, the stereological technique is the recommended approach for the estimation of quantitative parameters of the brain in normal aging, neurodegenerative diseases, and schizophrenia (Heidari et al., 2017b; Pakkenberg et al., 2009). These exact and unbiased findings help us to obtain a better perception of underlying mechanisms and alternations in the development and progression in different phases (acute, chronic) of the disease (Kipp et al., 2017). 
Quantitative volumetric brain measurements on magnetic resonance imaging (MRI) scans in patients with neurodegenerative disease owing to selective regional atrophy are beneficial for clinicians to ascertain disease progression and to evaluate volume alternations and response to treatment (Ciumas et al., 2008; Heidari et al., 2017b). A previous study conducted by our team on brain MRI scans of methamphetamine abusers showed that volume loss was significant in some areas of the brain in drug abusers compared to controls (Heidari et al., 2017a). Another volumetric study based on Cavalieri’s point counting method on brain MRI scans of patients with Parkinson disease revealed that volume reduction in some regions of the brain in these patients was significant compared to that in the controls. These studies suggested that quantitative evaluation of MRI scans might be beneficial for clinical applications and to analyze clinical manifestations in patients (Heidari et al., 2020; Heidari et al., 2017b). Therefore, the main goal of the current study is to estimate the volumetric analysis of brain MRI scans in patients with schizophrenia and compare the results with the controls. 

2. Materials and Methods
Study design and subjects

In the current case-control study, we evaluated volumetric alternations on brain MRI scans of 40 subjects in two groups: Patients with schizophrenia (n=20) and gender and age-matched healthy controls (n=20). Schizophrenia was diagnosed based on the diagnostic and statistical manual of mental disorders fourth edition, the criteria of text revision (DSM-IV TR), by an expert psychiatrist. The schizophrenia group included patients (14 males, 6 females) who had a history of the disease for at least 12 months without a history of other neurological diseases such as epilepsy, Parkinson and Alzheimer disease, mental retardation, and head trauma and taking psychoactive substances. The healthy control group included those without a history of psychiatric and neurological disorders, underlying diseases, and drug abuse. In addition, alcoholics and smokers were excluded from the study. All the subjects were enrolled by the convenience sampling method from individuals referred to the psychiatric clinic of Baharan Psychiatric Hospital, Zahedan, Southeastern Iran. 

MRI protocol and volumetric estimations
Stereological estimations and quantitative measurements of brain regions in both groups were done based on Cavalieri’s principle. According to this principle, for unbiased estimation of the volume of an object, it must be sectioned into a series of parallel planes with a fixed distance. To avoid bias, the first section must be placed at a random situation in a constant interval of length. The serial sections acquired from the object must be transited via the entire area (Alper et al., 2006). In the present study, the method of stereological estimation was conducted in the following manner:
At first, for estimation of volumetric parameters of various areas in the participants, FLAIR (fluid-attenuated inversion recovery) successions of structural brain MRI scans taken in two diverse anatomical axes (sagittal, coronal) with 4 mm slice thickness and 5 mm intervals were prepared. The brain structural MRIs from patients with schizophrenia and controls were captured using a three-dimensional (3D) high-resolution T1-weighted MR 1.5 T scanner system (GE systems, Paris). Next, point-counting grids that contained organized points superimposed on MRI scans and points hit the desired regions of the brain were computed by Cavalieri’s point-counting method as described in our previous studies (Heidari et al., 2020; Heidari et al., 2017a; Heidari et al., 2017b). (Figure 1).

Subsequently, the brain regions’ quantitative estimations (volumes and volume densities) were compared between schizophrenia and control groups. All volumetric calculations were performed using Cavalieri’s point-counting Equcation (Equcation 1), and the results were reported as cm3. The Points counting technique demonstrated on a sagittal brain MRI using a stereological method (Equation 1):

Where v is the estimated volume of any desired object, ∑P is the sum of the number of points hitting that object in all slices, a/p is the area associated with each point in the stereological grid, t is the mean distance between the captured slices, and M is the linear magnification of the image (Heidari et al., 2020; Heidari et al., 2017a; Heidari   et al., 2017b). 
In the next step, an estimate of the volume density (Vv) of the brain components in the reference space (total brain) was obtained using the formula Vv=P (part)/P (ref), where P (part) is the number of test points that fall in each component profile, and P (ref) is the number of points that hit the total brain (Heidari et al., 2020).

