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Cao P, Li Y, Dong Y, Tang Y, Xu G, Si Q, Chen C, Yao Y, Li R, Sui Y. Different structural connectivity patterns in the subregions of the thalamus, hippocampus, and cingulate cortex between schizophrenia and psychotic bipolar disorder. J Affect Disord 2024; 363:269-281. [PMID: 39053628 DOI: 10.1016/j.jad.2024.07.077] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/14/2024] [Revised: 06/25/2024] [Accepted: 07/14/2024] [Indexed: 07/27/2024]
Abstract
OBJECTIVE Schizophrenia (SCZ) and psychotic bipolar disorder (PBD) are two major psychotic disorders with similar symptoms and tight associations on the psychopathological level, posing a clinical challenge for their differentiation. This study aimed to investigate and compare the structural connectivity patterns of the limbic system between SCZ and PBD, and to identify specific regional disruptions associated with psychiatric symptoms. METHODS Using sMRI data from 146 SCZ, 160 PBD, and 145 healthy control (HC) participants, we employed a data-driven approach to segment the hippocampus, thalamus, hypothalamus, amygdala, and cingulate cortex into subregions. We then investigated the structural connectivity patterns between these subregions at the global and nodal levels. Additionally, we assessed psychotic symptoms by utilizing the subscales of the Brief Psychiatric Rating Scale (BPRS) to examine correlations between symptom severity and network metrics between groups. RESULTS Patients with SCZ and PBD had decreased global efficiency (Eglob) (SCZ: adjusted P<0.001; PBD: adjusted P = 0.003), local efficiency (Eloc) (SCZ and PBD: adjusted P<0.001), and clustering coefficient (Cp) (SCZ and PBD: adjusted P<0.001), and increased path length (Lp) (SCZ: adjusted P<0.001; PBD: adjusted P = 0.004) compared to HC. Patients with SCZ showed more pronounced decreases in Eglob (adjusted P<0.001), Eloc (adjusted P<0.001), and Cp (adjusted P = 0.029), and increased Lp (adjusted P = 0.024) compared to patients with PBD. The most notable structural disruptions were observed in the hippocampus and thalamus, which correlated with different psychotic symptoms, respectively. CONCLUSION This study provides evidence of distinct structural connectivity disruptions in the limbic system of patients with SCZ and PBD. These findings might contribute to our understanding of the neuropathological basis for distinguishing SCZ and PBD.
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Affiliation(s)
- Peiyu Cao
- Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing Brain Hospital, Nanjing 210000, Jiangsu, China
| | - Yuting Li
- Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing Brain Hospital, Nanjing 210000, Jiangsu, China; Huzhou Third People's Hospital, Huzhou 313000, Zhejiang, China
| | - Yingbo Dong
- Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing Brain Hospital, Nanjing 210000, Jiangsu, China
| | - Yilin Tang
- Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing Brain Hospital, Nanjing 210000, Jiangsu, China
| | - Guoxin Xu
- Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing Brain Hospital, Nanjing 210000, Jiangsu, China
| | - Qi Si
- Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing Brain Hospital, Nanjing 210000, Jiangsu, China; Huai'an No. 3 People's Hospital, Huai'an 223001, Jiangsu, China
| | - Congxin Chen
- Women's Hospital of Nanjing Medical University, Nanjing Maternity and Child Health Care Hospital, Nanjing 210000, Jiangsu, China
| | - Ye Yao
- Nanjing Medical University, Nanjing 210000, Jiangsu, China
| | - Runda Li
- Vanderbilt University, Nashville 37240, TN, USA
| | - Yuxiu Sui
- Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing Brain Hospital, Nanjing 210000, Jiangsu, China.
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2
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Yang S, Kim JW. Electrophysiological Markers Predicting Antipsychotic Treatment Response in Patients with Schizophrenia: A Retrospective Study. Neuropsychiatr Dis Treat 2024; 20:1387-1394. [PMID: 39007072 PMCID: PMC11246663 DOI: 10.2147/ndt.s467180] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/28/2024] [Accepted: 06/29/2024] [Indexed: 07/16/2024] Open
Abstract
Purpose This study aimed to provide an objective means of predicting treatment responses in patients with schizophrenia using quantitative electroencephalography (qEEG) as an electrophysiological indicator. We obtained qEEG recordings from patients with schizophrenia and explored them for patterns indicative of treatment responsiveness. Patients and Methods The study included 68 patients had been diagnosed with schizophrenia spectrum disorder. After retrospectively gathering demographic information, clinical data such as qEEG, Positive and Negative Syndrome Scale (PANSS), a multiple regression analysis was performed. This analysis employed baseline qEEG findings as independent variables and PANSS score changes as dependent variables to discern causal relationships. Results The mean age of the participants was 38.4 years(SD =13.73). The mean PANSS score on admission was 92.97, decreasing to 67.41 at discharge. Multiple regression analysis revealed that delta waves in T4 (β=0.346, t=3.165, p=0.002), and high-beta waves in Fp2 (β=0.231, t=2.361, p=0.021) were associated with PANSS changes in absolute power. In addition, the delta waves of O2 (β=0.250, t=3.288, p=0.002); beta waves of T3 (β=-1.463, t=-5.423, p<0.001) and O2 (β=0.551, t=3.366, p=0.001); high beta waves of Fp1 (β=0.307, t=4.026, p<0.001), T3 (β=0.855, t=4.414, p<0.001) and T6 (β=-0.838, t=-4.559, p<0.001) of absolute power using the Z-score were also related to PANSS changes. Pearson's correlation analysis showed that only delta waves at Cz (r= 0.246, p=0.043) in absolute power correlated with changes in the PANSS. Conclusion We found that certain qEEG wave patterns in patients with schizophrenia prior to antipsychotic treatment were linked to PANSS changes before and after treatment. Delta waves and beta waves, primarily in the frontal and temporal regions, were found to be significantly associated with changes in PANSS scores. In the future, the qEEG indicators identified in this study could serve as electrophysiological markers for predicting antipsychotic treatment responses in patients with schizophrenia.
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Affiliation(s)
- Seungheon Yang
- Department of Psychiatry, Daegu Catholic University Medical Center, Daegu, Republic of Korea
| | - Jun Won Kim
- Department of Psychiatry, Daegu Catholic University Medical Center, Daegu, Republic of Korea
- Department of Psychiatry, Daegu Catholic University School of Medicine, Daegu, Republic of Korea
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3
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Sun H, Liu N, Qiu C, Tao B, Yang C, Tang B, Li H, Zhan K, Cai C, Zhang W, Lui S. Applications of MRI in Schizophrenia: Current Progress in Establishing Clinical Utility. J Magn Reson Imaging 2024. [PMID: 38946400 DOI: 10.1002/jmri.29470] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2023] [Revised: 05/20/2024] [Accepted: 05/20/2024] [Indexed: 07/02/2024] Open
Abstract
Schizophrenia is a severe mental illness that significantly impacts the lives of affected individuals and with increasing mortality rates. Early detection and intervention are crucial for improving outcomes but the lack of validated biomarkers poses great challenges in such efforts. The use of magnetic resonance imaging (MRI) in schizophrenia enables the investigation of the disorder's etiological and neuropathological substrates in vivo. After decades of research, promising findings of MRI have been shown to aid in screening high-risk individuals and predicting illness onset, and predicting symptoms and treatment outcomes of schizophrenia. The integration of machine learning and deep learning techniques makes it possible to develop intelligent diagnostic and prognostic tools with extracted or selected imaging features. In this review, we aimed to provide an overview of current progress and prospects in establishing clinical utility of MRI in schizophrenia. We first provided an overview of MRI findings of brain abnormalities that might underpin the symptoms or treatment response process in schizophrenia patients. Then, we summarized the ongoing efforts in the computer-aided utility of MRI in schizophrenia and discussed the gap between MRI research findings and real-world applications. Finally, promising pathways to promote clinical translation were provided. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY: Stage 3.
