Objectives: This study aimed to develop a machine learning model for diagnosing schizophrenia (SZ) and bipolar disorder (BD) based on diffusion tensor imaging (DTI) data. Methods: We used 3T-magnetic resonance imaging to examine SZ, BD, healthy control (HC) subjects (aged 20-50 years, n=65 in each group). Applying Support Vector Machine (SVM) to fractional anisotropy (FA) values, we built classification models of SZ and HC, BD and HC, and SZ and BD. Features of white matter (WM) tracts were selected through recursive feature elimination, and 5-fold cross validation was performed. Results: The SVM models classified SZ and BD from HC with a mean accuracy of 83.5% and 75.4%, respectively. The SZ-BD classification model archived 75.0% accuracy. These classification models used FA values in 15-18 WM tracts as features, including the retrolenticular part of the internal capsule, superior corona radiata, cingulum, and superior fronto-occipital fasciculus. Conclusions This study presented a preliminary machine learning model to diagnose SZ and BD based on DTI data. Our findings also suggest that there might be a specific pattern of abnormalities in WM integrity that can differentiate the two psychotic disorders.

Background: Mandibular condyle remodeling and displacement are post-orthognathic surgery concerns that can potentially lead to occlusal issues after bilateral sagittal split ramus osteotomy. This retrospective study examined the relationship between condylar volume changes and position alterations after surgery in patients with skeletal class II and III malocclusions using cone-beam CT. Methods: The study included 16 patients (6 with Class II malocclusion, 10 with Class III malocclusion) who underwent bilateral sagittal split ramus osteotomy at Chonnam National University Hospital. Cone-beam CT data were collected at three specific time points: before surgery, immediately after surgery, and approximately 6 months post-surgery.Mandibular movement was measured using InVivoDental 5.4.6. ITK-SNAP 3.8.0 was used to assessed condylar volume changes post-surgery. Condyle positions were evaluated in four parts with RadiAnt DICOM Viewer 4.6.9. Statistical analyses were performed using the SPSS version 23. Results: Considering both Class II and III malocclusion, a 2.91% volume reduction was noted immediately and at 6 months after surgery. Both Class II and III cases demonstrated a decrease in superior joint space by -0.59 mm and medial joint space by -1.09 mm. No significant correlation was found between this process and condylar volume change. Conclusions The mandibular condyle volume decreased, and superior-medial movement of the condyle was detected in patients with Class II and III malocclusion immediately and at 6 months after surgery with no volumeposition correlation.

This study aimed to present the prognosis after minor acute ischemic stroke (AIS) or transient ischemic attack (TIA), using a definition of subsequent stroke in accordance with recent clinical trials. In total, 9,506 patients with minor AIS (National Institutes of Health Stroke Scale ≤ 5) or high-risk TIA (acute lesions or ≥ 50% cerebral artery steno-occlusion) admitted between November 2010 and October 2013 were included. The primary outcome was the composite of stroke (progression of initial event or a subsequent event) and all-cause mortality. The cumulative incidence of stroke or death was 11.2% at 1 month, 13.3% at 3 months and 16.7% at 1 year. Incidence rate of stroke or death in the first month was 12.5 per 100 person-months: highest in patients with large artery atherosclerosis (17.0). The risk of subsequent events shortly after a minor AIS or high-risk TIA was substantial, particularly in patients with large artery atherosclerosis.

Objectives: This study aimed to investigate suicidal behaviors and the related psychopathology across the different stages of schizophrenia. Methods: We recruited 131 patients with schizophrenia and categorized them into two groups, according to the duration of illness (DI) as follows: ≤10 years (n=39) and >10 years (n=92). Psychopathology and suicidality were assessed using the 18-item Brief Psychiatric Rating Scale (BPRS-18) and the suicidality module from the Mini-International Neuropsychiatric Interview, respectively. Results: One-quarter of the patients with a DI ≤10 years and nearly one-sixth of the patients with a DI >10 years experienced suicidal behaviors in the previous month. Suicidality scores were significantly associated with the “affect” factor scores of the BPRS-18 in patients with a DI ≤10 years (β=0.55, p=0.003) and with the “resistance” factor scores in patients with a DI of >10 years (β=0.29, p=0.006). Conclusion The present study demonstrated that psychopathological factors were differentially associated with suicidality in patients with schizophrenia according to the illness stage. Our findings suggest that for effective suicide prevention, different approaches are required for the management of each stage of schizophrenia.

