Huaiqiang Sun

Two Patterns of White Matter Abnormalities in Medication-Naive Patients With First-Episode Schizophrenia Revealed by Diffusion Tensor Imaging and Cluster Analysis.

IMPORTANCE Accumulating evidence supports the hypothesis that cerebral white matter abnormalities are involved in the pathophysiology of schizophrenia; however, findings from in vivo neuroimaging studies have been inconsistent. Besides confounding factors, including age, illness duration, and medication effects, an additional cause for the inconsistent results may be heterogeneity in the nature of white matter alterations associated with the disorder. OBJECTIVE To investigate whether different patterns of white matter abnormalities exist in a large cohort of medication-naive patients with first-episode schizophrenia and the relationship between such patterns and clinical parameters. DESIGN, SETTING, AND PARTICIPANTS A cross-sectional diffusion tensor imaging study of 113 medication-naive patients with first-episode schizophrenia and 110 demographically matched healthy control individuals. The study was conducted in the mental health center of West China Hospital, Sichuan University, Chengdu, China, from January 2006 to June 2014. MAIN OUTCOMES AND MEASURES The patterns of white matter abnormalities revealed by tract-specific analysis in conjunction with hierarchical clustering. RESULTS With diffusion features extracted from 18 fiber tracts, cluster analysis revealed 2 patterns of abnormalities. One pattern (42.5% of patient sample) showed widespread white matter abnormalities compared with matched healthy control individuals, while another pattern (57.5% of patient sample) only showed circumscribed regional white matter abnormalities, mainly in the left superior longitudinal fasciculus. Patients in these subgroups did not differ in demographic features; however, negative symptoms were more severe in patients with widespread white matter abnormalities. CONCLUSIONS AND RELEVANCE Two distinct patterns of white matter abnormalities exist at the early phase of schizophrenia, with those having global abnormalities experiencing more severe negative symptoms. The finding that distinct subgroups of patients with schizophrenia have different forms of white matter pathology may reflect qualitatively distinct genetic influences or neurodevelopmental alterations and thus represents a promising strategy for resolving neurobiological heterogeneity in the schizophrenia syndrome.

Multivariate pattern analysis of obsessive–compulsive disorder using structural neuroanatomy

Magnetic resonance imaging (MRI) studies have revealed brain structural abnormalities in obsessive-compulsive disorder (OCD) patients, involving both gray matter (GM) and white matter (WM). However, the results of previous publications were based on average differences between groups, which limited their usages in clinical practice. Therefore, the aim of this study was to examine whether the application of multivariate pattern analysis (MVPA) to high-dimensional structural images would allow accurate discrimination between OCD patients and healthy control subjects (HCS). High-resolution T1-weighted images were acquired from 33 OCD patients and 33 demographically matched HCS in a 3.0 T scanner. Differences in GM and WM volume between OCD and HCS were examined using two types of well-established MVPA techniques: support vector machine (SVM) and Gaussian process classifier (GPC). We also drew a receiver operating characteristic (ROC) curve to evaluate the performance of each classifier. The classification accuracies for both classifiers using GM and WM anatomy were all above 75%. The highest classification accuracy (81.82%, P<0.001) was achieved with the SVM classifier using WM information. Regional brain anomalies with high discriminative power were based on three distributed networks including the fronto-striatal circuit, the temporo-parieto-occipital junction and the cerebellum. Our study illustrated that both GM and WM anatomical features may be useful in differentiating OCD patients from HCS. WM volume using the SVM approach showed the highest accuracy in our population for revealing group differences, which suggested its potential diagnostic role in detecting highly enriched OCD patients at the level of the individual.

Psychoradiologic Utility of MR Imaging for Diagnosis of Attention Deficit Hyperactivity Disorder: A Radiomics Analysis