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Affiliation(s)
- Hui Sun
- Department of Radiology, and Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China
- Huaxi MR Research Center (HMRRC), West China Hospital of Sichuan University, Chengdu, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China
| | - Naici Liu
- Department of Radiology, and Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China
- Huaxi MR Research Center (HMRRC), West China Hospital of Sichuan University, Chengdu, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China
| | - Changjian Qiu
- Mental Health Center, West China Hospital of Sichuan University, Sichuan Clinical Medical Research Center for Mental Disorders, Chengdu, China
| | - Bo Tao
- Department of Radiology, and Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China
- Huaxi MR Research Center (HMRRC), West China Hospital of Sichuan University, Chengdu, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China
| | - Chengmin Yang
- Department of Radiology, and Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China
- Huaxi MR Research Center (HMRRC), West China Hospital of Sichuan University, Chengdu, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China
| | - Biqiu Tang
- Department of Radiology, and Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China
- Huaxi MR Research Center (HMRRC), West China Hospital of Sichuan University, Chengdu, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China
| | - Hongwei Li
- Department of Radiology, and Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China
- Huaxi MR Research Center (HMRRC), West China Hospital of Sichuan University, Chengdu, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China
- Department of Radiology, The Third Hospital of Mianyang/Sichuan Mental Health Center, Mianyang, China
| | - Kongcai Zhan
- Department of Radiology, Zigong Affiliated Hospital of Southwest Medical University, Zigong Psychiatric Research Center, Zigong, China
| | - Chunxian Cai
- Department of Radiology, the Second People's Hospital of Neijiang, Neijiang, China
| | - Wenjing Zhang
- Department of Radiology, and Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China
- Huaxi MR Research Center (HMRRC), West China Hospital of Sichuan University, Chengdu, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China
| | - Su Lui
- Department of Radiology, and Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, China
- Huaxi MR Research Center (HMRRC), West China Hospital of Sichuan University, Chengdu, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China
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4
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Wu XS, Kang XW, Li X, Bai LJ, Xi YB, Li Y, Xu YQ, Hu WZ, Yin H, Lv YL. Baseline white matter function predicts short-term treatment response in first-episode schizophrenia. J Neuroimaging 2023. [PMID: 36939186 DOI: 10.1111/jon.13101] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2022] [Revised: 02/26/2023] [Accepted: 03/06/2023] [Indexed: 03/21/2023] Open
Abstract
BACKGROUND AND PURPOSE The detection and characterization of functional activities in the gray matter of schizophrenia (SZ) have been widely explored. However, the relationship between resting-state functional signals in the white matter of first-episode SZ and short-term treatment response remains unclear. METHODS Thirty-six patients with first-episode SZ and 44 matched healthy controls were recruited in this study. Patients were classified as nonresponders and responders based on response to antipsychotic medication during a single hospitalization. The fractional amplitude of low-frequency fluctuation (fALFF), regional homogeneity (ReHo), and functional connectivity (FC) of white matter were calculated. The relationships between functional changes and clinical features were analyzed. In addition, voxel-based morphometry was performed to analyze the white matter volume. RESULTS One-way analysis of variance showed significant differences of fALFF and ReHo in the left posterior thalamic radiation and left cingulum (hippocampus) in the patient group, and the areas were regarded as seeds. The FC was calculated between seeds and other white matter networks. Compared with responders, nonresponders showed significantly increased FC between the left cingulum (hippocampus) and left posterior thalamic radiation, splenium of corpus callosum, and left tapetum, and were associated with the changes of clinical assessment. However, there was no difference in white matter volume between groups. CONCLUSION Our work provides a novel insight that psycho-neuroimaging-based white matter function holds promise for influencing the clinical diagnosis and treatment of SZ.
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Affiliation(s)
- Xu-Sha Wu
- Department of Radiology, Xi'an People's Hospital (Xi'an Fourth Hospital), Xi'an, China
| | - Xiao-Wei Kang
- Department of Radiology, Xi'an People's Hospital (Xi'an Fourth Hospital), Xi'an, China
| | - Xuan Li
- The Key Laboratory of Biomedical Information Engineering, Ministry of Education, Department of Biomedical Engineering, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, China
| | - Li-Jun Bai
- The Key Laboratory of Biomedical Information Engineering, Ministry of Education, Department of Biomedical Engineering, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, China
| | - Yi-Bin Xi
- Department of Radiology, Xi'an People's Hospital (Xi'an Fourth Hospital), Xi'an, China
| | - Yan Li
- Department of Radiology, Xi'an People's Hospital (Xi'an Fourth Hospital), Xi'an, China.,School of Medical Technology, Shaanxi University of Chinese Medicine, Xianyang, China
| | - Yong-Qiang Xu
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Wen-Zhong Hu
- Department of Radiology, Xi'an People's Hospital (Xi'an Fourth Hospital), Xi'an, China.,Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Hong Yin
- Department of Radiology, Xi'an People's Hospital (Xi'an Fourth Hospital), Xi'an, China
| | - Ya-Li Lv
- Department of Neurology, Xi'an People's Hospital, Xi'an Fourth Hospital, Xi'an, China
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5
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Lencz T, Moyett A, Argyelan M, Barber AD, Cholewa J, Birnbaum ML, Gallego JA, John M, Szeszko PR, Robinson DG, Malhotra AK. Frontal lobe fALFF measured from resting-state fMRI as a prognostic biomarker in first-episode psychosis. Neuropsychopharmacology 2022; 47:2245-2251. [PMID: 36198875 PMCID: PMC9630308 DOI: 10.1038/s41386-022-01470-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/13/2022] [Revised: 09/05/2022] [Accepted: 09/21/2022] [Indexed: 11/09/2022]
Abstract
Clinical response to antipsychotic drug treatment is highly variable, yet prognostic biomarkers are lacking. The goal of the present study was to test whether the fractional amplitude of low-frequency fluctuations (fALFF), as measured from baseline resting-state fMRI data, can serve as a potential biomarker of treatment response to antipsychotics. Patients in the first episode of psychosis (n = 126) were enrolled in two prospective studies employing second-generation antipsychotics (risperidone or aripiprazole). Patients were scanned at the initiation of treatment on a 3T MRI scanner (Study 1, GE Signa HDx, n = 74; Study 2, Siemens Prisma, n = 52). Voxelwise fALFF derived from baseline resting-state fMRI scans served as the primary measure of interest, providing a hypothesis-free (as opposed to region-of-interest) search for regions of the brain that might be predictive of response. At baseline, patients who would later meet strict criteria for clinical response (defined as two consecutive ratings of much or very much improved on the CGI, as well as a rating of ≤3 on psychosis-related items of the BPRS-A) demonstrated significantly greater baseline fALFF in bilateral orbitofrontal cortex compared to non-responders. Thus, spontaneous activity in orbitofrontal cortex may serve as a prognostic biomarker of antipsychotic treatment.
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Affiliation(s)
- Todd Lencz
- Department of Psychiatry, Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, 11550, USA.
- Department of Psychiatry, Division of Research, The Zucker Hillside Hospital Division of Northwell Health, Glen Oaks, NY, 11004, USA.
- Institute for Behavioral Science, The Feinstein Institutes for Medical Research, Manhasset, NY, 11030, USA.
| | - Ashley Moyett
- Department of Psychiatry, Division of Research, The Zucker Hillside Hospital Division of Northwell Health, Glen Oaks, NY, 11004, USA
| | - Miklos Argyelan
- Department of Psychiatry, Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, 11550, USA
- Department of Psychiatry, Division of Research, The Zucker Hillside Hospital Division of Northwell Health, Glen Oaks, NY, 11004, USA
- Institute for Behavioral Science, The Feinstein Institutes for Medical Research, Manhasset, NY, 11030, USA
| | - Anita D Barber
- Department of Psychiatry, Division of Research, The Zucker Hillside Hospital Division of Northwell Health, Glen Oaks, NY, 11004, USA
- Institute for Behavioral Science, The Feinstein Institutes for Medical Research, Manhasset, NY, 11030, USA
| | - John Cholewa
- Department of Psychiatry, Division of Research, The Zucker Hillside Hospital Division of Northwell Health, Glen Oaks, NY, 11004, USA
| | - Michael L Birnbaum
- Department of Psychiatry, Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, 11550, USA
- Department of Psychiatry, Division of Research, The Zucker Hillside Hospital Division of Northwell Health, Glen Oaks, NY, 11004, USA
- Institute for Behavioral Science, The Feinstein Institutes for Medical Research, Manhasset, NY, 11030, USA
| | - Juan A Gallego
- Department of Psychiatry, Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, 11550, USA
- Department of Psychiatry, Division of Research, The Zucker Hillside Hospital Division of Northwell Health, Glen Oaks, NY, 11004, USA
- Institute for Behavioral Science, The Feinstein Institutes for Medical Research, Manhasset, NY, 11030, USA
| | - Majnu John
- Department of Psychiatry, Division of Research, The Zucker Hillside Hospital Division of Northwell Health, Glen Oaks, NY, 11004, USA
- Institute for Behavioral Science, The Feinstein Institutes for Medical Research, Manhasset, NY, 11030, USA
- Department of Mathematics, Hofstra University, Hempstead, NY, 11549, USA
| | - Philip R Szeszko
- James J. Peters VA Medical Center, Bronx, NY, 10468, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Delbert G Robinson
- Department of Psychiatry, Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, 11550, USA
- Department of Psychiatry, Division of Research, The Zucker Hillside Hospital Division of Northwell Health, Glen Oaks, NY, 11004, USA
- Institute for Behavioral Science, The Feinstein Institutes for Medical Research, Manhasset, NY, 11030, USA
| | - Anil K Malhotra
- Department of Psychiatry, Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, 11550, USA
- Department of Psychiatry, Division of Research, The Zucker Hillside Hospital Division of Northwell Health, Glen Oaks, NY, 11004, USA
- Institute for Behavioral Science, The Feinstein Institutes for Medical Research, Manhasset, NY, 11030, USA
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6
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Schizophrenia: A Narrative Review of Etiopathogenetic, Diagnostic and Treatment Aspects. J Clin Med 2022; 11:jcm11175040. [PMID: 36078967 PMCID: PMC9457502 DOI: 10.3390/jcm11175040] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2022] [Revised: 08/23/2022] [Accepted: 08/24/2022] [Indexed: 11/25/2022] Open
Abstract
Although schizophrenia is currently conceptualized as being characterized as a syndrome that includes a collection of signs and symptoms, there is strong evidence of heterogeneous and complex underpinned etiological, etiopathogenetic, and psychopathological mechanisms, which are still under investigation. Therefore, the present viewpoint review is aimed at providing some insights into the recently investigated schizophrenia research fields in order to discuss the potential future research directions in schizophrenia research. The traditional schizophrenia construct and diagnosis were progressively revised and revisited, based on the recently emerging neurobiological, genetic, and epidemiological research. Moreover, innovative diagnostic and therapeutic approaches are pointed to build a new construct, allowing the development of better clinical and treatment outcomes and characterization for schizophrenic individuals, considering a more patient-centered, personalized, and tailored-based dimensional approach. Further translational studies are needed in order to integrate neurobiological, genetic, and environmental studies into clinical practice and to help clinicians and researchers to understand how to redesign a new schizophrenia construct.
