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Development of MRI Techniques for Applications in Substance Use Disorders

MRI 技术在药物滥用障碍中应用的发展

基本信息

批准号：
10932026
负责人：
Yihong Yang
金额：
$ 148.11万
依托单位：
NATIONAL INSTITUTE ON DRUG ABUSE
依托单位国家：
美国
项目类别：
财政年份：
资助国家：
美国
起止时间：
至
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10932026
关键词：
10 year old Address Adolescent Adult Affect Anisotropy Attenuated Behavior Behavior assessment Behavioral Brain Categories Cerebrum Characteristics Clinical Cognition Disorders Data Data Set Development Diagnosis Diagnostic Diffusion Diffusion Magnetic Resonance Imaging Dimensions Disease Dose Enrollment Exhibits Fiber Fingerprint Functional Magnetic Resonance Imaging Functional disorder Genetic Variation Heritability Human Impaired cognition Impairment Individual Investigation Journals Link Location MRI Scans Machine Learning Magnetic Resonance Imaging Manuscripts Measures Mental Depression Mental disorders Methamphetamine use disorder Modeling Network-based Neurosciences Obsessive compulsive behavior Obsessive-Compulsive Disorder Pathologic Patients Pattern Positioning Attribute Prediction of Response to Therapy Property Psychiatric therapeutic procedure Psychopathology Psychopharmacology Questionnaires Relapse Research Project Grants Rest Risk Scanning Schizophrenia Self Perception Severities Severity of illness Shapes Short-Term Memory Structure Substance Use Disorder Support System Symptoms System Techniques Testing Therapeutic Effect Training Transcranial magnetic stimulation Treatment Efficacy Treatment outcome Twin Multiple Birth Validation Variant Verbal Auditory Hallucinations Youth addiction adverse childhood events aged cognitive capacity cognitive control cognitive development cognitive function cohort connectome executive function experience follow-up frontier genetic association imaging biomarker indexing male neural neurobiological mechanism neuroimaging neuromechanism neuroregulation novel outcome prediction pediatric trauma preadolescence predictive marker resilience response white matter