Statistical analysis
The collected data were reported as Mean±SE, and a nonparametric Mann-Whitney U test was applied to characterize volumetric differences between the two groups. SPSS software, version 21 for windows (Chicago, IL, USA) was used for all statistical analyses. The significance level was set at P<0.05.

3. Results
The Mean±SD age of patients with schizophrenia and healthy controls was 60.4±7.09 and 61.3±6.91 years, respectively. There was no significant difference between patients and healthy participants in gender. The ratio of males to females in patients with schizophrenia and healthy participants was 14 to 6.
A comparison of the results of volumetric analysis in patients with schizophrenia and controls revealed a statistically significant increase in cerebral ventricles volume and volume density, right ventricle volume and volume density, and left ventricle volume density (P<0.05). The total volume of lateral ventricles in schizophrenia patients and healthy subjects was 36.60±4.32 mm3 and 30.10±7.98 mm3, respectively. 
On the other hand, gray matter volume, white matter/gray matter volume, and total volume and volume density of each hippocampus were significantly lower in patients with schizophrenia than in healthy participants (P<0.05). 
However, there were no statistically significant changes in the brain’s total volume and volume of cerebral hemispheres, white matter, brain stem, cerebellum, and corpus callosum between the two groups (P˃0.05). Additional details of volumetric changes in different brain areas of each group are presented in Table 1.