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Gong J, Cui LB, Zhao YS, Liu ZW, Yang XJ, Xi YB, Liu L, Liu P, Sun JB, Zhao SW, Liu XF, Jia J, Li P, Yin H, Qin W. The correlation between dynamic functional architecture and response to electroconvulsive therapy combined with antipsychotics in schizophrenia. Eur J Neurosci 2022; 55:2024-2036. [PMID: 35388553 DOI: 10.1111/ejn.15664] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2021] [Revised: 03/29/2022] [Accepted: 03/31/2022] [Indexed: 11/26/2022]
Abstract
Attempts to determine why some patients respond to electroconvulsive therapy (ECT) are valuable in schizophrenia. Schizophrenia is associated with aberrant dynamic functional architecture, which might impact the efficacy of ECT. We aimed to explore the relationship between pre-treatment temporal variability and ECT acute efficacy. Forty-eight patients with schizophrenia and thirty healthy controls underwent functional magnetic resonance imaging to examine whether patterns of temporary variability of functional architecture differ between high responders (HR) and low responders (LR) at baseline. Compared with LR, HR exhibited significantly abnormal temporal variability in right inferior front gyrus (IFGtriang.R), left temporal pole (TPOsup.L) and right middle temporal gyrus (MTG.R). In the pooled patient group, ∆PANSS was correlated with the temporal variability of these regions. Patients with schizophrenia with a distinct dynamic functional architecture appear to reveal differential response to ECT. Our findings provide not only an understanding of the neural functional architecture patterns that are found in schizophrenia but also the possibility of using these measures as moderators for ECT selection.
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Affiliation(s)
- Jie Gong
- Engineering Research Center of Molecular and Neuroimaging of Ministry of Education, School of Life Science and Technology, Xidian University, Xi'an, China
| | - Long-Biao Cui
- Department of Radiology, The Second Medical Center, Chinese PLA General Hospital, Beijing, China.,Department of Clinical Psychology, School of Medical Psychology, Fourth Military Medical University, Xi'an, China
| | - Ying-Song Zhao
- Engineering Research Center of Molecular and Neuroimaging of Ministry of Education, School of Life Science and Technology, Xidian University, Xi'an, China
| | - Zhao-Wen Liu
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Xue-Juan Yang
- Engineering Research Center of Molecular and Neuroimaging of Ministry of Education, School of Life Science and Technology, Xidian University, Xi'an, China
| | - Yi-Bin Xi
- Department of Radiology, Xi'an People's Hospital, Xi'an, China
| | - Lin Liu
- Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China
| | - Peng Liu
- Engineering Research Center of Molecular and Neuroimaging of Ministry of Education, School of Life Science and Technology, Xidian University, Xi'an, China
| | - Jin-Bo Sun
- Engineering Research Center of Molecular and Neuroimaging of Ministry of Education, School of Life Science and Technology, Xidian University, Xi'an, China
| | - Shu-Wan Zhao
- Department of Clinical Psychology, School of Medical Psychology, Fourth Military Medical University, Xi'an, China.,Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Xiao-Fan Liu
- Department of Clinical Psychology, School of Medical Psychology, Fourth Military Medical University, Xi'an, China.,Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Jie Jia
- Department of Early Intervention, Xi'an Mental Health Center, Xi'an, Shaanxi, China
| | - Ping Li
- Department of Medical Imaging, Xi'an Mental Health Center, Xi'an, Shaanxi, China
| | - Hong Yin
- Department of Radiology, Xi'an People's Hospital, Xi'an, China.,Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Wei Qin
- Engineering Research Center of Molecular and Neuroimaging of Ministry of Education, School of Life Science and Technology, Xidian University, Xi'an, China
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8
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Wei J, Wang X, Cui X, Wang B, Xue J, Niu Y, Wang Q, Osmani A, Xiang J. Functional Integration and Segregation in a Multilayer Network Model of Patients with Schizophrenia. Brain Sci 2022; 12:brainsci12030368. [PMID: 35326324 PMCID: PMC8946586 DOI: 10.3390/brainsci12030368] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Revised: 03/08/2022] [Accepted: 03/08/2022] [Indexed: 12/24/2022] Open
Abstract
Research has shown that abnormal brain networks in patients with schizophrenia appear at different frequencies, but the relationship between these different frequencies is unclear. Therefore, it is necessary to use a multilayer network model to evaluate the integration of information from different frequency bands. To explore the mechanism of integration and separation in the multilayer network of schizophrenia, we constructed multilayer frequency brain network models in 50 patients with schizophrenia and 69 healthy subjects, and the entropy of the multiplex degree (EMD) and multilayer clustering coefficient (MCC) were calculated. The results showed that the ability to integrate and separate information in the multilayer network of patients was significantly higher than that of normal people. This difference was mainly reflected in the default mode network, sensorimotor network, subcortical network, and visual network. Among them, the subcortical network was different in both MCC and EMD outcomes. Furthermore, differences were found in the posterior cingulate gyrus, hippocampus, amygdala, putamen, pallidum, and thalamus. The thalamus and posterior cingulate gyrus were associated with the patient’s symptom scores. Our results showed that the cross-frequency interaction ability of patients with schizophrenia was significantly enhanced, among which the subcortical network was the most active. This interaction may serve as a compensation mechanism for intralayer dysfunction.
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Affiliation(s)
- Jing Wei
- College of Information and Computer, Taiyuan University of Technology, Taiyuan 030024, China; (J.W.); (X.W.); (X.C.); (B.W.); (J.X.); (Y.N.); (Q.W.); (A.O.)
- School of Information, Shanxi University of Finance and Economics, Taiyuan 030024, China
| | - Xiaoyue Wang
- College of Information and Computer, Taiyuan University of Technology, Taiyuan 030024, China; (J.W.); (X.W.); (X.C.); (B.W.); (J.X.); (Y.N.); (Q.W.); (A.O.)
| | - Xiaohong Cui
- College of Information and Computer, Taiyuan University of Technology, Taiyuan 030024, China; (J.W.); (X.W.); (X.C.); (B.W.); (J.X.); (Y.N.); (Q.W.); (A.O.)
| | - Bin Wang
- College of Information and Computer, Taiyuan University of Technology, Taiyuan 030024, China; (J.W.); (X.W.); (X.C.); (B.W.); (J.X.); (Y.N.); (Q.W.); (A.O.)
| | - Jiayue Xue
- College of Information and Computer, Taiyuan University of Technology, Taiyuan 030024, China; (J.W.); (X.W.); (X.C.); (B.W.); (J.X.); (Y.N.); (Q.W.); (A.O.)
| | - Yan Niu
- College of Information and Computer, Taiyuan University of Technology, Taiyuan 030024, China; (J.W.); (X.W.); (X.C.); (B.W.); (J.X.); (Y.N.); (Q.W.); (A.O.)
| | - Qianshan Wang
- College of Information and Computer, Taiyuan University of Technology, Taiyuan 030024, China; (J.W.); (X.W.); (X.C.); (B.W.); (J.X.); (Y.N.); (Q.W.); (A.O.)
| | - Arezo Osmani
- College of Information and Computer, Taiyuan University of Technology, Taiyuan 030024, China; (J.W.); (X.W.); (X.C.); (B.W.); (J.X.); (Y.N.); (Q.W.); (A.O.)
| | - Jie Xiang
- College of Information and Computer, Taiyuan University of Technology, Taiyuan 030024, China; (J.W.); (X.W.); (X.C.); (B.W.); (J.X.); (Y.N.); (Q.W.); (A.O.)
- Correspondence:
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9
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Wang M, Hu K, Fan L, Yan H, Li P, Jiang T, Liu B. Predicting Treatment Response in Schizophrenia With Magnetic Resonance Imaging and Polygenic Risk Score. Front Genet 2022; 13:848205. [PMID: 35186051 PMCID: PMC8847599 DOI: 10.3389/fgene.2022.848205] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2022] [Accepted: 01/12/2022] [Indexed: 11/15/2022] Open
Abstract
Background: Prior studies have separately demonstrated that magnetic resonance imaging (MRI) and schizophrenia polygenic risk score (PRS) are predictive of antipsychotic medication treatment outcomes in schizophrenia. However, it remains unclear whether MRI combined with PRS can provide superior prognostic performance. Besides, the relative importance of these measures in predictions is not investigated. Methods: We collected 57 patients with schizophrenia, all of which had baseline MRI and genotype data. All these patients received approximately 6 weeks of antipsychotic medication treatment. Psychotic symptom severity was assessed using the Positive and Negative Syndrome Scale (PANSS) at baseline and follow-up. We divided these patients into responders (N = 20) or non-responders (N = 37) based on whether their percentages of PANSS total reduction were above or below 50%. Nine categories of MRI measures and PRSs with 145 different p-value thresholding ranges were calculated. We trained machine learning classifiers with these baseline predictors to identify whether a patient was a responder or non-responder. Results: The extreme gradient boosting (XGBoost) technique was applied to build binary classifiers. Using a leave-one-out cross-validation scheme, we achieved an accuracy of 86% with all MRI and PRS features. Other metrics were also estimated, including sensitivity (85%), specificity (86%), F1-score (81%), and area under the receiver operating characteristic curve (0.86). We found excluding a single feature category of gray matter volume (GMV), amplitude of low-frequency fluctuation (ALFF), and surface curvature could lead to a maximum accuracy drop of 10.5%. These three categories contributed more than half of the top 10 important features. Besides, removing PRS features caused a modest accuracy drop (8.8%), which was not the least decrease (1.8%) among all feature categories. Conclusions: Our classifier using both MRI and PRS features was stable and not biased to predicting either responder or non-responder. Combining with MRI measures, PRS could provide certain extra predictive power of antipsychotic medication treatment outcomes in schizophrenia. PRS exhibited medium importance in predictions, lower than GMV, ALFF, and surface curvature, but higher than measures of cortical thickness, cortical volume, and surface sulcal depth. Our findings inform the contributions of PRS in predictions of treatment outcomes in schizophrenia.
