Creating dynamic images of short-lived dopamine fluctuations with lp-ntPET: dopamine movies of cigarette smoking.
Creating dynamic images of short-lived dopamine fluctuations with lp-ntPET: dopamine movies of cigarette smoking.
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DOI：
10.3791/50358
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发表时间：
2013-08-06
期刊：
影响因子：
--
通讯作者：
Cosgrove KP
中科院分区：
文献类型：
--
作者：
Morris ED;Kim SJ;Sullivan JM;Wang S;Normandin MD;Constantinescu CC;Cosgrove KP
我们描述了从动态PET数据创建大脑多巴胺电影的实验和统计步骤。这些电影表现了吸烟引起的多巴胺每分钟的波动。吸烟者在自然吸烟体验中被成像，而其他可能的混杂影响(如头部运动、期望、新奇或对重复吸烟的厌恶)被最小化。我们介绍了我们独特的分析的细节。常规的PET分析方法估计时不变的动力学模型参数，不能捕捉神经递质释放的短期波动。我们的分析--产生一部多巴胺电影--是基于我们使用动力学模型和其他分解技术所做的工作，这些技术允许参数1-7随时间变化。分析的这一方面--时间变化--是我们工作的关键。因为我们的模型在参数上也是线性的，所以在计算上应用于体素级别是实用的。该分析技术包括五个主要步骤：预处理、建模、统计比较、掩蔽和可视化。利用减少空间噪声但保留关键时间信息的独特的‘HYPR’空间滤波器8对PET数据进行预处理。模型确定了最能描述多巴胺对11C-拉氯普利摄取的影响的时变函数。统计步骤将我们的(LP-ntPET)模型7与传统模型9的适合性进行比较。掩蔽将治疗限制在新模型最好描述的体素。可视化将每个体素的多巴胺功能映射到一个色标，并产生一部多巴胺电影。介绍了吸烟的中期结果和多巴胺样片。
We describe experimental and statistical steps for creating dopamine movies of the brain from dynamic PET data. The movies represent minute-to-minute fluctuations of dopamine induced by smoking a cigarette. The smoker is imaged during a natural smoking experience while other possible confounding effects (such as head motion, expectation, novelty, or aversion to smoking repeatedly) are minimized. We present the details of our unique analysis. Conventional methods for PET analysis estimate time-invariant kinetic model parameters which cannot capture short-term fluctuations in neurotransmitter release. Our analysis - yielding a dopamine movie - is based on our work with kinetic models and other decomposition techniques that allow for time-varying parameters 1-7. This aspect of the analysis - temporal-variation - is key to our work. Because our model is also linear in parameters, it is practical, computationally, to apply at the voxel level. The analysis technique is comprised of five main steps: pre-processing, modeling, statistical comparison, masking and visualization. Preprocessing is applied to the PET data with a unique 'HYPR' spatial filter 8 that reduces spatial noise but preserves critical temporal information. Modeling identifies the time-varying function that best describes the dopamine effect on 11C-raclopride uptake. The statistical step compares the fit of our (lp-ntPET) model 7 to a conventional model 9. Masking restricts treatment to those voxels best described by the new model. Visualization maps the dopamine function at each voxel to a color scale and produces a dopamine movie. Interim results and sample dopamine movies of cigarette smoking are presented.
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影响因子：
3.1
作者：
Morris, Evan D.;Normandin, Marc D.;Schiffer, Wynne K.
通讯作者：
Schiffer, Wynne K.
影响因子：
6.3
作者：
Finnema, Sjoerd J.;Varrone, Andrea;Farde, Lars
通讯作者：
Farde, Lars
影响因子：
5.7
作者：
Gunn, RN;Lammertsma, AA;Cunningham, VJ
通讯作者：
Cunningham, VJ
DOI：
10.1097/00004647-199601000-00005
发表时间：
1996-01-01
影响因子：
6.3
作者：
Lammertsma, AA;Bench, CJ;Frackowiak, RSJ
通讯作者：
Frackowiak, RSJ
影响因子：
2.3
作者：
Barrett, SP;Boileau, I;Dagher, A
通讯作者：
Dagher, A