基于精神分裂症公认认知成套测验(MCCB)的多模态脑影像标志鉴定

The long-standing cognitive impairments are recognized as one of the core function deficits of schizophrenia (SZ), which are also the main reasons that SZ patients can not successfully re-entering the community. Currently, MCCB (MATRICS Consensus Cognitive Battery) is recognized as the most valuable clinical tool for comprehensive cognitive function evaluation of schizophrenia, which contains neurophysiologic tests in 7 domains, including 1) speed of processing, 2) attention/ vigilance, 3) working memory, 4) verbal learning, 5) visual learning, 6) reasoning /problem solving, and 7) social cognition. However, to the best of our knowledge, most of the MCCB studies are pure clinical assessments to verify the test re-test reliability of this tool, few of them adopted magnetic resonance imaging (MRI); on the other hand, most MRI studies related to SZ cognitive deficits focus on only one cognitive domain, not all of the seven. Namely, the identification of multimodal brain imaging biomarkers of schizophrenia cognitive deficits based on MCCB has not been carried out yet. Therefore, in this project, we are motivated to combine fMRI, sMRI and DTI to explore the neuroimaging markers related to MATRICS composite score and its 7 specific cognitive domain scores. We will develop a set of novel multimodal fusion approaches that can combine multiple types of diverse brain imaging data, aiming to thoroughly investigate the abnormal brain regions or various brain network properties that significantly associate with MCCB. By combing brain functional, structural, and anatomical information, we aim to generate a full perspective of cognitive function impairments in schizophrenia patients, so as to obtain the multimodal neuroimaging "targets" related to MCCB. In summary, this interdisciplinary project aims at the frontiers of international neuroimaging research, requires considerable expertise of math, computer science and psychiatric knowledge. Completion of this project will provide a set of quantitative, reliable biomarkers that could reflect the core function deficits of schizophrneia, which may have an ground-breaking impact on the long-term cognition recovery of SZ patients, and may make significant contribution to help SZ patients re-entering the community and to reduce the burden of families and the whole society.

认知功能的持久性损伤被认为是精神分裂症的核心特征之一，也是患者不能重新回归社会的主要原因。基于MATRICS的公认认知成套测验(MCCB)是目前精神分裂症认知功能临床评估中最具价值的测验工具, 能全面系统的对7种认知领域进行测评。然而针对MCCB的绝大多数研究仅仅是临床评分，与认知相关的脑影像研究又常常集中于一个认知领域；即国际上基于MCCB的综合认知能力的多模态脑影像研究尚未展开。本项目拟通过开发先进的多模态脑影像融合理论与网络分析方法，发掘针对MATRICS总分和7个认知领域的脑影像特征映射，将脑结构、脑连接、脑功能等多模态信息整合成一个反映精神分裂症认知缺损机制的全景图。获取针对精分患者综合认知障碍的多模态神经影像靶点，提供一系列可量化的"生物标志"。该理工医交叉课题瞄准国际科学前沿，有可能使精神分裂症患者的长期预后出现革命性的突破，为其有效的回归社会、减轻家庭和社会负担做出重要贡献。

认知功能的持久性损伤被认为是精神分裂症的核心特征之一，也是患者不能重新回归社会的主要原因。基于MATRICS 的公认认知成套测验(MCCB)是目前精神分裂症认知功能临床评估中最具价值的测验工具, 能全面系统的对7 种认知领域进行测评。然而针对MCCB的绝大多数研究仅仅是临床评分，与认知相关的脑影像研究又常常集中于一个认知领域；即国际上基于MCCB 的综合认知能力的多模态脑影像研究尚未展开。本项目开发了一系列先进的多模态脑影像融合理论与网络分析方法，在Nature communications, Brain, Biological Psychiatry共发表论文专利49篇，其中影响因子10分以上3篇，SCI论文35篇，EI 检索8篇，申请发明专利2项，收集健康对照和精分患者各100例。发掘了针对MATRICS 总分和7个认知领域的脑影像特征映射，将脑结构、脑连接、脑功能等多模态信息整合成一个反映精神分裂症认知缺损机制的全景图。获取了一组针对精分患者综合认知障碍的多模态神经影像靶点，并能够在多个中心实现交叉验证。该理工医交叉课题瞄准国际科学前沿，培养了3名博士生，3名硕士生，为业内提供了一系列创新的多模态影像分析工具，有望普及到多种脑疾病的应用中。