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Affiliation(s)
- Meng Wang
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China.,School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China
| | - Ke Hu
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China.,School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China
| | - Lingzhong Fan
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China.,School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China.,Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, China
| | - Hao Yan
- Peking University Sixth Hospital/Institute of Mental Health, Beijing, China.,Key Laboratory of Mental Health, Ministry of Health (Peking University), Beijing, China
| | - Peng Li
- Peking University Sixth Hospital/Institute of Mental Health, Beijing, China.,Key Laboratory of Mental Health, Ministry of Health (Peking University), Beijing, China
| | - Tianzi Jiang
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China.,School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China.,Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, China.,Key Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China.,Innovation Academy for Artificial Intelligence, Chinese Academy of Sciences, Beijing, China
| | - Bing Liu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China.,Chinese Institute for Brain Research, Beijing, China
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10
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Wang Y, Jiang Y, Liu D, Zhang J, Yao D, Luo C, Wang J. Atypical Antipsychotics Mediate Dynamics of Intrinsic Brain Activity in Early-Stage Schizophrenia? A Preliminary Study. Psychiatry Investig 2021; 18:1205-1212. [PMID: 34965706 PMCID: PMC8721296 DOI: 10.30773/pi.2020.0418] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/29/2020] [Accepted: 09/24/2021] [Indexed: 12/16/2022] Open
Abstract
OBJECTIVE Abnormalities of static brain activity have been reported in schizophrenia, but it remains to be clarified the temporal variability of intrinsic brain activities in schizophrenia and how atypical antipsychotics affect it. METHODS We employed a resting-state functional magnetic resonance imaging (rs-fMRI) and a sliding-window analysis of dynamic amplitude of low-frequency fluctuation (dALFF) to evaluate the dynamic brain activities in schizophrenia (SZ) patients before and after 8-week antipsychotic treatment. Twenty-six schizophrenia individuals and 26 matched healthy controls (HC) were included in this study. RESULTS Compared with HC, SZ showed stronger dALFF in the right inferior temporal gyrus (ITG.R) at baseline. After medication, the SZ group exhibited reduced dALFF in the right middle occipital gyrus (MOG.R) and increased dALFF in the left superior frontal gyrus (SFG.L), right middle frontal gyrus (MFG.R), and right inferior parietal lobule (IPL.R). Dynamic ALFF in IPL.R was found to significant negative correlate with the Scale for the Assessment of Negative Symptoms (SANS) scores at baseline. CONCLUSION Our results showed dynamic intrinsic brain activities altered in schizophrenia after short term antipsychotic treatment. The findings of this study support and expand the application of dALFF method in the study of the pathological mechanism in psychosis in the future.
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Affiliation(s)
- Yingchan Wang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yuchao Jiang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Dengtang Liu
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jianye Zhang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Dezhong Yao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Cheng Luo
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Jijun Wang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.,CAS Center for Excellence in Brain Science and Intelligence Technology (CEBSIT), Chinese Academy of Science, Shanghai, China.,Institute of Psychology and Behavioral Science, Shanghai Jiao Tong University, Shanghai, China
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11
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Li P, Zhao SW, Wu XS, Zhang YJ, Song L, Wu L, Liu XF, Fu YF, Wu D, Wu WJ, Zhang YH, Yin H, Cui LB, Guo F. The Association Between Lentiform Nucleus Function and Cognitive Impairments in Schizophrenia. Front Hum Neurosci 2021; 15:777043. [PMID: 34744673 PMCID: PMC8566813 DOI: 10.3389/fnhum.2021.777043] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2021] [Accepted: 09/29/2021] [Indexed: 01/10/2023] Open
Abstract
Introduction: Cognitive decline is the core schizophrenia symptom, which is now well accepted. Holding a role in various aspects of cognition, lentiform nucleus (putamen and globus pallidus) dysfunction contributes to the psychopathology of this disease. However, the effects of lentiform nucleus function on cognitive impairments in schizophrenia are yet to be investigated. Objectives: We aim to detect the fractional amplitude of low-frequency fluctuation (fALFF) alterations in patients with schizophrenia, and examine how their behavior correlates in relation to the cognitive impairments of the patients. Methods: All participants underwent magnetic resonance imaging (MRI) and cognitive assessment (digit span and digit symbol coding tests). Screening of brain regions with significant changes in fALFF values was based on analysis of the whole brain. The data were analyzed between Jun 2020 and Mar 2021. There were no interventions beyond the routine therapy determined by their clinicians on the basis of standard clinical practice. Results: There were 136 patients (75 men and 61 women, 24.1 ± 7.4 years old) and 146 healthy controls (82 men and 64 women, 24.2 ± 5.2 years old) involved in the experiments seriatim. Patients with schizophrenia exhibited decreased raw scores in cognitive tests (p < 0.001) and increased fALFF in the bilateral lentiform nuclei (left: 67 voxels; x = −24, y = −6, z = 3; peak t-value = 6.90; right: 16 voxels; x = 18, y = 0, z = 3; peak t-value = 6.36). The fALFF values in the bilateral lentiform nuclei were positively correlated with digit span-backward test scores (left: r = 0.193, p = 0.027; right: r = 0.190, p = 0.030), and the right lentiform nucleus was positively correlated with digit symbol coding scores (r = 0.209, p = 0.016). Conclusion: This study demonstrates that cognitive impairments in schizophrenia are associated with lentiform nucleus function as revealed by MRI, involving working memory and processing speed.
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Affiliation(s)
- Ping Li
- Medical Imaging Department 1, Xi'an Mental Health Center, Xi'an, China
| | - Shu-Wan Zhao
- Department of Radiology, Xijing Hospital, The Fourth Military Medical University, Xi'an, China
| | - Xu-Sha Wu
- Department of Radiology, Xijing Hospital, The Fourth Military Medical University, Xi'an, China
| | - Ya-Juan Zhang
- Department of Clinical Psychology, School of Medical Psychology, The Fourth Military Medical University, Xi'an, China
| | - Lei Song
- Department of Clinical Psychology, School of Medical Psychology, The Fourth Military Medical University, Xi'an, China
| | - Lin Wu
- Department of Clinical Psychology, School of Medical Psychology, The Fourth Military Medical University, Xi'an, China
| | - Xiao-Fan Liu
- Department of Radiology, Xijing Hospital, The Fourth Military Medical University, Xi'an, China
| | - Yu-Fei Fu
- Department of Radiology, Xijing Hospital, The Fourth Military Medical University, Xi'an, China
| | - Di Wu
- Department of Psychiatry, Xijing Hospital, The Fourth Military Medical University, Xi'an, China
| | - Wen-Jun Wu
- Department of Psychiatry, Xijing Hospital, The Fourth Military Medical University, Xi'an, China
| | - Ya-Hong Zhang
- Department of Psychiatry, Xijing Hospital, The Fourth Military Medical University, Xi'an, China
| | - Hong Yin
- Department of Radiology, Xijing Hospital, The Fourth Military Medical University, Xi'an, China
| | - Long-Biao Cui
- Department of Clinical Psychology, School of Medical Psychology, The Fourth Military Medical University, Xi'an, China.,Department of Radiology, The Second Medical Center, Chinese PLA General Hospital, Beijing, China
| | - Fan Guo
- Department of Radiology, Xijing Hospital, The Fourth Military Medical University, Xi'an, China
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12
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Resting-state functional connectivity predictors of treatment response in schizophrenia - A systematic review and meta-analysis. Schizophr Res 2021; 237:153-165. [PMID: 34534947 DOI: 10.1016/j.schres.2021.09.004] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/05/2021] [Revised: 08/18/2021] [Accepted: 09/06/2021] [Indexed: 11/21/2022]
Abstract
We aimed to systematically synthesize and quantify the utility of pre-treatment resting-state functional magnetic resonance imaging (rs-fMRI) in predicting antipsychotic response in schizophrenia. We searched the PubMed/MEDLINE database for studies that examined the magnitude of association between baseline rs-fMRI assessment and subsequent response to antipsychotic treatment in persons with schizophrenia. We also performed meta-analyses for quantifying the magnitude and accuracy of predicting response defined continuously and categorically. Data from 22 datasets examining 1280 individuals identified striatal and default mode network functional segregation and integration metrics as consistent determinants of treatment response. The pooled correlation coefficient for predicting improvement in total symptoms measured continuously was ~0.47 (12 datasets; 95% CI: 0.35 to 0.59). The pooled odds ratio of predicting categorically defined treatment response was 12.66 (nine datasets; 95% CI: 7.91-20.29), with 81% sensitivity and 76% specificity. rs-fMRI holds promise as a predictive biomarker of antipsychotic treatment response in schizophrenia. Future efforts need to focus on refining feature characterization to improve prediction accuracy, validate prediction models, and evaluate their implementation in clinical practice.
