Multivariate Machine Learning to Characterize Opioid-induced Alterations in the Brain in Chronic Pain

项目摘要/摘要 处方阿片类药物是治疗疼痛的一类有效药物。然而，越来越多的研究已经 描述了长期(90天)使用阿片类药物对慢性疼痛患者的医源性后果，包括 痛觉过敏和执行功能受损。多巴胺是执行功能的关键调节器。而当 疼痛和行为的变化已经被注意到，对大脑的形态、神经和 随着长期处方阿片类药物使用而随时间变化的多巴胺能活动。与NIDA一致 战略计划目标1.3，这份K25提案寻求“确定药物使用、成瘾和康复的影响 关于大脑回路、行为和健康的研究“使用神经成像信息工具。具体地说，本研究 结合了多层次的研究，包括结构和功能磁共振成像(MRI)， 正电子发射断层扫描(PET)、定量感觉测试(QST)和神经心理学 评估执行功能，并使用机器学习技术进行分析以确定影响 长期服用处方阿片类药物对慢性疼痛患者大脑的影响。申请者将使用她的预付款 具备神经成像数据分析和建模方面的量化技能，以及在QST培训方面的经验 认知神经心理学、慢性疼痛和成瘾流行病学制定独立研究计划 并成功地竞争未来的R01资金。实现所需的培训，以促进 在这项调查中，申请人咨询了一位慢性疼痛研究和阿片类药物治疗的专家， 物质滥用专家、神经心理学家、流行病学家、成像科学家和机器 神经影像领域的学习领导者，制定创新的学习和培训计划。40例患者的A 长期服用阿片类药物的诊断同质性慢性疼痛状况(即慢性下腰痛；CLBP) 与40名阿片类药物单纯CLBP患者相比，将研究治疗以实现以下目标：1) 在同时疼痛和执行期间测量疼痛、认知表现、神经和多巴胺能活动 功能任务fMRI-PET以表征阿片类药物对CLBP疼痛处理和执行功能的影响； 2)测量静息状态下的固有脑活动fMRI-PET，以确定相关的固有脑改变 长期使用阿片类药物的CLBP；3)应用高分辨率结构磁共振测量阿片类药物诱导的 CLBP的形态变化。本研究的创新之处在于将QST与神经网络相结合。 通过多模式成像和复杂的统计方法进行心理测量。这一点意义重大 因为它对解决NIDA战略计划目标采取了全面的方法。调查结果成立 为有关疼痛护理和阿片类药物处方以及风险缓解的医疗决策提供信息 战略。所获得的研究、培训和成果将为申请者的长期科学发展提供平台 成为独立的R01资助、教职员工级别的首席调查员的研究目标 转化性疼痛研究旨在开发具有临床应用价值的神经影像工具。

PROJECT SUMMARY/ABSTRACT Prescription opioids are a potent class of drugs for treating pain. However, growing body of research has described iatrogenic consequences of long-term (> 90 days) opioid use in patients with chronic pain including hyperalgesia and impaired executive function. Dopamine is a critical modulator of executive function. While changes in pain and behavior have been noted, little is known about the brain’s morphology, neural and dopaminergic activity that change over time with long-term prescription opioid use. Consistent with the NIDA Strategic Plan objective 1.3, this K25 proposal seeks to “establish the effects of drug use, addiction, and recovery on brain circuits, behavior, and health” using neuroimaging-informed tools. Specifically, the present study combines multiple levels of investigation, including structural and functional Magnetic Resonance Imaging (MRI), Positron Emission Tomography (PET), Quantitative Sensory Testing (QST) and neuropsychological assessments of executive function, and employ machine learning techniques for analysis to identify the effects of long-term prescription opioid use on the brain in chronic pain patients. The applicant will use her advanced quantitative skills in neuroimaging data analysis and modeling to training in QST, and experience in cognitive neuropsychology, epidemiology of chronic pain and addiction to develop an independent research plan in translational pain and successfully compete for future R01 funding. To achieve the training needed to facilitate this investigation, the applicant has consulted with an expert in chronic pain research and opioid therapy, a substance abuse specialist, a neuropsychologist, an epidemiologist, an imaging scientist, and a machine learning leader in neuroimaging field to develop an innovative study and training plan. 40 patients with a diagnostically homogeneous chronic pain condition (i.e., chronic low back pain; CLBP) on long-term opioid therapy, as compared to 40 opioid-naïve CLBP patients, will be studied to achieve the following Aims: 1) Measure pain, cognitive performance, neural and dopaminergic activity during concurrent pain and executive function task fMRI-PET to characterize the effects of opioids on pain processing and executive function in CLBP; 2) measure intrinsic brain activity during resting state fMRI-PET to identify intrinsic brain alterations associated with long-term opioid use in CLBP; and 3) apply high-resolution structural MRI to measure opioid-induced morphological changes in CLBP. This research is innovative in its use of combined QST and neuro- psychological measures with multimodal imaging and sophisticated statistical approaches. It is significant because of its comprehensive approach towards addressing the NIDA Strategic Plan objective. Findings stand to inform medical decision-making regarding pain care and opioid prescription, as well as risk mitigation strategies. The research, training and results obtained will provide a platform for applicant’s long-term scientific research goal of becoming an independent R01-funded, faculty-level principal investigator performing translational pain research aimed at developing neuroimaging tools to have clinical application.