4. Discussion
In the current study, a significant reduction was found in volumes of gray matter and hippocampus in patients with schizophrenia compared to that in controls. On the other hand, despite a decrease in the total volume of the brain and volume of cerebral hemispheres and white matter in patients with schizophrenia compared to those in healthy subjects, this volume reduction was not statistically significant. In addition, the volumes of lateral ventricles significantly increased in patients with schizophrenia compared to healthy participants. 
The findings of Chung et al. (2017) showed a substantial increase in lateral ventricle volume in patients with schizophrenia compared to controls. They also found a significant inverse association between ventricular volume expansion and gray matter thickness in individuals with clinically high-risk psychosis. They stated that lateral ventricular system enlargement is associated with significantly steep rates of cortical reduction (Chung et al., 2017). Another study conducted by Meduri et al. using morphometrical and morphological analyses of the lateral ventricles delineated that lateral ventricle total volume, right and left ventricle total volume and volume density, and left ventricle total volume in patients with schizophrenia were significantly higher than those in the control group (Meduri et al., 2010). Morphologically, the enlargement of the ventricular system is the most significant deficit in patients with schizophrenia compared to that in the controls (Shenton et al., 2001). Therefore, the results of our research team confirmed the previous findings about lateral ventricular enlargement in patients with schizophrenia. We speculate that increased ventricular volume in patients who have schizophrenia probably is one of the fundamental findings in brain MRI of these patients, which occurs in tandem with cortical and subcortical reduction of gray matter (basal ganglia) volume (Hashimoto et al., 2018; Meduri et al., 2010). Nevertheless, a reduction in the white matter volume of adjacent lateral ventricles (Price et al., 2006) and hyperdopaminergic situations with significant neurotoxic effects (Abi-Dargham, 2014) can affect the expansion of these spaces. 
The human hippocampus is one of the important brain structures with nearly 10 million glutamatergic and γ-amino butyric acid (GABA)-ergic neurons. It plays a substantial role in regulating emotion, affect, and cognitive functions. Based on neuroimaging and postmortem studies, the hippocampus is considered a key region in the early pathophysiology of schizophrenia (Konradi et al., 2011). Evidence suggests an abnormality in GABA-ergic inhibition of hippocampal pyramidal cells, impaired hippocampal interneurons, and a region-specific upregulation of GABA (A) receptor binding in patients with schizophrenia (Heidari et al., 2020). Falkai et al., in their stereological postmortem study, showed a significant reduction in glial cells and neuron numbers in subregions of the left side hippocampus in CA4 and dentate gyrus (DG), respectively, in patients with schizophrenia compared to those in healthy controls. In addition, they found that this cellular decline in the substructure of the hippocampus (CA4/DG) occurs along with the decreased volume of the total hippocampus (Falkai et al., 2016). Calvo et al. demonstrated that the total volume of right and left hippocampi in patients with schizophrenia was significantly less than in the controls. They concluded that the hippocampus volume loss in the early stages of the disease could increase patients’ vulnerability to severe mental illness (Calvo et al., 2018). Reduced volume of the hippocampus subregions (CA1 and CA4/DG) occurs even in the first episode of schizophrenia and is widespread more along with disease progression. Interestingly, volume loss in different subregions of the hippocampus due to the involvement of its anterior or posterior part is associated with the severity of symptoms (Nakahara et al., 2018). Our results regarding quantitative changes and reduced hippocampus volume in patients with schizophrenia were consistent with those reported in the above-mentioned studies. Therefore, it seems that the decline in hippocampus volume occurs in the first episode of schizophrenia, and a series of metabolic and structural factors including neuronal hyperactivation in particular GABA-ergic ones, levels of different neurotransmitters, decreased numbers of neurons and oligodendrocytes plays fundamental roles in this event (Falkai et al., 2016; Lieberman et al., 2018; Nakahara et al., 2018).
Despite our findings regarding the total volume of the brain and the cerebral hemispheres that did not show any statistically significant reductions in patients with schizophrenia compared to that in the controls, many previous studies on patients with schizophrenia conducted using neuroimaging indicated that these patients had a decreased cortical brain volume compared to that in healthy individuals (Haijma et al., 2012; Pantelis et al., 2003). This issue that the reduction in cortical brain volume in patients with schizophrenia occurs due to antipsychotic drug effects or neuropathological processes is still under debate (Ho et al., 2011). Vita et al. illustrated that antipsychotic drugs affected the cortical thickness and reduced the volume of the cortical brain (Vita et al., 2015). Another study conducted by Zhang et al. showed that cortical gray matter volume in patients with schizophrenia was significantly less than that in normal subjects. In addition, they claimed and supported that the reduction in cortical volumes of the brain in patients is associated with taking more antipsychotic medicines and related to the inflammatory basis (Zhang et al., 2016). Other experimental studies reported that antipsychotic drugs could lead to neurodegeneration and negative changes in the brain volume through induction of oxidative damage and reduction in the expression of growth factors (neurotrophins). These factors play critical roles in neuronal survival and differentiation in the brain (Pillai et al., 2007). However, our results related to the total volume of the brain and cerebral hemispheres did not show any significant difference between the two groups, but a significant reduction was observed in the volume of gray matter in patients with schizophrenia compared to that in the controls. This event is feasible due to volumetric changes in subcortical structures of the brain in patients with schizophrenia. Concerning the lack of reduced brain cortical volume in our study, we agree that various factors are involved in volumetric changes, including duration of disease, levels of inflammatory mediators, and exposure to antipsychotic drugs (Hashimoto et al., 2018; Zhang et al., 2016). Furthermore, reduction in the brain volume might be exaggerated in selected areas of the brain in some patients with schizophrenia due to disease heterogeneity (Kim et al., 2017; Zhang et al., 2016).
Kim et al. demonstrated a significant reduction in the volume of white matter in patients with schizophrenia compared to that in healthy subjects, especially in the superior frontal gyrus (SFG), superior temporal gyrus (STG), and inferior temporal gyrus (ITG). In addition, they found a negative correlation between the volume of white matter in STG and disease duration. Lastly, their results suggested that any abnormality and loss of white matter volume in STG could be related to the psychopathology of schizophrenia (Kim et al., 2017). Our results showed no statistically significant reduction in total volume and volume density of white matter in patients with schizophrenia compared to those in controls. In addition, we observed no significant difference in the volumes of the corpus callosum. Still, there was a significant increase in the volume density of the corpus callosum in patients with schizophrenia compared to controls. However, the results of other studies are contrary to changes in white matter and corpus callosum volumes in the present study (Arnone et al., 2008; de Moura et al., 2018; Del Re et al., 2016). The findings of Moura et al., which align with ours, showed no significant alternations in the corpus callosum volume in patients and healthy subjects. Their results showed that long-term exposure to antipsychotic drugs led to a greater increase in volume in some regions of the corpus callosum volume (posterior part) (de Moura et al., 2018). Amone et al., in their meta-analysis, explained that volume reduction in the corpus callosum region is more prominent in the first episode of schizophrenia, whereas patients with chronic schizophrenia showed relatively greater corpus callosum volume (Arnone et al., 2008). In addition to these results, Del Re et al. reported no substantial changes in the follow-up of patients with the first episode of schizophrenia compared to those in the controls (Del Re et al., 2016). Based on the aforementioned results, we proposed that volumetric changes in white matter and corpus callosum probably occur in specific brain areas and are associated with clinical severity symptoms. Variables affecting the volumes of white matter and corpus callosum in the brain are the duration of illness and chronic intake of antipsychotic medications. Another possible explanation for these findings (contrasting with those in different studies) could be the heterogeneity in subjects’ enrolment with different disease severity and the small sample size. Nevertheless, the role of compensatory processes for the structural and volumetric changes in different regions of the brain should not be forgotten (Heidari et al., 2017a; Heidari et al., 2017b). 
Some limitations we faced in this study were the small sample size, evaluation of variables such as duration of illness, number of episodes, and use of antipsychotic drugs. These limitations are suggested to be considered in designing future studies.