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13
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Increased Homotopic Connectivity in the Prefrontal Cortex Modulated by Olanzapine Predicts Therapeutic Efficacy in Patients with Schizophrenia. Neural Plast 2021; 2021:9954547. [PMID: 34512748 PMCID: PMC8429031 DOI: 10.1155/2021/9954547] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2021] [Revised: 08/08/2021] [Accepted: 08/18/2021] [Indexed: 11/18/2022] Open
Abstract
Background Previous studies have revealed the abnormalities in homotopic connectivity in schizophrenia. However, the relationship of these deficits to antipsychotic treatment in schizophrenia remains unclear. This study explored the effects of antipsychotic therapy on brain homotopic connectivity and whether the homotopic connectivity of these regions might predict individual treatment response in schizophrenic patients. Methods A total of 21 schizophrenic patients and 20 healthy controls were scanned by the resting-state functional magnetic resonance imaging. The patients received olanzapine treatment and were scanned at two time points. Voxel-mirrored homotopic connectivity (VMHC) and pattern classification techniques were applied to analyze the imaging data. Results Schizophrenic patients presented significantly decreased VMHC in the temporal and inferior frontal gyri, medial prefrontal cortex (MPFC), and motor and low-level sensory processing regions (including the fusiform gyrus and cerebellum lobule VI) relative to healthy controls. The VMHC in the superior/middle MPFC was significantly increased in the patients after eight weeks of treatment. Support vector regression (SVR) analyses revealed that VMHC in the superior/middle MPFC at baseline can predict the symptomatic improvement of the positive and negative syndrome scale after eight weeks of treatment. Conclusions This study demonstrated that olanzapine treatment may normalize decreased homotopic connectivity in the superior/middle MPFC in schizophrenic patients. The VMHC in the superior/middle MPFC may predict individual response for antipsychotic therapy. The findings of this study conduce to the comprehension of the therapy effects of antipsychotic medications on homotopic connectivity in schizophrenia.
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14
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Hosseininasab M, Zarghami M, Mazhari S, Salehifar E, Moosazadeh M, Fariborzifar A, Babaeirad S, Hendouei N. Nanocurcumin as an Add-on to Antipsychotic Drugs for Treatment of Negative Symptoms in Patients With Chronic Schizophrenia: A Randomized, Double-Blind, Placebo-Controlled Study. J Clin Psychopharmacol 2021; 41:25-30. [PMID: 33347019 DOI: 10.1097/jcp.0000000000001324] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
PURPOSE/BACKGROUND It is well documented that one of the pathophysiological mechanisms of negative symptoms in patients with schizophrenia is hypofunction of N-methyl-d-aspartate receptors. This double-blind, placebo-controlled clinical trial was designed to assess the efficacy and safety of nanocurcumin as an adjuvant agent on psychotic symptoms, especially negative symptoms, in patients with chronic schizophrenia. METHODS/PROCEDURES Fifty-six inpatients with stable chronic schizophrenia and predominant negative symptoms were randomized in a 1:1 ratio to nanocurcumin soft gel capsule (160 mg/d) and control groups, along with their antipsychotic regimen for 16 weeks. The efficacy of treatment was assessed by Positive and Negative Syndrome Scale, Calgary Depression Scale for Schizophrenia, Clinical Global Impressions-Severity, and Clinical Global Impressions-Improvement scales. Extrapyramidal symptoms were evaluated by Simpson-Angus Scale and Barnes Akathisia Rating Scale. Patients were assessed at baseline and weeks 4, 8, 12, and 16 after the medication started. FINDINGS/RESULTS No significant differences were observed in demographic or clinical variables between both groups at baseline. The nanocurcumin group showed significantly greater improvement on the negative subscale (P = 0.05), the general psychopathology subscale (P < 0.001), the positive subscale (P = 0.004), total Positive and Negative Syndrome Scale (P < 0.001), Clinical Global Impressions-Severity (P < 0.001), and Clinical Global Impressions-Improvement scores (P < 0.001) in comparison with the control group at the endpoint. Extrapyramidal symptom rating scales and Calgary Depression Scale for Schizophrenia and frequency of other adverse effects were comparable between 2 groups. IMPLICATIONS/CONCLUSIONS The present study indicates nanocurcumin as a safe and potential adjunctive treatment strategy for treatment of primary negative symptoms of schizophrenia.
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Affiliation(s)
- Masumeh Hosseininasab
- From the Department of Pharmacotherapy, Student Research Committee, Faculty of Pharmacy, Mazandaran University of Medical Sciences
| | | | - Shahrzad Mazhari
- Neuroscience Research Center; Psychiatric Department, School of Medicine, Kerman University of Medical Sciences, Kerman
| | - Ebrahim Salehifar
- Department of Pharmacotherapy, Faculty of Pharmacy, Pharmaceutical Sciences Research Center, Hemoglobinopathy Institute, Mazandaran University of Medical Sciences
| | - Mahmood Moosazadeh
- Epidemiology, Gastrointestinal Cancer Research Center, Health Sciences Research Center, Psychiatry and Behavioral Sciences Research Center, Addiction Institute, Non-communicable Diseases Institute, Mazandaran University of Medical Sciences
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15
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Cui LB, Zhang YJ, Lu HL, Liu L, Zhang HJ, Fu YF, Wu XS, Xu YQ, Li XS, Qiao YT, Qin W, Yin H, Cao F. Thalamus Radiomics-Based Disease Identification and Prediction of Early Treatment Response for Schizophrenia. Front Neurosci 2021; 15:682777. [PMID: 34290581 PMCID: PMC8289251 DOI: 10.3389/fnins.2021.682777] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2021] [Accepted: 05/31/2021] [Indexed: 12/15/2022] Open
Abstract
Background Emerging evidence suggests structural and functional disruptions of the thalamus in schizophrenia, but whether thalamus abnormalities are able to be used for disease identification and prediction of early treatment response in schizophrenia remains to be determined. This study aims at developing and validating a method of disease identification and prediction of treatment response by multi-dimensional thalamic features derived from magnetic resonance imaging in schizophrenia patients using radiomics approaches. Methods A total of 390 subjects, including patients with schizophrenia and healthy controls, participated in this study, among which 109 out of 191 patients had clinical characteristics of early outcome (61 responders and 48 non-responders). Thalamus-based radiomics features were extracted and selected. The diagnostic and predictive capacity of multi-dimensional thalamic features was evaluated using radiomics approach. Results Using radiomics features, the classifier accurately discriminated patients from healthy controls, with an accuracy of 68%. The features were further confirmed in prediction and random forest of treatment response, with an accuracy of 75%. Conclusion Our study demonstrates a radiomics approach by multiple thalamic features to identify schizophrenia and predict early treatment response. Thalamus-based classification could be promising to apply in schizophrenia definition and treatment selection.
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Affiliation(s)
- Long-Biao Cui
- The Second Medical Center, Chinese PLA General Hospital, Beijing, China.,Department of Clinical Psychology, Fourth Military Medical University, Xi'an, China
| | - Ya-Juan Zhang
- Military Medical Psychology School, Fourth Military Medical University, Xi'an, China
| | - Hong-Liang Lu
- Military Medical Psychology School, Fourth Military Medical University, Xi'an, China
| | - Lin Liu
- School of Life Sciences and Technology, Xidian University, Xi'an, China.,Peking University Sixth Hospital/Institute of Mental Health and Key Laboratory of Mental Health, Peking University, Beijing, China
| | - Hai-Jun Zhang
- Department of Clinical Aerospace Medicine, School of Aerospace Medicine, Fourth Military Medical University, Xi'an, China
| | - Yu-Fei Fu
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Xu-Sha Wu
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Yong-Qiang Xu
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Xiao-Sa Li
- Department of Psychiatry, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Yu-Ting Qiao
- Department of Psychiatry, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Wei Qin
- School of Life Sciences and Technology, Xidian University, Xi'an, China
| | - Hong Yin
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Feng Cao
- The Second Medical Center, Chinese PLA General Hospital, Beijing, China
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16
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Xie Y, Xi Y, Cui LB, Li C, Xu Y, Zhang Y, Yan Q, Fang P, Yin H. Altered functional connectivity of the dentate nuclei in patients with schizophrenia. Schizophr Res 2021; 233:16-23. [PMID: 34216941 DOI: 10.1016/j.schres.2021.06.035] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/23/2020] [Revised: 01/31/2021] [Accepted: 06/23/2021] [Indexed: 01/12/2023]
Abstract
Dentate nuclei (DN) are vital structures in the anatomical circuits that link the cerebellum to the cerebrum. However, the characteristics of DN functional connectivity (FC) in schizophrenia remain largely unknown. In this study, we investigated the FC of the DN in patients with schizophrenia and examined their possible clinical correlates using resting-state functional magnetic imaging data. We found that the patient group had greater DN FC with the parietal lobe (e.g., postcentral gyrus and superior parietal lobule) and less DN FC with the prefrontal cortex (e.g., superior frontal gyrus), posterior cingulate cortex, and regional cerebellum (e.g., vermis 4-5 and crus I) than did the control group. Furthermore, some abnormal connectivities of the DN with these regions significantly correlated with psychiatric symptoms. These results suggest that the DN circuits are disturbed and may participate in the pathophysiology of schizophrenia.
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Affiliation(s)
- Yuanjun Xie
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Yibin Xi
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Long-Biao Cui
- Department of Radiology, The Second Medical Center, Chinese PLA General Hospital, Beijing, China; Department of Clinical Psychology, School of Medical Psychology, Fourth Military Medical University, Xi'an, China
| | - Chen Li
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Yongqiang Xu
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Yahong Zhang
- Department of Psychiatry, School of Medical Psychology, Fourth Military Medical University, Xi'an, China
| | - Qinghong Yan
- Department of Psychiatry, School of Medical Psychology, Fourth Military Medical University, Xi'an, China
| | - Peng Fang
- Department of Military Medical Psychology, School of Medical Psychology, Fourth Military Medical University, Xi'an, China
| | - Hong Yin
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, China.