Objective: More recently, attention has turned to the linkage between childhood trauma and emotional dysregulation, but the evidence in bipolar disorder (BD) is limited. To determine neurobiological relationships between childhood trauma, current anxiety, and impulsivity, we investigated cortical volumetric correlates of these clinical factors in BD. Methods: We studied 36 patients with DSM-5 BD and 29 healthy controls. Childhood trauma, coexisting anxiety, and impulsivity were evaluated with the Korean version-Childhood Trauma Questionnaire (CTQ), the Korean version-Beck Anxiety Inventory (BAI), and the Korean version-Barratt Impulsiveness Scale (BIS). Voxel-based morphometry (VBM) was used to assess gray matter volume (GMV) alterations on the brain magnetic resonance imaging (MRI). Partial correlation analyses were conducted to examine associations between the GMV and each scale in the BD group. Results: Childhood trauma, anxiety, and impulsivity were interrelated in BD. BD patients revealed significant inverse correlations between the GMV in the right precentral gyrus and CTQ scores (r=-0.609, p<0.0003); between the GMV in the left middle frontal gyrus and BAI scores (r=-0.363, p=0.044). Moreover, patients showed similar tendency of negative correlations between the GMV in the right precentral gyrus and BIS scores; between the GMV in the left middle frontal gyrus and CTQ scores. Conclusion The present study provides evidence for a neural basis between childhood trauma and affect regulations in BD. The GMV alterations in multiple frontal lobe areas may represent neurobiological markers for anticipating the course of BD.

Objective: This study used network analyses to examine network structures reflecting interactions between specific domains of social functioning in schizophrenia (SZ) and bipolar disorder (BD). Methods: We used the World Health Organization Disability Assessment Schedule 2.0 (WHODAS 2.0) to assess six domains of social functioning (‘cognition’, ‘mobility’, ‘self-care’, ‘getting along’, ‘life activities’, and ‘participation’) in 143 patients with SZ, 81 patients with BD, and 106 healthy subjects. We constructed regularized partial correlation networks, estimated network centrality and edge strength, tested network stability, and compared SZ and BD network structures. Results: Patients with SZ showed a significantly higher level of functional disability than patients with BD. In the networks we constructed, ‘cognition’ was the most central domain of social functioning in both SZ and BD. The ‘cognition’ domain was primarily associated with the ‘getting along’ domain in the SZ network and the ‘life activities’ domain in the BD network. We found no significant group-level differences in network structures for SZ vs. BD. Conclusion Our results suggest that cognition may play a pivotal role in social functioning in both SZ and BD. In addition, domains of social functioning in SZ and BD have similar network structures despite the higher level of disability in SZ compared to BD.

