Multivariate Modeling of the Neural Mechanisms of Treatment Response in Opioid Addiction

项目摘要/摘要 拟议的K01项目将使用多模式磁共振成像(MRI)和机器学习(ML) 阐明青壮年阿片类药物使用障碍治疗失败的神经认知过程 (有声)。年轻人服用过量阿片类药物的风险特别高，而且是致命的。月度注射剂 缓释阿片类拮抗剂纳曲酮(XR-NTX)是一种高效的治疗药物，尤其是 非常适合年轻人。然而，XR-NTX依从性和复发率显示出相当大的个体差异， 与这种变异性相关的行为和临床因素仍然没有定论。以前的研究 已经证明了多模式MRI和ML技术用于阐明神经认知因素的潜力 这对治疗反应的贡献超出了行为和临床措施。这个项目将利用 对预测XR-NTX治疗的大脑结构和功能进行建模的尖端MRI和ML方法 患有先天性巨结肠的青壮年的结局。这项研究将评估18-34岁的OUD患者在治疗前和治疗中的情况 XR-NTX治疗的前三个月，这段时间与治疗中途辍学率最高相关。 主要结果将是每周尿毒学和自我报告证实的阿片类药物复发。第二个 结果将是未坚持，定义为未能完成前三次注射。这项研究将集中在 可能预测治疗反应的大脑结构和功能的五项基线测量：1) 灰质体积；2)与腹侧纹状体的功能连接；3)对阿片类药物提示的反应性；4)抑制 控制；5)自我评价。ML技术将用于揭示大脑结构/功能的模式 它们与每个结果变量相关联。根据文献和初步调查结果，我们预计 将MRI与行为和临床评估相结合将更好地解释XR-NTX的个体变异性 对患有OUD的年轻人的治疗结果，而不是仅使用行为和临床变量。数据 将揭示在这一关键人群中导致治疗失败风险的新的大脑机制。这个 该项目还将作为施振豪医生提高临床和计算技能的培训工具 并促进他独立的事业发展。具体地说，它将使史博士实现五项培训 目标：1)增进临床研究方法论方面的知识；2)获得临床研究的实践经验 主导临床项目；3)掌握ML和多元方法学；4)应用多模式MRI 翻译和临床研究的技术；以及5)提高他的一般独立研究技能 包括领导力、网络、协作、科学写作和英勇无畏。通过组合 教学和实践活动，该项目将满足史博士的培训需求，并使他能够过渡到 成功和独立的研究生涯，将先进的计算方法应用于 物质使用障碍及其治疗的神经科学研究。

PROJECT SUMMARY/ABSTRACT The proposed K01 project will use multimodal magnetic resonance imaging (MRI) and machine learning (ML) to elucidate the neurocognitive processes underlying treatment failure in young adults with opioid use disorder (OUD). Young adults are at particularly high risk of OUD and fatal opioid overdose. The monthly injectable extended-release opioid antagonist naltrexone (XR-NTX) is a highly effective OUD treatment and is particularly well suited for young adults. However, XR-NTX adherence and relapse show considerable individual variability, and the behavioral and clinical factors associated with such variability remain inconclusive. Previous research has demonstrated the potential for multimodal MRI and ML techniques to elucidate the neurocognitive factors that contribute to treatment response beyond behavioral and clinical measures. This project will take advantage of the cutting-edge MRI and ML methods to model brain structures and functions that predict XR-NTX treatment outcomes in young adults with OUD. The study will evaluate 18–34 year-old OUD patients before and during the first three months of XR-NTX treatment, a period associated with the highest rate of dropout from treatment. The primary outcome will be opioid relapse confirmed by weekly urine toxicology and self-report. The secondary outcome will be non-adherence defined as failure to complete the first three injections. The study will focus on five baseline measures of brain structures and functions that are potentially predictive of treatment response: 1) grey matter volume; 2) functional connectivity with the ventral striatum; 3) reactivity to opioid cues; 4) inhibitory control; and 5) self-evaluation. ML techniques will be used to reveal the patterns of brain structures/functions that are associated with each outcome variable. Based on literature and preliminary findings, we anticipate that combining MRI with behavioral and clinical assessments will better account for individual variability in XR-NTX treatment outcomes in young adults with OUD, than using the behavioral and clinical variables alone. The data will unveil novel brain mechanisms that contribute to the risk of treatment failure in this critical population. The project will also serve as a training vehicle for Dr. Zhenhao Shi to improve his clinical and computational skills and facilitate his independent career development. Specifically, it will enable Dr. Shi to achieve five training goals: 1) to advance his knowledge in the methodology of clinical research; 2) to gain hands-on experience in leading clinical projects; 3) to master ML and multivariate methodologies; 4) to apply multimodal MRI techniques to translational and clinical research; and 5) to advance his general independent research skills including leadership, networking, collaboration, scientific writing and grantsmanship. Through a combination of didactic and hands-on activities, the project will fulfill Dr. Shi's training needs and enable his transition to a successful and independent research career in applying advanced computational approaches to the neuroscience research of substance use disorders and their treatments.