5. Conclusion
In conclusion, according to our findings, it seems that volumetric estimations on brain MRI-based stereological technique can be helpful for elucidation of structural changes, follow-up the treatment trends, and evaluating the therapeutic situation in schizophrenia patients. Other volumetric changes can vary in the different areas of the brain depending on the duration of the disease, antipsychotic therapy, and the inflammatory status of the patients. These changes might be linked to cognitive impairments and the severity of clinical symptoms in patients with schizophrenia. Finally, these findings can be beneficial in assessing antipsychotic treatments and dysfunctional connectivity in patients with schizophrenia. Furthermore, elucidation of the different pathways of various structural abnormalities related to schizophrenia is required to recognize and determine the role of discrete pathophysiological phenomena in mental illness development and progress. Further studies with larger sample sizes and more variables are recommended in this regard.

Ethical Considerations
Compliance with ethical guidelines

This study was approved by the Institutional Ethics Committee of the Zahedan University of Medical Sciences (Code: IR.ZAUMS.Rec.1390-2391).

This study was financially funded by Zahedan University of Medical Sciences (Grant No.: 2391).

Authors' contributions
Study design: Mansour Shakiba, Zahra Heidari and Hamidreza Mahmoudzadeh-Sagheb; Supervision: Zahra Heidari and Hamidreza Mahmoudzadeh-Sagheb; Data collection and selection of samples: Mansour Shakiba; Literature review and drafting the manuscript: Enam Alhagh Charkhat Gorgich; Data analysis: Enam Alhagh Charkhat Gorgich, Zahra Heidari and Hamidreza Mahmoudzadeh-Sagheb; Review, editing and final approval: All authors.

Conflict of interest
The authors declared no conflict of interest.

The authors appreciate all schizophrenia patients and controls who participated in the study and from Zohreh Rohani and Omid Dadras for their help in MRI data collection. We thank the Student’s Scientific Association of Anatomical Sciences of Iranshahr University of Medical Sciences.

