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首发精神分裂症的磁共振成像研究进展:选择性综述与国家自然科学基金资助分析

Advances in MRI Research for First-Episode Schizophrenia: A Selective Review and NSFC-Funded Analysis.

作者信息

Yang Qi, Pan Xingchen, Yang Jun, Wang Ying, Tang Tingting, Guo Weisheng, Sun Ning

机构信息

Department of Radiology, The First Hospital of Jilin University, Changchun 130021, China.

Department of Psychiatry, First Hospital of Shanxi Medical University, Taiyuan 030001, China.

出版信息

Schizophr Bull. 2025 Mar 14;51(2):352-365. doi: 10.1093/schbul/sbae175.

Abstract

BACKGROUND AND HYPOTHESES

The causes of schizophrenia remain unclear, and research has been hindered by the lack of quantifiable standards. However, magnetic resonance imaging (MRI) is addressing these challenges, revealing critical neurobiological details and emphasizing its importance in both evaluation and treatment.

STUDY DESIGN

First, we reviewed the progress of research on structural MRI (sMRI), functional MRI (fMRI), multimodal/multiomics analysis, artificial intelligence, and neuromodulation in first-episode schizophrenia (FES) over the past 5 years. Second, we summarize the current state of schizophrenia research funded by the National Natural Science Foundation of China (NSFC) to facilitate academic exchange and cooperation both domestically and internationally.

STUDY RESULTS

sMRI has identified early neurodevelopmental biomarkers in FES patients, and fMRI has highlighted functional abnormalities across disease stages. Multimodal/multiomics analysis has revealed complex brain-neurobiology interactions. Neuromodulation techniques, which directly modulate neural activity in specific brain regions, offer promising long-term benefits for stabilizing conditions and enhancing patients' quality of life. NSFC-funded analysis shows China is increasing its funding for schizophrenia research, though funding distribution remains uneven. The research focus has shifted from a single perspective on brain structure and function to multichannel, multimodal comprehensive analysis methods. This progress has driven the integration of machine learning-driven multiomics research, aiming to construct disease classification models, explore disease mechanisms, and guide treatment from multidimensional and interdisciplinary perspectives.

CONCLUSIONS

MRI technology has provided new perspectives for the diagnosis and treatment of schizophrenia, especially the neurobiological foundations of the disease. Support from the NSFC provides a scientific and financial basis for future research and treatment, heralding scientific discoveries and technological innovations in this field and bringing hope to schizophrenia patients.

摘要

背景与假设

精神分裂症的病因仍不明确,且由于缺乏可量化标准,研究受到阻碍。然而,磁共振成像(MRI)正在应对这些挑战,揭示关键的神经生物学细节,并强调其在评估和治疗中的重要性。

研究设计

首先,我们回顾了过去5年中首发精神分裂症(FES)在结构MRI(sMRI)、功能MRI(fMRI)、多模态/多组学分析、人工智能和神经调节方面的研究进展。其次,我们总结了中国国家自然科学基金(NSFC)资助的精神分裂症研究的现状,以促进国内外的学术交流与合作。

研究结果

sMRI已在FES患者中识别出早期神经发育生物标志物,fMRI突出了疾病各阶段的功能异常。多模态/多组学分析揭示了复杂的脑-神经生物学相互作用。直接调节特定脑区神经活动的神经调节技术,为稳定病情和提高患者生活质量带来了有前景的长期益处。NSFC资助的分析表明,中国对精神分裂症研究的资助在增加,尽管资金分配仍不均衡。研究重点已从对脑结构和功能的单一视角,转向多渠道、多模态的综合分析方法。这一进展推动了机器学习驱动的多组学研究的整合,旨在构建疾病分类模型、探索疾病机制,并从多维和跨学科的角度指导治疗。

结论

MRI技术为精神分裂症的诊断和治疗提供了新的视角,尤其是该疾病的神经生物学基础。NSFC的支持为未来的研究和治疗提供了科学和资金基础,预示着该领域的科学发现和技术创新,并给精神分裂症患者带来希望。

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