Neuroanatomical comparison of treatment-resistant and treatment-responsive schizophrenia patients using the cloud-based brain magnetic resonance image segmentation and parcellation system: An MRIcloud study
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引用次数: 0
Abstract
Recent developments in neuroimaging have improved our understanding of the biological mechanisms underlying schizophrenia. However, neuroimaging findings in treatment-resistant schizophrenia (TRS) remain unclear. In the present study, we aimed to explore potential neuroanatomical regions that may be associated with treatment resistance in schizophrenia patients by comparing neuroanatomical regions of TRS and non-TRS patients using the MRICloud method. A total of 33 schizophrenia patients (meeting DSM 5 diagnostic criteria for schizophrenia) were included in the study. Patients were dichotomized into TRS (n = 18) and non-TRS (n = 15) groups, and all patients underwent MRI. Neuroanatomical regions of TRS and non-TRS patients were compared using the MRICloud method. Disease severity was measured using the Positive and Negative Syndrome Scale (PANSS). Interestingly, a statistically significant greater left Corpus Collosum (CC) thickness was found in TRS patients compared to non-TRS patients. It is clear that further studies comparing TRS patients with non-TRS patients are needed, and these studies should focus on the circuits in the corpus callosum that are thought to play a role in treatment resistance. Further longitudinal studies are also needed to complement the cross-sectional studies, using a multimodal imaging approach in the patients with clearly defined TRS criteria.
期刊介绍:
The Neuroimaging section of Psychiatry Research publishes manuscripts on positron emission tomography, magnetic resonance imaging, computerized electroencephalographic topography, regional cerebral blood flow, computed tomography, magnetoencephalography, autoradiography, post-mortem regional analyses, and other imaging techniques. Reports concerning results in psychiatric disorders, dementias, and the effects of behaviorial tasks and pharmacological treatments are featured. We also invite manuscripts on the methods of obtaining images and computer processing of the images themselves. Selected case reports are also published.