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17
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Wu XS, Yan TC, Wang XY, Cao Y, Liu XF, Fu YF, Wu L, Jin YC, Yin H, Cui LB. Magnetic Resonance Imaging-Guided and Navigated Individualized Repetitive Transcranial Magnetic Stimulation for Cognitive Impairment in Schizophrenia. Neurosci Bull 2021; 37:1365-1369. [PMID: 34145549 DOI: 10.1007/s12264-021-00727-3] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2020] [Accepted: 04/12/2021] [Indexed: 12/21/2022] Open
Affiliation(s)
- Xu-Sha Wu
- School of Medical Technology, Shaanxi University of Chinese Medicine, Xianyang, 712046, China
- Department of Clinical Psychology, School of Medical Psychology, Fourth Military Medical University, Xi'an, 710032, China
| | - Tian-Cai Yan
- School of Medical Imaging, Mudanjiang Medical University, Mudanjiang, 157011, China
| | - Xian-Yang Wang
- Department of Clinical Psychology, School of Medical Psychology, Fourth Military Medical University, Xi'an, 710032, China
| | - Yang Cao
- Department of Clinical Psychology, School of Medical Psychology, Fourth Military Medical University, Xi'an, 710032, China
| | - Xiao-Fan Liu
- School of Medical Technology, Shaanxi University of Chinese Medicine, Xianyang, 712046, China
- Department of Clinical Psychology, School of Medical Psychology, Fourth Military Medical University, Xi'an, 710032, China
| | - Yu-Fei Fu
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, 710032, China
| | - Lin Wu
- Department of Clinical Psychology, School of Medical Psychology, Fourth Military Medical University, Xi'an, 710032, China
| | - Yin-Chuan Jin
- Department of Clinical Psychology, School of Medical Psychology, Fourth Military Medical University, Xi'an, 710032, China
| | - Hong Yin
- School of Medical Technology, Shaanxi University of Chinese Medicine, Xianyang, 712046, China.
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, 710032, China.
| | - Long-Biao Cui
- Department of Clinical Psychology, School of Medical Psychology, Fourth Military Medical University, Xi'an, 710032, China.
- Department of Radiology, The Second Medical Center, Chinese PLA General Hospital, Beijing, 100853, China.
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18
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Kraguljac NV, McDonald WM, Widge AS, Rodriguez CI, Tohen M, Nemeroff CB. Neuroimaging Biomarkers in Schizophrenia. Am J Psychiatry 2021; 178:509-521. [PMID: 33397140 PMCID: PMC8222104 DOI: 10.1176/appi.ajp.2020.20030340] [Citation(s) in RCA: 114] [Impact Index Per Article: 38.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Schizophrenia is a complex neuropsychiatric syndrome with a heterogeneous genetic, neurobiological, and phenotypic profile. Currently, no objective biological measures-that is, biomarkers-are available to inform diagnostic or treatment decisions. Neuroimaging is well positioned for biomarker development in schizophrenia, as it may capture phenotypic variations in molecular and cellular disease targets, or in brain circuits. These mechanistically based biomarkers may represent a direct measure of the pathophysiological underpinnings of the disease process and thus could serve as true intermediate or surrogate endpoints. Effective biomarkers could validate new treatment targets or pathways, predict response, aid in selection of patients for therapy, determine treatment regimens, and provide a rationale for personalized treatments. In this review, the authors discuss a range of mechanistically plausible neuroimaging biomarker candidates, including dopamine hyperactivity, N-methyl-d-aspartate receptor hypofunction, hippocampal hyperactivity, immune dysregulation, dysconnectivity, and cortical gray matter volume loss. They then focus on the putative neuroimaging biomarkers for disease risk, diagnosis, target engagement, and treatment response in schizophrenia. Finally, they highlight areas of unmet need and discuss strategies to advance biomarker development.
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Affiliation(s)
- Nina V. Kraguljac
- Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham, Birmingham, AL,Corresponding Author: Nina Vanessa Kraguljac, MD, Department of Psychiatry and Behavioral Neurobiology, The University of Alabama at Birmingham, SC 501, 1720 7th Ave S, Birmingham, AL 35294-0017, 205-996-7171,
| | - William M. McDonald
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine
| | - Alik S. Widge
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN
| | - Carolyn I. Rodriguez
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA,Veterans Affairs Palo Alto Health Care System, Palo Alto, CA
| | - Mauricio Tohen
- Department of Psychiatry and Behavioral Sciences, University of New Mexico Health Sciences Center, Albuquerque, NM, USA
| | - Charles B. Nemeroff
- Department of Psychiatry, University of Texas Dell Medical School, Austin, TX
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19
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Korda AI, Andreou C, Borgwardt S. Pattern classification as decision support tool in antipsychotic treatment algorithms. Exp Neurol 2021; 339:113635. [PMID: 33548218 DOI: 10.1016/j.expneurol.2021.113635] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2020] [Revised: 01/20/2021] [Accepted: 02/01/2021] [Indexed: 10/22/2022]
Abstract
Pattern classification aims to establish a new approach in personalized treatment. The scope is to tailor treatment on individual characteristics during all phases of care including prevention, diagnosis, treatment, and clinical outcome. In psychotic disorders, this need results from the fact that a third of patients with psychotic symptoms do not respond to antipsychotic treatment and are described as having treatment-resistant disorders. This, in addition to the high variability of treatment responses among patients, enhances the need of applying advanced classification algorithms to identify antipsychotic treatment patterns. This review comprehensively summarizes advancements and challenges of pattern classification in antipsychotic treatment response to date and aims to introduce clinicians and researchers to the challenges of including pattern classification into antipsychotic treatment decision algorithms.
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Affiliation(s)
- Alexandra I Korda
- Department of Psychiatry and Psychotherapy, University Hospital Lübeck (UKSH), Ratzeburger Allee 160, 23538 Lübeck, Germany
| | - Christina Andreou
- Department of Psychiatry and Psychotherapy, University Hospital Lübeck (UKSH), Ratzeburger Allee 160, 23538 Lübeck, Germany
| | - Stefan Borgwardt
- Department of Psychiatry and Psychotherapy, University Hospital Lübeck (UKSH), Ratzeburger Allee 160, 23538 Lübeck, Germany.
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20
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Shan X, Liao R, Ou Y, Pan P, Ding Y, Liu F, Chen J, Zhao J, Guo W, He Y. Increased regional homogeneity modulated by metacognitive training predicts therapeutic efficacy in patients with schizophrenia. Eur Arch Psychiatry Clin Neurosci 2021; 271:783-798. [PMID: 32215727 PMCID: PMC8119286 DOI: 10.1007/s00406-020-01119-w] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/30/2019] [Accepted: 03/11/2020] [Indexed: 02/07/2023]
Abstract
Previous studies have demonstrated the efficacy of metacognitive training (MCT) in schizophrenia. However, the underlying mechanisms related to therapeutic effect of MCT remain unknown. The present study explored the treatment effects of MCT on brain regional neural activity using regional homogeneity (ReHo) and whether these regions' activities could predict individual treatment response in schizophrenia. Forty-one patients with schizophrenia and 20 healthy controls were scanned using resting-state functional magnetic resonance imaging. Patients were randomly divided into drug therapy (DT) and drug plus psychotherapy (DPP) groups. The DT group received only olanzapine treatment, whereas the DPP group received olanzapine and MCT for 8 weeks. The results revealed that ReHo in the right precuneus, left superior medial prefrontal cortex (MPFC), right parahippocampal gyrus and left rectus was significantly increased in the DPP group after 8 weeks of treatment. Patients in the DT group showed significantly increased ReHo in the left ventral MPFC/anterior cingulate cortex (ACC), left superior MPFC/middle frontal gyrus (MFG), left precuneus, right rectus and left MFG, and significantly decreased ReHo in the bilateral cerebellum VIII and left inferior occipital gyrus (IOG) after treatment. Support vector regression analyses showed that high ReHo levels at baseline in the right precuneus and left superior MPFC could predict symptomatic improvement of Positive and Negative Syndrome Scale (PANSS) after 8 weeks of DPP treatment. Moreover, high ReHo levels at baseline and alterations of ReHo in the left ventral MPFC/ACC could predict symptomatic improvement of PANSS after 8 weeks of DT treatment. This study suggests that MCT is associated with the modulation of ReHo in schizophrenia. ReHo in the right precuneus and left superior MPFC may predict individual therapeutic response for MCT in patients with schizophrenia.
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Affiliation(s)
- Xiaoxiao Shan
- grid.452708.c0000 0004 1803 0208Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, 410011 Hunan China ,National Clinical Research Center on Mental Disorders, Changsha, 410011 Hunan China
| | - Rongyuan Liao
- grid.412990.70000 0004 1808 322XThe Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, Henan China
| | - Yangpan Ou
- grid.452708.c0000 0004 1803 0208Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, 410011 Hunan China ,National Clinical Research Center on Mental Disorders, Changsha, 410011 Hunan China
| | - Pan Pan
- grid.452708.c0000 0004 1803 0208Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, 410011 Hunan China ,National Clinical Research Center on Mental Disorders, Changsha, 410011 Hunan China
| | - Yudan Ding
- grid.452708.c0000 0004 1803 0208Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, 410011 Hunan China ,National Clinical Research Center on Mental Disorders, Changsha, 410011 Hunan China
| | - Feng Liu
- grid.412645.00000 0004 1757 9434Department of Radiology, Tianjin Medical University General Hospital, Tianjin, 300000 China
| | - Jindong Chen
- grid.452708.c0000 0004 1803 0208Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, 410011 Hunan China ,National Clinical Research Center on Mental Disorders, Changsha, 410011 Hunan China
| | - Jingping Zhao
- grid.452708.c0000 0004 1803 0208Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, 410011 Hunan China ,National Clinical Research Center on Mental Disorders, Changsha, 410011 Hunan China
| | - Wenbin Guo
- Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, 410011, Hunan, China. .,National Clinical Research Center on Mental Disorders, Changsha, 410011, Hunan, China.
| | - Yiqun He
- The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, Henan, China.
