Cigarette smoking is a serious addiction that continues to cost the country dearly, both monetarily and in terms of lost productivity and premature death (U.S. Dept. of Human Services, 2008). Microdialysis studies in animals administered nicotine (iv or sc) indicate that nicotine induces dopamine (DA) release (Di Chiara and Imperato, 1988) and this response is believed to be central to the addictive quality of the drug (Imperato et al., 1986). Positron Emission Tomography (PET) imaging of human smokers has a role to play in the much-needed development of new medications for smoking cessation that work through the DA system. For PET to be maximally useful, however, will require new types of image analysis that yield endpoints that are sensitive to smoking-induced DA effects that are highly localized in time and/or space. Conventional methods of analysis of PET scans with displaceable D2-receptor tracers (i.e., that are sensitive to fluctuations in DA) typically rey on averaging data over time, via calculation of changes in Binding Potential (BP), or over space, via region-of-interest (ROI) analysis. We have recently introduced a new type of PET image analysis ('ntPET') whose endpoint is a dynamic sequence of dopamine images that does not rely on ROI-wide phenomena but is sensitive to transient effects of DA. Rather, it is a voxel-based-method which does not rely on time-averaging or equilibrium, as is the case for calculation of BP. We present the first instance of a """"""""dynamic dopamine image"""""""" (DDI) of the response to smoking in the current proposal. We have preliminarily demonstrated that the DDI contains the individual responses at the voxel level in the striatum to smoking multiple cigarettes in the PET scanner. The DDI has the potential to be a detailed spatio- temporal biomarker of the effect of smoking cigarettes on the brain's DA system. We envision using such a biomarker as an indicator of the progression of dependence or the response to therapy. As with the development of any new method, a key question to ask is whether or not the output of the method is reproducible. The primary goal of the current proposal is to address the issue of reproducibility. We have configured a test/retest imaging paradigm with dependent smokers to quantify the consistency and reproducibility of the DDI of smoking in each individual from one scan session to the next. We believe that the proposed project is well constructed to test and validate a new tool that could, in turn, aid in the understanding and treatment of smoking.
In this study, we will use newly established mathematical techniques to produce detailed, time-sequences of images of the brain's dopamine system responding to cigarette smoking. The images, which have not been created before, will be derived from dynamic PET imaging data and will reveal much new information about the location and timing of the dopaminergic response to smoking in the brains of dependent smokers. The primary goal of the study will be to investigate how reproducible are the series of dopamine images and thus to gauge how useful they might be as a new tool for understanding the neurochemistry of smoking.
|Wang, Shuo; Kim, Sujin; Cosgrove, Kelly P et al. (2017) A framework for designing dynamic lp-ntPET studies to maximize the sensitivity to transient neurotransmitter responses to drugs: Application to dopamine and smoking. Neuroimage 146:701-714|
|Kim, Su Jin; Sullivan, Jenna M; Wang, Shuo et al. (2014) Voxelwise lp-ntPET for detecting localized, transient dopamine release of unknown timing: sensitivity analysis and application to cigarette smoking in the PET scanner. Hum Brain Mapp 35:4876-91|
|Cosgrove, Kelly P; Wang, Shuo; Kim, Su-Jin et al. (2014) Sex differences in the brain's dopamine signature of cigarette smoking. J Neurosci 34:16851-5|
|Sullivan, Jenna M; Kim, Su Jin; Cosgrove, Kelly P et al. (2013) Limitations of SRTM, Logan graphical method, and equilibrium analysis for measuring transient dopamine release with [(11)C]raclopride PET. Am J Nucl Med Mol Imaging 3:247-60|