Abi-Dargham, A. (2014). Schizophrenia: Overview and dopamine dysfunction. The Journal of Clinical Psychiatry, 75(11), e31. [DOI:10.4088/JCP.13078tx2c] [PMID]
Alper, F., Kantarci, M., Altunkaynak, E., Varoglu, A. O., Karaman, A., & Oral, E., et al. (2006). Quantitative magnetic resonance imaging of brainstem volumes, plaques, and surface area in the occipital regions of patients with multiple sclerosis. Acta Radiologica, 47(4), 413-418. [DOI:10.1080/02841850600596800] [PMID]
Arnone, D., McIntosh, A. M., Tan, G. M., & Ebmeier, K. P. (2008). Meta-analysis of magnetic resonance imaging studies of the corpus callosum in schizophrenia. Schizophrenia Research, 101(1-3), 124-132. [DOI:10.1016/j.schres.2008.01.005] [PMID]
Calvo, A., O’Hanlon, E., Coughlan, H., Kelleher, I., Clarke, M., & Cannon, M. (2018). O6. 1. Hippccampal volume in adolescents with persistent psychotic experiences: A longitudinal population-based MRI study. Schizophrenia Bulletin, 44(Suppl 1), S89. [DOI:10.1093/schbul/sby015.222] [PMCID]
Chung, Y., Haut, K. M., He, G., van Erp, T. G. M., McEwen, S., & Addington, J., et al. (2017). Ventricular enlargement and progressive reduction of cortical gray matter are linked in prodromal youth who develop psychosis. Schizophrenia Research, 189, 169-174. [DOI:10.1016/j.schres.2017.02.014] [PMID] [PMCID]
Ciumas, C., Montavont, A., & Ryvlin, P. (2008). Magnetic resonance imaging in clinical trials. Current Opinion in Neurology, 21(4), 431-436. [DOI:10.1097/WCO.0b013e3283056a3c] [PMID]
de Moura, M. T. M., Zanetti, M. V., Duran, F. L. S., Schaufelberger, M. S., Menezes, P. R., & Scazufca, M., et al. (2018). Corpus callosum volumes in the 5 years following the first-episode of schizophrenia: Effects of antipsychotics, chronicity and maturation. NeuroImage. Clinical, 18, 932–942. [DOI:10.1016/j.nicl.2018.03.015] [PMID] [PMCID]
Del Re, E. C., Konishi, J., Bouix, S., Blokland, G. A., Mesholam-Gately, R. I., & Goldstein, J., et al. (2016). Enlarged lateral ventricles inversely correlate with reduced corpus callosum central volume in first episode schizophrenia: Association with functional measures. Brain Imaging and Behavior, 10(4), 1264-1273. [DOI:10.1007/s11682-015-9493-2] [PMID] [PMCID]
Falkai, P., Malchow, B., Wetzestein, K., Nowastowski, V., Bernstein, H. G., & Steiner, J., et al. (2016). Decreased oligodendrocyte and neuron number in anterior hippocampal areas and the entire hippocampus in schizophrenia: A stereological postmortem study. Schizophrenia Bulletin, 42(suppl_1), S4-S12. [DOI:10.1093/schbul/sbv157] [PMID] [PMCID]
Haijma, S. V., Van Haren, N., Cahn, W., Koolschijn, P. C., Hulshoff Pol, H. E., & Kahn, R. S. (2013). Brain volumes in schizophrenia: A meta-analysis in over 18 000 subjects. Schizophrenia Bulletin, 39(5), 1129-1138. [DOI:10.1093/schbul/sbs118] [PMID] [PMCID]
Hashimoto, N., Ito, Y. M., Okada, N., Yamamori, H., Yasuda, Y., & Fujimoto, M., et al. (2017). The effect of duration of illness and antipsychotics on subcortical volumes in schizophrenia: Analysis of 778 subjects. NeuroImage. Clinical, 17, 563-569. [DOI:10.1016/j.nicl.2017.11.004] [PMID] [PMCID]
Heidari, Z., Mahmoudzadeh-Sagheb, H., Moghtaderi, A., Ramazanpour, N., & Gorgich, E. A. C. (2020). Structural changes in the brain of patients with relapsing-remitting multiple sclerosis compared to controls: A MRI-based stereological study. Irish Journal of Medical Science, 189(4), 1421–1427. [DOI:10.1007/s11845-020-02253-z] [PMID]