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21
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Yao C, Hu N, Cao H, Tang B, Zhang W, Xiao Y, Zhao Y, Gong Q, Lui S. A Multimodal Fusion Analysis of Pretreatment Anatomical and Functional Cortical Abnormalities in Responsive and Non-responsive Schizophrenia. Front Psychiatry 2021; 12:737179. [PMID: 34925087 PMCID: PMC8671303 DOI: 10.3389/fpsyt.2021.737179] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/07/2021] [Accepted: 10/29/2021] [Indexed: 02/05/2023] Open
Abstract
Background: Antipsychotic medications provide limited long-term benefit to ~30% of schizophrenia patients. Multimodal magnetic resonance imaging (MRI) data have been used to investigate brain features between responders and nonresponders to antipsychotic treatment; however, these analytical techniques are unable to weigh the interrelationships between modalities. Here, we used multiset canonical correlation and joint independent component analysis (mCCA + jICA) to fuse MRI data to examine the shared and specific multimodal features between the patients and healthy controls (HCs) and between the responders and non-responders. Method: Resting-state functional and structural MRI data were collected from 55 patients with drug-naïve first-episode schizophrenia (FES) and demographically matched HCs. Based on the decrease in Positive and Negative Syndrome Scale scores from baseline to the 1-year follow-up, FES patients were divided into a responder group (RG) and a non-responder group (NRG). Gray matter volume (GMV), fractional amplitude of low-frequency fluctuation (fALFF), and regional homogeneity (ReHo) maps were used as features in mCCA + jICA. Results: Between FES patients and HCs, there were three modality-specific discriminative independent components (ICs) showing the difference in mixing coefficients (GMV-IC7, GMV-IC8, and fALFF-IC5). The fusion analysis indicated one modality-shared IC (GMV-IC2 and ReHo-IC2) and three modality-specific ICs (GMV-IC1, GMV-IC3, and GMV-IC6) between the RG and NRG. The right postcentral gyrus showed a significant difference in GMV features between FES patients and HCs and modality-shared features (GMV and ReHo) between responders and nonresponders. The modality-shared component findings were highlighted by GMV, mainly in the bilateral temporal gyrus and the right cerebellum associated with ReHo in the right postcentral gyrus. Conclusions: This study suggests that joint anatomical and functional features of the cortices may reflect an early pathophysiological mechanism that is related to a 1-year treatment response.
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Affiliation(s)
- Chenyang Yao
- Department of Radiology, Huaxi Magnetic Resonance Research Center, West China Hospital, Sichuan University, Chengdu, China.,Department of Radiology, West China Hospital, Sichuan University, Chengdu, China.,Department of Imaging Medicine, Inner Mongolia Autonomous Region People's Hospital, Hohhot, China
| | - Na Hu
- Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
| | - Hengyi Cao
- Department of Radiology, Huaxi Magnetic Resonance Research Center, West China Hospital, Sichuan University, Chengdu, China.,Center for Psychiatric Neuroscience, Feinstein Institute for Medical Research, Manhasset, NY, United States.,Division of Psychiatry Research, Zucker Hillside Hospital, Glen Oaks, NY, United States
| | - Biqiu Tang
- Department of Radiology, Huaxi Magnetic Resonance Research Center, West China Hospital, Sichuan University, Chengdu, China.,Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
| | - Wenjing Zhang
- Department of Radiology, Huaxi Magnetic Resonance Research Center, West China Hospital, Sichuan University, Chengdu, China.,Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
| | - Yuan Xiao
- Department of Radiology, Huaxi Magnetic Resonance Research Center, West China Hospital, Sichuan University, Chengdu, China.,Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
| | - Youjin Zhao
- Department of Radiology, Huaxi Magnetic Resonance Research Center, West China Hospital, Sichuan University, Chengdu, China.,Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
| | - Qiyong Gong
- Department of Radiology, Huaxi Magnetic Resonance Research Center, West China Hospital, Sichuan University, Chengdu, China.,Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
| | - Su Lui
- Department of Radiology, Huaxi Magnetic Resonance Research Center, West China Hospital, Sichuan University, Chengdu, China.,Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
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22
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Cui LB, Fu YF, Liu L, Wu XS, Xi YB, Wang HN, Qin W, Yin H. Baseline structural and functional magnetic resonance imaging predicts early treatment response in schizophrenia with radiomics strategy. Eur J Neurosci 2020; 53:1961-1975. [PMID: 33206423 DOI: 10.1111/ejn.15046] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2020] [Revised: 10/27/2020] [Accepted: 11/11/2020] [Indexed: 02/07/2023]
Abstract
Multimodal neuroimaging features provide opportunities for accurate classification and personalized treatment options in the psychiatric domain. This study aimed to investigate whether brain features predict responses to the overall treatment of schizophrenia at the end of the first or a single hospitalization. Structural and functional magnetic resonance imaging (MRI) data from two independent samples (N = 85 and 63, separately) of schizophrenia patients at baseline were included. After treatment, patients were classified as responders and non-responders. Radiomics features of gray matter morphology and functional connectivity were extracted using Least Absolute Shrinkage and Selection Operator. Support vector machine was used to explore the predictive performance. Prediction models were based on structural features (cortical thickness, surface area, gray matter regional volume, mean curvature, metric distortion, and sulcal depth), functional features (functional connectivity), and combined features. There were 12 features after dimensionality reduction. The structural features involved the right precuneus, cuneus, and inferior parietal lobule. The functional features predominately included inter-hemispheric connectivity. We observed a prediction accuracy of 80.38% (sensitivity: 87.28%; specificity 82.47%) for the model using functional features, and 69.68% (sensitivity: 83.96%; specificity: 72.41%) for the one using structural features. Our model combining both structural and functional features achieved a higher accuracy of 85.03%, with 92.04% responder and 80.23% non-responders to the overall treatment to be correctly predicted. These results highlight the power of structural and functional MRI-derived radiomics features to predict early response to treatment in schizophrenia. Prediction models of the very early treatment response in schizophrenia could augment effective therapeutic strategies.
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Affiliation(s)
- Long-Biao Cui
- Department of Clinical Psychology, School of Medical Psychology, Fourth Military Medical University, Xi'an, China.,Department of Psychiatry, Xijing Hospital, Fourth Military Medical University, Xi'an, China.,Department of Radiology, The Second Medical Center, Chinese PLA General Hospital, Beijing, China
| | - Yu-Fei Fu
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Lin Liu
- School of Life Sciences and Technology, Xidian University, Xi'an, China.,Sixth Hospital/Institute of Mental Health and Key Laboratory of Mental Health, Peking University, Beijing, China
| | - Xu-Sha Wu
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Yi-Bin Xi
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Hua-Ning Wang
- Department of Psychiatry, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Wei Qin
- School of Life Sciences and Technology, Xidian University, Xi'an, China
| | - Hong Yin
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, China
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23
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Cortical abnormalities and identification for first-episode schizophrenia via high-resolution magnetic resonance imaging. Biomark Neuropsychiatry 2020. [DOI: 10.1016/j.bionps.2020.100022] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
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24
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Xi YB, Cui LB, Gong J, Fu YF, Wu XS, Guo F, Yang X, Li C, Wang XR, Li P, Qin W, Yin H. Neuroanatomical Features That Predict Response to Electroconvulsive Therapy Combined With Antipsychotics in Schizophrenia: A Magnetic Resonance Imaging Study Using Radiomics Strategy. Front Psychiatry 2020; 11:456. [PMID: 32528327 PMCID: PMC7253706 DOI: 10.3389/fpsyt.2020.00456] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/18/2019] [Accepted: 05/05/2020] [Indexed: 12/18/2022] Open
Abstract
OBJECTIVE Neuroimaging-based brain signatures may be informative in identifying patients with psychosis who will respond to antipsychotics. However, signatures that inform the electroconvulsive therapy (ECT) health care professional about the response likelihood remain unclear in psychosis with radiomics strategy. This study investigated whether brain structure-based signature in the prediction of ECT response in a sample of schizophrenia patients using radiomics approach. METHODS This high-resolution structural magnetic resonance imaging study included 57 patients at baseline. After ECT combined with antipsychotics, 28 and 29 patients were classified as responders and non-responders. Features of gray matter were extracted and compared. The logistic regression model/support vector machine (LRM/SVM) analysis was used to explore the predictive performance. RESULTS The regularized multivariate LRM accurately discriminated responders from non-responders, with an accuracy of 90.91%. The structural features were further confirmed in the validating data set, resulting in an accuracy of 87.59%. The accuracy of the SVM in the training set was 90.91%, and the accuracy in the validation set was 91.78%. CONCLUSION Our results support the possible use of structural brain feature-based radiomics as a potential tool for predicting ECT response in patients with schizophrenia undergoing antipsychotics, paving the way for utilization of markers in psychosis.
