Introduction
Schizophrenia is a severe psychiatric disease with significant social consequences and has been the subject of decades of neuroimaging study, yet little is known about its neurobiology.1 Genetic and histopathological investigations have shown a connection between white matter (WM) genetic variations and genes associated with the risk of schizophrenia.2 3 Schizophrenia symptoms are thought to be the result of a disruption of the interhemispheric communication.4 WM investigations using MRI have supported the interruption theory, showing that the corpus callosum (CC) of patients with schizophrenia (including first-episode schizophrenia) is substantially smaller than that of healthy controls (HC).5–7 Despite significant discrepancies in the findings, many investigations using a variety of imaging methods have revealed important details regarding the pathophysiology of schizophrenia. The advent of MRI aided in the identification of the neuroanatomical origins of schizophrenic illness.8 Nonetheless, the disease’s heterogeneity and the categorisation of all subjects with a diagnosis of ‘schizophrenia’ have most likely served as a barrier to this invention. Some neuroimaging studies have been aimed at clinical subtypes of schizophrenia.9 10 Extensive neuroanatomical, neurobiological and neuropsychological studies have been conducted to delineate possible subgroups of diverse groups of schizophrenia characterised by symptom domain predominance. Carpenter et al 11 used the term ‘deficit syndrome’ (DS) to refer to the presence of main and persistent negative symptoms (a deficit in goal-directed or pleasurable behaviour, voice and non-verbal expression). In patients with DS, impaired cognition, longer course, poorer functional outcomes, lower life quality, and compromised educational and professional activity have all been identified.12 13 In a diverse population of patients with schizophrenia, the prevalence of DS is about 15% in first-episode psychosis and 25%–30% overall.14 Numerous investigations with limited sample sizes and participant numbers tried to scan the neurostructure of patients with DS and compared the results with those obtained from non-deficit syndrome (NDS) imaging studies.15 They found that individuals with DS exhibited lower fractional anisotropy (FA) values in many brain regions compared with those with NDS. This may imply a larger dissociation of the WM in DS.9 16–20 Voineskos et al 17 found that individuals with first-episode psychosis who also have clinical indications of DS had a greater impairment in the WM tract. This demonstrates that disruptions of the interhemispheric communication may contribute to the development of clinical symptoms in DS. Disruption of WM in the superior longitudinal fasciculus and the uncinate fasciculus indicates a disconnection between the temporal, parietal and limbic cortices.9 16 Spalletta et al 20 and Lei et al 18 both found that the FA values decreased in the CC. Meanwhile, it has been shown that the FA values in the CC splenium and the body have reduced.17 19 This indicates that comprehending the psychopathology of DS requires a thorough knowledge of the brain’s interhemispheric regions.
Although callosal fibres extend extensively into each cerebral hemisphere, the callosal mid-sagittal border of the cross section has received the greatest attention, both because of the documented correlations between fibre number and callosal area and because it is easier to identify, depict and analyse.21 The location of the WM impairment may have psychopathological implications; therefore, we chose to concentrate on determining whether geometric morphometric disturbances in particular areas of the CC may be implicated in the pathophysiology of DS.
Geometric morphometrics is a term that refers to applications of statistical shape analysis based on landmarks.22 Geometric morphometrics is a relatively new paradigm for quantitatively analysing the variability and covariance of the forms of biological things.23 24 Coordinate-based techniques are also known as geometric morphometrics because they preserve all geometric information throughout the data gathering, processing and visualisation processes.25
Statistical shape or image analysis, which is used to evaluate two-dimensional or three-dimensional shape data, is gaining increasing popularity in medicine and biology. The principal cause of the increasing use of statistical shape analysis in medicine is technological advances in imaging and a desire to understand the impact of illnesses and environmental variables on organ or organism structure.25
To our knowledge, this is the first study to investigate the topographic distribution of the CC in patients with schizophrenia using cranial MRI in order to discover whether the form of the CC varies between schizophrenia and its subgroups (DS and NDS) as well as between HCs.