Heidari, Z., Mahmoudzadeh-Sagheb, H., Shakiba, M., & Alhagh Charkhat Gorgich, E. (2017). Stereological analysis of the brain in methamphetamine abusers compared to the controls. International Journal of High Risk Behaviors and Addiction, 6(4), e63201. [DOI:10.5812/ijhrba.63201]
Heidari, Z., Moghtaderi, A., Mahmoudzadeh-Sagheb, H., & Gorgich, E. A. C. (2017). Stereological evaluation of the brains in patients with parkinson’s disease compared to controls. Revista Romana de Medicina de Laborator, 25(3), 265-274.[DOI:10.1515/rrlm-2017-0010]
Ho, B. C., Andreasen, N. C., Ziebell, S., Pierson, R., & Magnotta, V. (2011). Long-term antipsychotic treatment and brain volumes: A longitudinal study of first-episode schizophrenia. Archives of General Psychiatry, 68(2), 128-137. [DOI:10.1001/archgenpsychiatry.2010.199] [PMID] [PMCID]
IInsel T. R. (2010). Rethinking schizophrenia. Nature, 468(7321), 187-193. [DOI:10.1038/nature09552] [PMID]
Jaaro-Peled, H., Ayhan, Y., Pletnikov, M. V., & Sawa, A. (2010). Review of pathological hallmarks of schizophrenia: Comparison of genetic models with patients and nongenetic models. Schizophrenia Bulletin, 36(2), 301-313. [DOI:10.1093/schbul/sbp133] [PMID] [PMCID]
Jaaro-Peled, H., Hayashi-Takagi, A., Seshadri, S., Kamiya, A., Brandon, N. J., & Sawa, A. (2009). Neurodevelopmental mechanisms of schizophrenia: understanding disturbed postnatal brain maturation through neuregulin-1-ErbB4 and DISC1. Trends in Neurosciences, 32(9), 485-495. [DOI:10.1016/j.tins.2009.05.007] [PMID] [PMCID]
Kim, G. W., Kim, Y. H., & Jeong, G. W. (2017). Whole brain volume changes and its correlation with clinical symptom severity in patients with schizophrenia: A DARTEL-based VBM study. PloS One, 12(5), e0177251. [DOI:10.1371/journal.pone.0177251] [PMID] [PMCID]
Kim, G. W., Yang, J. C., & Jeong, G. W. (2015). Emotional effect on cognitive control in implicit memory tasks in patients with schizophrenia. NeuroReport, 26(11), 647-655. [DOI:10.1097/WNR.0000000000000405] [PMID]
Kipp, M., Kiessling, M. C., Hochstrasser, T., Roggenkamp, C., & Schmitz, C. (2017). Design-based stereology for evaluation of histological parameters. Journal of Molecular Neuroscience, 61(3), 325-342. [DOI:10.1007/s12031-016-0858-9] [PMID]
Konradi, C., Yang, C. K., Zimmerman, E. I., Lohmann, K. M., Gresch, P., & Pantazopoulos, H., et al. (2011). Hippocampal interneurons are abnormal in schizophrenia. Schizophrenia Research, 131(1-3), 165-173. [DOI:10.1016/j.schres.2011.06.007] [PMID] [PMCID]
Lieberman, J. A., Girgis, R. R., Brucato, G., Moore, H., Provenzano, F., & Kegeles, L., et al. (2018). Hippocampal dysfunction in the pathophysiology of schizophrenia: A selective review and hypothesis for early detection and intervention. Molecular Psychiatry, 23(8), 1764-1772. [DOI:10.1038/mp.2017.249] [PMID] [PMCID]
Meduri, M., Bramanti, P., Ielitro, G., Favaloro, A., Milardi, D., & Cutroneo, G., et al. (2010). Morphometrical and morphological analysis of lateral ventricles in schizophrenia patients versus healthy controls. Psychiatry Research, 183(1), 52-58. [DOI:10.1016/j.pscychresns.2010.01.014] [PMID]
Meyer, U. (2013). Developmental neuroinflammation and schizophrenia. Progress in Neuro-Psychopharmacology and Biological Psychiatry, 42, 20-34. [DOI:10.1016/j.pnpbp.2011.11.003] [PMID]
Murray, R. M., & Lewis, S. W. (1987). Is schizophrenia a neurodevelopmental disorder? British Medical Journal (Clinical Research Ed.), 295(6600), 681-682. [DOI:10.1136/bmj.295.6600.681] [PMID] [PMCID]