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Affiliation(s)
- Yi-Bin Xi
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Long-Biao Cui
- Department of Clinical Psychology, School of Medical Psychology, Fourth Military Medical University, Xi'an, China
| | - Jie Gong
- School of Life Sciences and Technology, Xidian University, Xi'an, China
| | - Yu-Fei Fu
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, China.,Department of Clinical Psychology, School of Medical Psychology, Fourth Military Medical University, Xi'an, China
| | - Xu-Sha Wu
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, China.,Department of Clinical Psychology, School of Medical Psychology, Fourth Military Medical University, Xi'an, China
| | - Fan Guo
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Xuejuan Yang
- School of Life Sciences and Technology, Xidian University, Xi'an, China
| | - Chen Li
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Xing-Rui Wang
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Ping Li
- Department of Radiology, Xi'an Mental Health Center, Xi'an, China
| | - Wei Qin
- School of Life Sciences and Technology, Xidian University, Xi'an, China
| | - Hong Yin
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, China
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25
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Joo SW, Yoon W, Jo YT, Kim H, Kim Y, Lee J. Aberrant Executive Control and Auditory Networks in Recent-Onset Schizophrenia. Neuropsychiatr Dis Treat 2020; 16:1561-1570. [PMID: 32606708 PMCID: PMC7319504 DOI: 10.2147/ndt.s254208] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/16/2020] [Accepted: 05/27/2020] [Indexed: 12/21/2022] Open
Abstract
PURPOSE Despite a large number of resting-state functional MRI (rsfMRI) studies in schizophrenia, current evidence on the abnormalities of functional connectivity (FC) of resting-state networks shows high variability, and the findings on recent-onset schizophrenia are insufficient compared to those on chronic schizophrenia. PATIENTS AND METHODS We performed a rsfMRI in 46 patients with recent-onset schizophrenia and 22 healthy controls. Group independent component brainmap and dual regression were performed for voxel-wise comparisons between the groups. Correlation of the symptom severity, cognitive function, duration of illness, and a total antipsychotics dose with FC was evaluated with Spearman's rho correlation. RESULTS The patient group had areas with a significantly decreased FC compared to that of the control group in which it existed in the left supplementary motor cortex and supramarginal gyrus (the executive control network) and the right postcentral gyrus (the auditory network). The patient group had a significant correlation of the total antipsychotics dose with the FC of the cluster in the left supplementary motor cortex in the executive control network. CONCLUSION Patients with recent-onset schizophrenia have decreased FC of the executive control and auditory networks compared to healthy controls.
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Affiliation(s)
- Sung Woo Joo
- Medical Corps, Republic of Korea Navy 1st Fleet, Donghae, Republic of Korea
| | - Woon Yoon
- Department of Psychiatry, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
| | - Young Tak Jo
- Department of Psychiatry, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
| | - Harin Kim
- Department of Psychiatry, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
| | - Yangsik Kim
- Department of Psychiatry, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
| | - Jungsun Lee
- Department of Psychiatry, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
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26
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Keshavan MS, Collin G, Guimond S, Kelly S, Prasad KM, Lizano P. Neuroimaging in Schizophrenia. Neuroimaging Clin N Am 2019; 30:73-83. [PMID: 31759574 DOI: 10.1016/j.nic.2019.09.007] [Citation(s) in RCA: 64] [Impact Index Per Article: 12.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/09/2023]
Abstract
Schizophrenia is a chronic psychotic disorder with a lifetime prevalence of about 1%. Onset is typically in adolescence or early adulthood; characteristic symptoms include positive symptoms, negative symptoms, and impairments in cognition. Neuroimaging studies have shown substantive evidence of brain structural, functional, and neurochemical alterations that are more pronounced in the association cortex and subcortical regions. These abnormalities are not sufficiently specific to be of diagnostic value, but there may be a role for imaging techniques to provide predictions of outcome. Incorporating multimodal imaging datasets using machine learning approaches may offer better diagnostic and predictive value in schizophrenia.
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Affiliation(s)
- Matcheri S Keshavan
- Beth Israel Deaconess Medical Center, Harvard Medical School, 75 Fenwood Road, Boston, MA 02115, USA.
| | - Guusje Collin
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, 43 Vassar St, Cambridge, MA 02139, USA; University Medical Center Utrecht Brain Center, Heidelberglaan 100, Postbus 85500, 3508 GA, Utrecht, the Netherlands
| | - Synthia Guimond
- Department of Psychiatry, The Royal's Institute of Mental Health Research, University of Ottawa, 1145 Carling Avenue, Ottawa, ON K1Z 7K4, Canada
| | - Sinead Kelly
- Beth Israel Deaconess Medical Center, Harvard Medical School, 75 Fenwood Road, Boston, MA 02115, USA
| | - Konasale M Prasad
- University of Pittsburgh School of Medicine, Suite 279, 3811 O'Hara St, Pittsburgh, PA 15213, USA; Swanson School of Engineering, University of Pittsburgh, Pittsburgh, PA, USA; Veterans Affairs Pittsburgh Healthcare System, Pittsburgh, PA, USA
| | - Paulo Lizano
- Beth Israel Deaconess Medical Center, Harvard Medical School, 75 Fenwood Road, Boston, MA 02115, USA
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27
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Liu L, Cui LB, Xi YB, Wang XR, Liu YC, Xu ZL, Wang HN, Yin H, Qin W. Association Between Connectivity of Hippocampal Sub-Regions and Auditory Verbal Hallucinations in Schizophrenia. Front Neurosci 2019; 13:424. [PMID: 31130837 PMCID: PMC6509236 DOI: 10.3389/fnins.2019.00424] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2018] [Accepted: 04/12/2019] [Indexed: 01/28/2023] Open
Abstract
Background: Hippocampal dysconnectivity has been detected in schizophrenia patients with auditory verbal hallucinations (AVHs). Neuroanatomical evidence has indicated distinct sub-regions in the hippocampus, but which sub-regions within the hippocampus may emerge dysfunction in the brain network, and the relationship between connection strength and the severity of this debilitating disorder have yet to be revealed. Masked independent component analysis (mICA), i.e., ICA restricted to a defined region of interest, can provide insight into observing local functional connectivity in a particular brain region. We aim to map out the sub-regions in the hippocampus with dysconnectivity linked to AVHs in schizophrenia. Methods: In this functional magnetic resonance imaging study of schizophrenia patients with (n = 57) and without (n = 83) AVHs, and 71 healthy controls, we first examined hippocampal connectivity using mICA, and then the correlation between connection metric and clinical severity was generated. Results: As compared with patients without AVHs, mICA showed a group of hyper-connections for the left middle part, as well as another group of hypo-connections for the bilateral antero-lateral and right antero-medial parts in patients with AVHs. Connectivity was linked to the clinical symptoms scores in the sample of patients with AVHs. Conclusion: These findings demonstrate that the left middle part is more densely connected, but the bilateral antero-lateral and right antero-medial parts are more sparsely connected in schizophrenia patients with AVHs. The findings in the present study show proof of precious location in the hippocampus mediating the neural mechanism behind AVHs in schizophrenia.
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Affiliation(s)
- Lin Liu
- School of Life Sciences and Technology, Xidian University, Xi'an, China
| | - Long-Biao Cui
- Department of Clinical Psychology, School of Medical Psychology, Fourth Military Medical University, Xi'an, China
| | - Yi-Bin Xi
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Xing-Rui Wang
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Yu-Chen Liu
- School of Life Sciences and Technology, Xidian University, Xi'an, China
| | - Zi-Liang Xu
- School of Life Sciences and Technology, Xidian University, Xi'an, China
| | - Hua-Ning Wang
- Department of Psychiatry, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Hong Yin
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Wei Qin
- School of Life Sciences and Technology, Xidian University, Xi'an, China
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28
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Cui LB, Cai M, Wang XR, Zhu YQ, Wang LX, Xi YB, Wang HN, Zhu X, Yin H. Prediction of early response to overall treatment for schizophrenia: A functional magnetic resonance imaging study. Brain Behav 2019; 9:e01211. [PMID: 30701701 PMCID: PMC6379641 DOI: 10.1002/brb3.1211] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/06/2018] [Revised: 12/18/2018] [Accepted: 12/19/2018] [Indexed: 12/21/2022] Open
Abstract
INTRODUCTION Treatment response at an early stage of schizophrenia is of considerable value with regard to future management of the disorder; however, there are currently no biomarkers that can inform physicians about the likelihood of response. OBJECTS We aim to develop and validate regional brain activity derived from functional magnetic resonance imaging (fMRI) as a potential signature to predict early treatment response in schizophrenia. METHODS Amplitude of low-frequency fluctuation (ALFF) was measured at the start of the first/single episode resulting in hospitalization. Inpatients were included in a principal dataset (n = 79) and a replication dataset (n = 44). Two groups of healthy controls (n = 87; n = 106) were also recruited for each dataset. The clinical response was assessed at discharge from the hospital. The predictive capacity of normalized ALFF in patients by healthy controls, ALFFratio , was evaluated based on diagnostic tests and clinical correlates. RESULTS In the principal dataset, responders exhibited increased baseline ALFF in the left postcentral gyrus/inferior parietal lobule relative to non-responders. ALFFratio of responders before treatment was significantly higher than that of non-responders (p < 0.001). The area under the receiver operating characteristic curve was 0.746 for baseline ALFFratio to distinguish responders from non-responders, and the sensitivity, specificity, and accuracy were 72.7%, 68.6%, and 70.9%, respectively. Similar results were found in the independent replication dataset. CONCLUSIONS Baseline regional activity of the brain seems to be predictive of early response to treatment for schizophrenia. This study shows that psycho-neuroimaging holds promise for influencing the clinical treatment and management of schizophrenia.
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Affiliation(s)
- Long-Biao Cui
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, China.,School of Medical Psychology, Fourth Military Medical University, Xi'an, China
| | - Min Cai
- Department of Psychiatry, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Xing-Rui Wang
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Yuan-Qiang Zhu
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Liu-Xian Wang
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Yi-Bin Xi
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Hua-Ning Wang
- Department of Psychiatry, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Xia Zhu
- School of Medical Psychology, Fourth Military Medical University, Xi'an, China
| | - Hong Yin
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, China
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