项目摘要

1. Brain Functional Connectome Defines a Transdiagnostic Dimension Shared by Cognitive Function and Psychopathology in Preadolescents Cognitive function and general psychopathology are two important classes of human behavior dimensions, individually relate to mental disorders across diagnostic categories. However, whether the two transdiagnostic dimensions link to common or distinct brain networks that convey resilience or risk for the development of psychiatric disorders remains unclear. The current study is a longitudinal investigation with 11,875 youths aged 9- to 10-years-old at study onset, from the Adolescent Brain Cognitive Development study. A machine-learning approach based on canonical correlation analysis was used to identify latent dimensional associations of the resting-state functional connectome with multi-domain behavioral assessments including cognitive functions and psychopathological measures. For the latent rsFC factor showing a robust behavioral association, its ability to predict psychiatric disorders was assessed using two-year follow-up data and its genetic association was evaluated using twin data from the same cohort. A latent functional connectome pattern was identified that showed a strong and generalizable association with the multi-domain behavioral assessments (5-fold cross validation: = 0.680.73, for the training set (N = 5096); = 0.56 0.58, for the test set (N = 1476)). This functional connectome pattern was highly heritable (h2 = 74.42%, 95% CI: 56.76%-85.42%), exhibited a dose-response relationship with cumulative number of psychiatric disorders assessed concurrently and 2-years post-MRI-scan, and predicted the transition of diagnosis across disorders over the 2-year follow-up period. (Manuscript under review) 2. Structural fingerprinting of the frontal aslant tract: predicting cognitive control capacity and obsessive-compulsive symptoms White matter of the human brain is influenced by common genetic variations and shaped by neural activity-dependent experiences. Variations in microstructure of cerebral white matter across individuals and even across fiber tracts might underlie differences in cognitive capacity and vulnerabilities to mental disorders. The frontoparietal and cingulo-opercular networks of the brain constitute the central system supporting cognitive functions, and functional connectivity of these networks has been used to distinguish individuals known as functional fingerprinting. The frontal aslant tract (FAT) that passes through the two networks has been implicated in executive functions. However, whether FAT can be used as a structural fingerprint to distinguish individuals and predict individuals cognitive function and dysfunction is unknown. Here we investigated the fingerprinting property of FAT microstructural profiles using three independent diffusion MRI datasets with repeated scans. We found that diffusion and geometric profiles of FAT can be used to distinguish individuals with a high accuracy. Next, we demonstrated that fractional anisotropy, a widely used index of white matter integrity, in different FAT segments predicted distinct cognitive functions, including working memory, inhibitory control, and relational reasoning. Finally, we assessed the contribution of altered FAT microstructural profiles to cognitive dysfunction in unmedicated patients with obsessive-compulsive disorders. We found that the altered microstructure in FAT was associated with the severity of obsessive-compulsive symptoms. Collectively, our findings suggest that the microstructural profiles of FAT can identify individuals with a high accuracy and may serve as an imaging marker for predicting individuals cognitive capacity and disease severity. (Wang et al., Journal of Neuroscience, in press) 3. Targeting the pathological network: feasibility of network-based optimization of transcranial magnetic stimulation coil placement for treatment of psychiatric disorders It has been recognized that the efficacy of TMS-based modulation may depend on the network profile of the stimulated regions throughout the brain. However, what profile of this stimulation network optimally benefits treatment outcomes is yet to be addressed. The answer to the question is crucial for informing network-based optimization of stimulation parameters, such as coil placement, in TMS treatments. In this study, we aimed to investigate the feasibility of taking a disease-specific network as the target of stimulation network for guiding individualized coil placement in TMS treatments. We present here a novel network-based model for TMS targeting of the pathological network. First, combining E-field modeling and resting-state functional connectivity, stimulation networks were modeled from locations and orientations of the TMS coil. Second, the spatial anti-correlation between the stimulation network and the pathological network of a given disease was hypothesized to predict the treatment outcome. The proposed model was validated to predict treatment efficacy from the position and orientation of TMS coils in two depression cohorts and one schizophrenia cohort with auditory verbal hallucinations. We further demonstrate the utility of the proposed model in guiding individualized TMS treatment for psychiatric disorders. In this proof-of-concept study, we demonstrated the feasibility of the novel network-based targeting strategy that uses the whole-brain, system-level abnormity of a specific psychiatric disease as a target. Results based on empirical data suggest that the strategy may potentially be utilized to identify individualized coil parameters for maximal therapeutic effects. (Cao et al., Frontiers in Neuroscience, 2023) 4. The association between default-mode network functional connectivity and childhood trauma on the symptom load in male adults with methamphetamine use disorder. The relationship between adverse childhood experiences and methamphetamine use disorder (MUD) has been shown in previous studies; nevertheless, the underlying neural mechanisms remain elusive. Childhood trauma is associated with aberrant functional connectivity (FC) within the default-mode network (DMN). Furthermore, within the DMN, FC may contribute to impaired self-awareness in addiction, while cross-network FC is critical for relapse. We aimed to investigate whether childhood trauma was associated with DMN-related resting-state FC among healthy controls and patients with MUD and to examine whether DMN-related FC affected the effect of childhood trauma on the symptom load of MUD diagnosis. Twenty-seven male patients with MUD and 27 male healthy controls were enrolled and completed the Childhood Trauma Questionnaire (CTQ). DMN-related resting-state FC was examined using functional magnetic resonance imaging. There were 47.1% healthy controls and 66.7% MUD patients in this study with adverse childhood experiences. Negative correlations between adverse childhood experiences and within-DMN FC were observed in both healthy controls and MUD patients, while within-DMN FC was significantly altered in MUD patients. The detrimental effects of adverse childhood experiences on MUD patients may be attenuated through DMN-executive control networks (ECN) FC. In conclusion, adverse childhood experiences were negatively associated with within-DMN FC in MUD patients and healthy controls. However, DMN-ECN FC may attenuate the effects of childhood trauma on symptoms load of MUD. (Wei et al., Clinical Psychopharmacology and Neuroscience, in press)