Nakahara, S., Matsumoto, M., & van Erp, T. G. M. (2018). Hippocampal subregion abnormalities in schizophrenia: A systematic review of structural and physiological imaging studies. Neuropsychopharmacology Reports, 38(4), 156-166. [DOI:10.1002/npr2.12031] [PMID] [PMCID]
Pakkenberg, B., Scheel-Krüger, J., & Kristiansen, L. V. (2009). Schizophrenia; from structure to function with special focus on the mediodorsal thalamic prefrontal loop. Acta Psychiatrica Scandinavica, 120(5), 345-354. [DOI:10.1111/j.1600-0447.2009.01447.x] [PMID]
Pantelis, C., Velakoulis, D., McGorry, P. D., Wood, S. J., Suckling, J., & Phillips, L. J., et al. (2003). Neuroanatomical abnormalities before and after onset of psychosis: A cross-sectional and longitudinal MRI comparison. Lancet, 361(9354), 281-288. [DOI:10.1016/S0140-6736(03)12323-9] [PMID]
Pillai, A., Parikh, V., Terry, A. V., Jr, & Mahadik, S. P. (2007). Long-term antipsychotic treatments and crossover studies in rats: Differential effects of typical and atypical agents on the expression of antioxidant enzymes and membrane lipid peroxidation in rat brain. Journal of Psychiatric Research, 41(5), 372-386. [DOI:10.1016/j.jpsychires.2006.01.011] [PMID]
Price, G., Cercignani, M., Bagary, M. S., Barnes, T. R., Barker, G. J., & Joyce, E. M., et al. (2006). A volumetric MRI and magnetization transfer imaging follow-up study of patients with first-episode schizophrenia. Schizophrenia Research, 87(1-3), 100-108. [DOI:10.1016/j.schres.2006.06.019] [PMID]
Roussos, P., & Haroutunian, V. (2014). Schizophrenia: Susceptibility genes and oligodendroglial and myelin related abnormalities. Frontiers in Cellular Neuroscience, 8, 5. [DOI:10.3389/fncel.2014.00005] [PMID] [PMCID]
Shenton, M. E., Dickey, C. C., Frumin, M., & McCarley, R. W. (2001). A review of MRI findings in schizophrenia. Schizophrenia Research, 49(1-2), 1-52. [DOI:10.1016/S0920-9964(01)00163-3] [PMID]
Tandon, R., Nasrallah, H. A., & Keshavan, M. S. (2009). Schizophrenia, “just the facts” 4. Clinical features and conceptualization. Schizophrenia Research, 110(1-3), 1-23. [DOI:10.1016/j.schres.2009.03.005] [PMID]
Tepest, R., Schwarzbach, C. J., Krug, B., Klosterkötter, J., Ruhrmann, S., & Vogeley, K. (2013). Morphometry of structural disconnectivity indicators in subjects at risk and in age-matched patients with schizophrenia. European Archives of Psychiatry and Clinical Neuroscience, 263(1), 15-24. [DOI:10.1007/s00406-012-0343-6] [PMID]
van Os, J., & Kapur, S. (2009). Schizophrenia. Lancet (London, England), 374(9690), 635–645. [DOI:10.1016/S0140-6736(09)60995-8] [PMID]
Vita, A., De Peri, L., Deste, G., Barlati, S., & Sacchetti, E. (2015). The effect of antipsychotic treatment on cortical gray matter changes in schizophrenia: Does the class matter? A meta-analysis and meta-regression of longitudinal magnetic resonance imaging studies. Biological Psychiatry, 78(6), 403-412. [DOI:10.1016/j.biopsych.2015.02.008] [PMID]
Zhang, Y., Catts, V. S., Sheedy, D., McCrossin, T., Kril, J. J., & Shannon Weickert, C. (2016). Cortical grey matter volume reduction in people with schizophrenia is associated with neuro-inflammation. Translational Psychiatry, 6(12), e982. [DOI:10.1038/tp.2016.238] [PMID] [PMCID]
Type of Study: Original | Subject: Clinical Neuroscience
Received: 2021/06/16 | Accepted: 2021/08/7 | Published: 2023/05/8

Add your comments about this article : Your username or Email:

Send email to the article author

Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

© 2023 CC BY-NC 4.0 | Basic and Clinical Neuroscience

Designed & Developed by : Yektaweb