BACKGROUND AND PURPOSE: Thrombectomy within 24 hours can improve outcomes in selected patients with a clinical-infarct mismatch. We devised an easy-to-use visual estimation tool that allows infarct volume estimation in centers with limited resources. METHODS: We identified 1,031 patients with cardioembolic or large-artery atherosclerosis infarction on diffusion-weighted images (DWIs) obtained before recanalization therapy and within 24 hours of onset, and occlusion of the internal carotid or middle cerebral artery. Acute DWIs were mapped onto a standard template and used to create visual reference maps with known lesion volumes, which were then used in a validation study (with 130 cases) against software estimates of infarct volume. RESULTS: The DWI reference map chart comprises 144 maps corresponding to 12 different infarct volumes (0.5, 1, 2, 3, 5, 7, 9, 11, 13, 15, 17, and 19 mL) in each of 12 template slices (Montreal Neurological Institute z-axis –15 to 51 mm). Infarct volume in a patient is estimated by selecting a slice with a similar infarct size at the corresponding z-axis level on the reference maps and then adding up over all slices. The method yielded good correlations to software volumetrics and was easily learned by both experienced and junior physicians, with approximately 1 to 2 minutes spent per case. The sensitivity, specificity, and accuracy for detecting threshold infarct volumes ( < 21, < 31, and < 51 mL) were very high (all about >90%). CONCLUSIONS: We developed easy-to-use reference maps that allow prompt and reliable visual estimation of infarct volumes for triaging patients to thrombectomy in acute stroke.
Atherosclerosis ; Cerebral Infarction ; Decision Making ; Diffusion Magnetic Resonance Imaging ; Humans ; Infarction ; Medical Staff, Hospital ; Methods ; Middle Cerebral Artery ; Sensitivity and Specificity ; Stroke ; Thrombectomy

OBJECTIVE: We aimed to develop predictive models to identify suicide attempters among individuals with suicide ideation using a machine learning algorithm. METHODS: Among 35,116 individuals aged over 19 years from the Korea National Health & Nutrition Examination Survey, we selected 5,773 subjects who reported experiencing suicide ideation and had answered a survey question about suicide attempts. Then, we performed resampling with the Synthetic Minority Over-sampling TEchnique (SMOTE) to obtain data corresponding to 1,324 suicide attempters and 1,330 non-suicide attempters. We randomly assigned the samples to a training set (n=1,858) and a test set (n=796). In the training set, random forest models were trained with features selected through recursive feature elimination with 10-fold cross validation. Subsequently, the fitted model was used to predict suicide attempters in the test set. RESULTS: In the test set, the prediction model achieved very good performance [area under receiver operating characteristic curve (AUC)=0.947] with an accuracy of 88.9%. CONCLUSION: Our results suggest that a machine learning approach can enable the prediction of individuals at high risk of suicide through the integrated analysis of various suicide risk factors.
Forests ; Korea ; Machine Learning ; Risk Factors ; ROC Curve ; Suicide

OBJECTIVES: This study examined the functional disabilities of patients with chronic schizophrenia using WHO Disability Assessment Schedule 2.0 (WHODAS 2.0) and its related factors. METHODS: The subjects consisted of 86 patients with schizophrenia with more than 10 years' duration of illness and 40 healthy volunteers. The functional disabilities and psychopathology were evaluated using the WHODAS 2.0 and 18-items Brief Psychiatric Rating Scale (BPRS-18), respectively. This study analyzed the six sub-domains ('cognition', 'mobility', 'self-care', 'getting along', 'life activities', and 'participation') of WHODAS 2.0 and the four sub-scales ('positive symptoms', 'negative symptoms', 'affect', and 'resistance') of BPRS-18. RESULTS: Patients with chronic schizophrenia experienced severe functional disabilities across all six sub-domains of WHODAS 2.0 compared to healthy people. Hierarchical regression showed that 'negative symptoms' explained the disabilities in the WHODAS 2.0 sub-domains of 'cognition' (p<0.05), 'self-care' (p<0.05), 'getting along' (p<0.01), and 'life activities' (p<0.05). 'Positive symptoms' and 'affect' explained the disabilities in 'cognition' (p<0.01 and p<0.05, respectively) and 'participation' (p<0.05 and p<0.01, respectively). 'Resistance' was found to be a predictor of 'getting along' disabilities (p<0.01). CONCLUSION: Negative symptoms mainly accounted for the multiple domains of functional disabilities in the WHODAS 2.0 but residual positive and affective symptoms could also deteriorate the cognition and social participation of patients with chronic schizophrenia.
Affective Symptoms ; Appointments and Schedules ; Brief Psychiatric Rating Scale ; Cognition ; Disability Evaluation ; Global Health ; Healthy Volunteers ; Humans ; Psychopathology ; Schizophrenia ; Social Participation ; World Health Organization