1. 脑功能连接组定义了青春期前认知功能和精神病理学共有的跨诊断维度认知功能和一般精神病理学是人类行为维度的两类重要类别，分别与跨诊断类别的精神障碍相关。然而，这两个跨诊断维度是否与共同或不同的大脑网络相关，这些网络传递了精神疾病的恢复力或发展风险，目前尚不清楚。目前的研究是一项针对 11,875 名 9 至 10 岁青少年的纵向调查，来自青少年大脑认知发展研究。基于典型相关分析的机器学习方法用于识别静息态功能连接组与多领域行为评估（包括认知功能和心理病理学测量）的潜在维度关联。对于显示出强大行为关联的潜在 rsFC 因子，使用两年随访数据评估其预测精神疾病的能力，并使用来自同一队列的双胞胎数据评估其遗传关联。确定了潜在的功能连接组模式，该模式显示出与多域行为评估有很强且可概括的关联（5 倍交叉验证：= 0.680.73，对于训练集（N = 5096）；= 0.56 0.58，对于测试集（N = 1476））。这种功能性连接组模式具有高度遗传性（h2 = 74.42%，95% CI：56.76%-85.42%），与同时评估和 MRI 扫描后 2 年评估的精神疾病累积数量呈现剂量反应关系，并预测 2 年随访期间跨疾病诊断的转变。（稿件正在审核中） 2. 额叶倾斜束的结构指纹：预测认知控制能力和强迫症状人类大脑的白质受到常见遗传变异的影响，并受到神经活动依赖经历的影响。个体之间甚至纤维束之间大脑白质微观结构的差异可能是认知能力和精神障碍脆弱性差异的基础。大脑的额顶叶和扣带盖网络构成了支持认知功能的中央系统，这些网络的功能连接已被用来区分个体，称为功能指纹。通过这两个网络的额叶倾斜束（FAT）与执行功能有关。然而，FAT是否可以作为结构指纹来区分个体并预测个体的认知功能和功能障碍尚不清楚。在这里，我们使用三个独立的扩散 MRI 数据集和重复扫描研究了 FAT 微观结构轮廓的指纹识别特性。我们发现 FAT 的扩散和几何轮廓可以用来高精度地区分个体。接下来，我们证明了分数各向异性（一种广泛使用的白质完整性指标）在不同 FAT 片段中可以预测不同的认知功能，包括工作记忆、抑制控制和关系推理。最后，我们评估了 FAT 微结构特征的改变对未接受药物治疗的强迫症患者认知功能障碍的影响。我们发现 FAT 微观结构的改变与强迫症状的严重程度相关。总的来说，我们的研究结果表明，FAT 的微观结构特征可以高精度地识别个体，并且可以作为预测个体认知能力和疾病严重程度的成像标记。（Wang 等人，《神经科学杂志》，出版中） 3. 瞄准病理网络：基于网络优化经颅磁刺激线圈置入治疗精神疾病的可行性人们已经认识到，基于 TMS 的调制的功效可能取决于整个大脑受刺激区域的网络分布。然而，这种刺激网络的哪种配置最有利于治疗结果仍有待解决。这个问题的答案对于在 TMS 治疗中基于网络的刺激参数（例如线圈放置）优化至关重要。在本研究中，我们旨在探讨以疾病特异性网络作为刺激网络的目标来指导 TMS 治疗中个体化线圈放置的可行性。我们在这里提出了一种基于网络的新型模型，用于 TMS 靶向病理网络。首先，结合电场建模和静息态功能连接，根据 TMS 线圈的位置和方向对刺激网络进行建模。其次，假设特定疾病的刺激网络和病理网络之间的空间反相关性来预测治疗结果。所提出的模型经过验证，可以根据 TMS 线圈的位置和方向来预测两个抑郁症队列和一个出现幻听的精神分裂症队列的治疗效果。我们进一步证明了所提出的模型在指导精神疾病个体化 TMS 治疗方面的实用性。在这项概念验证研究中，我们证明了基于网络的新型靶向策略的可行性，该策略使用特定精神疾病的全脑、系统级异常作为目标。基于经验数据的结果表明，该策略有可能用于识别个体化线圈参数以获得最大治疗效果。（Cao 等人，《神经科学前沿》，2023） 4. 默认模式网络功能连接与童年创伤对患有甲基苯丙胺使用障碍的成年男性症状负荷的关联。先前的研究已表明不良童年经历与甲基苯丙胺使用障碍（MUD）之间的关系；然而，潜在的神经机制仍然难以捉摸。童年创伤与默认模式网络（DMN）内的异常功能连接（FC）有关。此外，在 DMN 内，FC 可能会导致成瘾的自我意识受损，而跨网络 FC 对于复发至关重要。我们的目的是调查健康对照者和 MUD 患者中童年创伤是否与 DMN 相关静息态 FC 相关，并检查 DMN 相关 FC 是否影响童年创伤对 MUD 诊断症状负荷的影响。 27 名患有 MUD 的男性患者和 27 名男性健康对照者被纳入并完成了儿童创伤问卷 (CTQ)。使用功能磁共振成像检查 DMN 相关的静息态 FC。本研究中有 47.1% 的健康对照者和 66.7% 的 MUD 患者有不良童年经历。在健康对照和 MUD 患者中均观察到不良童年经历与 DMN 内 FC 之间呈负相关，而 MUD 患者中 DMN 内 FC 显着改变。不良童年经历对 MUD 患者的不利影响可以通过 DMN 执行控制网络 (ECN) FC 来减轻。总之，MUD 患者和健康对照者的不良童年经历与 DMN 内 FC 呈负相关。然而，DMN-ECN FC 可能会减弱童年创伤对 MUD 症状负荷的影响。（Wei 等人，临床精神药理学和神经科学，待出版）