Purpose To identify cerebral radiomic features related to diagnosis and subtyping of attention deficit hyperactivity disorder (ADHD) and to build and evaluate classification models for ADHD diagnosis and subtyping on the basis of the identified features. Materials and Methods A consecutive cohort of 83 age- and sex-matched children with newly diagnosed and never-treated ADHD (mean age 10.83 years ± 2.30; range, 7-14 years; 71 boys, 40 with ADHD-inattentive [ADHD-I] and 43 with ADHD-combined [ADHD-C, or inattentive and hyperactive]) and 87 healthy control subjects (mean age, 11.21 years ± 2.51; range, 7-15 years; 72 boys) underwent anatomic and diffusion-tensor magnetic resonance (MR) imaging. Features representing the shape properties of gray matter and diffusion properties of white matter were extracted for each participant. The initial feature set was input into an all-relevant feature selection procedure within cross-validation loops to identify features with significant discriminative power for diagnosis and subtyping. Random forest classifiers were constructed and evaluated on the basis of identified features. Results No overall difference was found between children with ADHD and control subjects in total brain volume (1069830.00 mm3 ± 90743.36 vs 1079 213.00 mm3 ± 92742.25, respectively; P = .51) or total gray and white matter volume (611978.10 mm3 ± 51622.81 vs 616960.20 mm3 ± 51872.93, respectively; P = .53; 413532.00 mm3 ± 41 114.33 vs 418173.60 mm3 ± 42395.48, respectively; P = .47). The mean classification accuracy achieved with classifiers to discriminate patients with ADHD from control subjects was 73.7%. Alteration in cortical shape in the left temporal lobe, bilateral cuneus, and regions around the left central sulcus contributed significantly to group discrimination. The mean classification accuracy with classifiers to discriminate ADHD-I from ADHD-C was 80.1%, with significant discriminating features located in the default mode network and insular cortex. Conclusion The results of this study provide preliminary evidence that cerebral morphometric alterations can allow discrimination between patients with ADHD and control subjects and also between the most common ADHD subtypes. By identifying features relevant for diagnosis and subtyping, these findings may advance the understanding of neurodevelopmental alterations related to ADHD.

Magnetization Transfer Imaging of Treatment-resistant Depression

Purpose To detect biophysical abnormalities in patients with postmedication treatment-resistant depression (TRD) with magnetization transfer imaging. Materials and Methods This study was approved by the local ethics committee, and written informed consent was obtained from all participants. Participants included 69 patients with major depressive disorder (MDD) (30 with TRD; 39 with non-TRD) and 41 healthy control subjects. Age and sex were examined with one-way analysis of variance and χ2 tests and were well matched among the three groups. Whole-brain voxel-based analysis was used to compare the magnetization transfer ratio (MTR) between the three groups. Regional MTR values were used to analyze the correlations with symptom severity and illness duration. Results MTR differences were identified in the bilateral precentral gyrus, left cerebellum posterior lobe, left middle occipital lobe, left precuneus, and left temporal lobe among the three groups. Relative to patients with non-TRD, those with TRD had significantly lower MTR in the task-positive network regions, including the bilateral precentral gyrus and left middle occipital lobe, and had lower MTR in the default mode network regions, including the left precuneus and left temporal lobe. Regional MTRs were not associated with symptom severity or illness duration. Conclusion These results suggest that treatment resistance in patients with MDD may be mediated by macromolecular abnormalities in the task-positive and default mode functional networks.

Support vector machine-based classification of first episode drug-naïve schizophrenia patients and healthy controls using structural MRI

Although regional brain deficits have been demonstrated in schizophrenia patients by structural MRI studies, one important question that remains largely unanswered is whether the complex and subtle deficits revealed by MRI could be used as objective biomarkers to discriminate patients from healthy controls individually. To address this question, a total of 326 right-handed participants were recruited, including 163 drug-naïve first-episode schizophrenia (FES) patients and 163 demographically matched healthy controls. High-resolution anatomic data were acquired from all subjects and processed via Freesurfer software to obtain cortical thickness and surface area measurements. Subsequently, the Support Vector Machine (SVM) was used to explore the potential utility for cortical thickness and surface area measurements in the differentiation of individual patients and healthy controls. The accuracy of correct classification of patients and controls was 85.0% (specificity 87.0%, sensitivity 83.0%) for surface area and 81.8% (specificity 85.0%, sensitivity 76.9%) for cortical thickness (p<0.001 after permutation testing). Regions contributing to classification accuracy mainly included the gray matter in default mode, central executive, salience, and visual networks. Current findings, in a sample of never-treated FES patients, suggest that the patterns of illness-related gray matter changes has potential as a biomarker for identifying structural brain alterations in individuals with schizophrenia. Future prospective studies are needed to evaluate the utility of imaging biomarkers for research and potentially for clinical purpose.

