Longitudinal Examination of Abstinence Maintenance and Relapse in Cigarette Smokers

项目摘要：美国大约有百分之十五的人吸烟。尽管多次 大多数戒烟尝试在一年内失败。预测谁将无法留下来 戒烟将通过提供有关复吸的客观反馈来改善戒烟结果 风险，并允许更有效地分配预防复发的资源。我们自己的试点数据和最近的 文献综述表明，使用神经影像学方法确定复发生物标志物的前景相当可观 接近。虽然一些研究已经开始调查复发预测，很少，如果有任何研究有考试- 在达到最初的戒断后，纵向地记录了复发或延长戒断的过程。 这项建议的重点是获得神经影像学标记物，前瞻性地预测随后的复发， 以及了解大脑如何改变以支持持续的禁欲。为了实现这一目标 在一个项目中，50名在过去三到六个月内戒烟的前吸烟者将完成功能性磁共振成像扫描 在基线和3个月、6个月和9个月随访ses时， 目的是鉴定那些在复发前随时间稳定的生物标志物。神经预测未来 在那些最近尝试戒烟的人中复发对患者来说可能是极其重要的， 根据复发风险进行治疗匹配和/或差别资源分配。此外，通过识别 恢复后大脑功能发生的变化，可能有可能以大脑相关网络为目标 刺激技术

Project Summary: Approximately fifteen percent of individuals in the US smoke cigarettes. Despite multiple attempts to quit, most smoking cessation attempt fails within one year. Predicting who will be unable to remain abstinent from smoking would improve cessation outcomes by providing objective feedback regarding relapse risk and allowing for more efficient allocation of relapse prevention resources. Our own pilot data and recent reviews of the literature suggest considerable promise in identifying biomarkers for relapse using neuroimaging approaches. While some studies have begun to investigate relapse prediction, few, if any studies have exam- ined the process of relapse or prolonged abstinence longitudinally after initial abstinence has been achieved. The focus of this proposal is to derive neuroimaging markers that prospectively predict subsequent relapse as well as to understand how the brain changes to support continued abstinence. To accomplish the aims of this project, 50 former smokers who have quit within the last three to six months will complete functional MRI scans of cognitive control, cue reactivity, and intrinsic connectivity at baseline and at 3-, 6-, and 9-month follow-up ses- sions to identify those biomarkers that are stable over time prior to relapse. Deriving neural predictors of future relapse among those individuals who have recently made a quit attempt could be extremely important for patient- treatment matching and/or differential allocation of resources based on risk for relapse. In addition, by identifying the changes that occur in brain function after recovery, it may be possible to target relevant networks with brain stimulation techniques.