Heterogeneity of Structural Brain Changes in Subtypes of Schizophrenia Revealed Using Magnetic Resonance Imaging Pattern Analysis

Background:

Schizophrenia is a multifaceted mental disorder characterized by cognitive, perceptual, and affective symptom dimensions. This heterogeneity at the phenomenological level may be subserved by complex and heterogeneous patterns of structural abnormalities. Thus, delineating such patterns may improve the insight into the variability of disease and facilitate future magnetic resonance imaging-based diagnosis.

Methods:

We aimed to identify structurally complex signatures that directly differentiate patients with predominantly negative (pNEG), positive (pPOS), and disorganized (pDIS) symptoms using Optimally-Discriminative Voxel-Based Analysis (ODVBA). ODVBA is a new analytical framework for group analysis, which showed to have superior sensitivity and specificity over conventional voxel-based morphometric approaches, thus facilitating the identification of subtle neuroanatomical signatures delineating different subgroups.

Results:

pPOS were characterized by pronounced gray matter (GM) volume reductions in the ventromedial prefrontal cortex (vmPFC), which herein is defined to include the orbitofrontal cortex, and in occipitotemporal GM and parts of the lingual gyrus. pNEG was found to have vmPFC reduction but to a lesser degree than pPOS and with a relative sparing of the more medial vmPFC regions, compared to pDIS; it also had significantly less cerebellar GM. pDIS showed relatively highest GM volume preservation among three subtypes.

Conclusions:

Although a common prefronto-perisylvian GM reduction pattern was present at the whole-group level, marked morphometric differences emerged between the three subgroups, including reduced cerebellar GM in pNEG and reduced vmPFC and occipitotemporal GM in pPOS. Besides deepening our insight into the neurobiological underpinnings of clinical heterogeneity, these results also identify important imaging biomarkers that may aid patient stratification.Key words: volume reduction, ODVBA, voxel-based morphometry, patient stratification     

Magnetic Resonance Spectroscopy

Magnetic resonance spectroscopy (MRS) is noninvasive and may be readily combined with magnetic resonance imaging (MRI). Attention has focussed on proton (¹H) and phosphorus (³¹P) MRS, and studies have been undertaken by using single voxels or many voxels simultaneously (chemical-shift imaging, magnetic resonance spectroscopic imaging). The latter is more difficult and prone to artefact but potentially yields significantly more information. ¹H MRS has principally yielded data on concentrations of N-acetyl aspartate (NAA), choline, creatine, and phosphocreatine. NAA is located primarily within neurons, and reduction of the ratio of NAA to choline, creatine, and phosphocreatine is a marker of neu-ronal loss and dysfunction. This technique may be useful as a noninvasive tool for localizing epileptogenic foci, but its role requires further evaluation. As with all functional imaging methods, coregistration with high-quality MRI is essential for interpreting data. ¹H MRS can be used also to estimate cerebral concentrations of several neurotrans-mitters: glutamate, glutamine, and γ-aminobutyric acid (GABA). This may prove useful for characterizing the neurometabolic profiles of patients with different epilepsy syndromes and for evaluating the effects of medical and surgical treatments. ³¹P MRS can detect adenosine tri-phosphate, phosphodiesters, phosphomonoesters, phosphocreatine, and inorganic phosphate, and estimate intra-cerebral pH. Abnormalities that have been associated with epileptogenic brain areas include increased inorganic phosphate, reduced phosphomonoesters, and increased pH. Only small numbers of patients have been studied, however, so that conclusions are not definitive, and the clinical role of this technique is not yet established.     

Transcranial Magnetic Stimulation for Schizophrenia

People with schizophrenia typically experience auditory hallucinations or delusions during acute episodes. Although effective drug treatments are available, many have intractable symptoms that do not recover between acute episodes. One proposed alternative to drug treatments is transcranial magnetic stimulation (TMS). To date, many research trials to assess effectiveness of TMS for people with symptoms of schizophrenia have been conducted worldwide. However, there is a lack of consensus on whether TMS should be recommended to be adopted in routine clinical practice. We conducted a systematic review of the literature for all relevant randomized controlled trials (RCTs) comparing TMS with sham or standard treatment. Forty-one trials (1473 participants) survived eligibility criteria and had extractable data. We found significant differences in favor of temporoparietal TMS compared with sham TMS for global state (7 RCTs, n = 224, MD: -0.5, 95% CI: -0.76 to -0.23) and for positive symptoms measured on the Positive and Negative Syndrome Scale (5 RCTs, n = 127, MD: -6.09, 95% CI: -10.95 to -1.22). However, we also found that the quality of trial reporting was frequently suboptimal and the risks of bias were strong or unascertainable for many trial aspects; this led to many results being graded as very low-quality evidence. On that basis, we were unable to definitively support or refute the routine use of TMS in clinical practice. Future definitive trials of TMS with rigorous processes and high-quality reporting are needed.Key words: schizophrenia, transcranial magnetic stimulation, auditory hallucinations     

Neuropsychological Testing and Structural Magnetic Resonance Imaging as Diagnostic Biomarkers Early in the Course of Schizophrenia and Related Psychoses

Making an accurate diagnosis of schizophrenia and related psychoses early in the course of the disease is important for initiating treatment and counseling patients and families. In this study, we developed classification models for early disease diagnosis using structural MRI (sMRI) and neuropsychological (NP) testing. We used sMRI measurements and NP test results from 28 patients with recent-onset schizophrenia and 47 healthy subjects, drawn from the larger sample of the Mind Clinical Imaging Consortium. We developed diagnostic models based on Linear Discriminant Analysis (LDA) following two approaches; namely, (a) stepwise (STP) LDA on the original measurements, and (b) LDA on variables created through Principal Component Analysis (PCA) and selected using the Humphrey-Ilgen parallel analysis. Error estimation of the modeling algorithms was evaluated by leave-one-out external cross-validation. These analyses were performed on sMRI and NP variables separately and in combination. The following classification accuracy was obtained for different variables and modeling algorithms. sMRI only: (a) STP-LDA: 64.3% sensitivity and 76.6% specificity, (b) PCA-LDA: 67.9% sensitivity and 72.3% specificity. NP only: (a) STP-LDA: 71.4% sensitivity and 80.9% specificity, (b) PCA-LDA: 78.5% sensitivity and 91.5% specificity. Combined sMRI-NP: (a) STP-LDA: 64.3% sensitivity and 83.0% specificity, (b) PCA-LDA: 89.3% sensitivity and 93.6% specificity. (i) Maximal diagnostic accuracy was achieved by combining sMRI and NP variables. (ii) NP variables were more informative than sMRI, indicating that cognitive deficits can be detected earlier than volumetric structural abnormalities. (iii) PCA-LDA yielded more accurate classification than STP-LDA. As these sMRI and NP tests are widely available, they can increase accuracy of early intervention strategies and possibly be used in evaluating treatment response.