Altered brain network topology in left-behind children: A resting-state functional magnetic resonance imaging study

Whether a lack of direct parental care affects brain function in children is an important question, particularly in developing countries where hundreds of millions of children are left behind when their parents migrate for economic or political reasons. In this study, we investigated changes in the topological architectures of brain functional networks in left-behind children (LBC). Resting-state functional magnetic resonance imaging data were obtained from 26 LBC and 21 children living within their nuclear family (non-LBC). LBC showed a significant increase in the normalized characteristic path length (λ), suggesting a decrease in efficiency in information access, and altered nodal centralities in the fronto-limbic regions and motor and sensory systems. Moreover, a decreased nodal degree and the nodal betweenness of the right rectus gyrus were positively correlated with annual family income. The present study provides the first empirical evidence that suggests that a lack of direct parental care could affect brain functional development in children, particularly involving emotional networks.

Abnormal metabolite concentrations and amygdala volume in patients with recent-onset posttraumatic stress disorder

BACKGROUND Previous psychoradiological studies of posttraumatic stress disorder (PTSD) were mainly of patients at a chronic stage, focusing on brain regions outside the amygdala. The goals of this study were to investigate the early biochemical and structural changes of anterior cingulate cortex (ACC) and amygdala in patients with PTSD and to explore their relationships. METHODS Seventy-eight drug-naïve PTSD subjects and 71 non-PTSD age- and sex-matched control subjects were enrolled, all of whom had suffered the same earthquake about one year before. Single-voxel proton magnetic resonance spectroscopy (1H-MRS) was performed and absolute metabolite concentrations in ACC and bilateral amygdalae were estimated with LCModel. Bilateral amygdalae were manually outlined and their volumes were calculated and corrected for the total intracranial volume. RESULTS The PTSD group showed significantly increased N-acetylaspartate (NAA) concentration in the ACC, increased creatine (Cr) concentration in the left amygdala, and increased myo-inositol (mI) concentration in the right amygdala, compared to non-PTSD controls. The NAA concentration in ACC was negatively correlated with the time since trauma. The PTSD group showed significantly decreased volumes of bilateral amygdalae compared to non-PTSD controls, but amygdala volumes were not correlated with metabolite concentrations. LIMITATIONS Longitudinal studies are needed to explore the metabolic and structural changes of PTSD at different stages. The volume of ACC was not measured. CONCLUSIONS This concurrent increase in some metabolite concentrations and decrease of amygdala volumes may represent a pattern of biochemical and morphological changes in recent-onset PTSD which is different from that reported in chronic PTSD.

White Matter Abnormalities in Never-Treated Patients With Long-Term Schizophrenia

OBJECTIVE: This study tested for differences of white matter integrity between treated and never-treated long-term schizophrenia patients, matched on illness duration, and for differential changes in relation to age in these two groups relative to healthy comparison subjects. METHOD: This cross-sectional diffusion tensor imaging study included 31 never-treated and 46 matched antipsychotic-treated patients with long-term schizophrenia and 58 healthy comparison subjects. Fractional anisotropy measures of white matter tracts were extracted and compared. Linear regression analysis was used to explore the association between age and fractional anisotropy among the three groups. RESULTS: Fractional anisotropy significantly differed among the three groups in 14 of 20 white matter tracts defined in the Johns Hopkins University white matter template. Never-treated patients displayed greater reduction of fractional anisotropy than antipsychotic-treated patients in the left anterior thalamic radiation, the left cingulum-hippocampus pathway, the splenium and genu of the corpus callosum, and the left superior longitudinal fasciculus, and greater fractional anisotropy in the right uncinate fasciculus. Both patient groups showed multiple reductions relative to healthy comparison subjects. Never-treated patients showed an accelerated and clinically relevant age-related reduction of fractional anisotropy in the genu of the corpus callosum. CONCLUSIONS: These psychoradiological findings provide insight into the regional distribution of white matter deficits in the years after illness onset in long-term schizophrenia. Findings of greater impairments in never-treated patients, and a greater age-related reduction in the genu of the corpus callosum in these patients, suggest that long-term antipsychotic treatment does not adversely affect white matter tracts over the longer-term course of illness and may confer benefits.