1- Biological determinants of opioid craving in pain patients: Opioid craving (i.e., the subjective desire to consume opioids) is one of the strongest predictors of opioid misuse among patients with chronic pain. A better understanding of the factors determining opioid craving is therefore among the most promising targets for opioid misuse prevention. Several studies have established that opioid craving in chronic pain patients is only weakly correlated with the intensity of the pain, indicating that craving for opioids may be best explain by other psychological or neurobiological factors. Our lab aims to shed light on the neurobiological factors associated with opioid craving in chronic pain patients. This will be achieved by conducting a cross-sectional observational study among patients that received prescribed opioids in the context of their medical care in a tertiary pain management setting.
Chronic pain and substance use disorders have both been associated with severe impairments in the mesolimbic dopaminergic system that dampens the ability to feel pleasure and reduces the motivation to pursue normal activities. Here, positron emission tomography (PET) will be used to respectively measure dopamine D2 receptor availability in subregions of the striatum (ventral; dorsal, and posterior dorsal).
2- Derive brain-based markers for chronic pain: The cause of chronic pain remains elusive as tissue damage following injury is a poor predictor of persisting pain. This makes the diagnosis and prognosis of pain conditions challenging for clinicians. There is therefore a need for developing better diagnostic and prognostic tools to efficiently and accurately identify and predict the development of chronic pain. Unfortunately, there is currently no available clinically useful biomarker available for diagnosis and prognostication of chronic pain. To date, no brain imaging studies have been optimally designed to predict clinical outcomes about chronic pain. Past attempts to develop brain-based biomarkers for chronic pain were hindered by small datasets, limiting the generalizability of the predictions.
Our access to large healthcare databases (curated UKBiobank and Open Pain) will allow us to train and validate biomarkers on an amount of data rarely available to typical brain imaging studies. We expect to develop brain-based biomarkers capable of making clinically relevant predictions regarding the presence and the severity of chronic pain that will generalize to various clinical populations. Developing a biomarker for chronic pain would represent a major advancement for objectively detecting pain, identifying individuals at risk of developing pain, and assessing drug efficacy in randomized controlled trials (RCTs).
3- Mapping brain pathways using high field MRI: Recent methodological advances in fMRI using higher field strength of 7-Tesla demonstrate that the brain activity can be reliability measure across the different layers of the human cortex. This spatial resolution provides unprecedented opportunities to map the human brain circuitries and improve our understanding of its organization. So far, layer dependant fMRI has been applied to multiple primary sensory cortices, such as the visual, the auditory, and the motor cortices. More recently, layer fMRI has been applied to complex cognitive task to show that superficial layers of the dorsolateral prefrontal cortex are activated in the manipulation of information and deep layers are activated during the response during a working memory task. To our knowledge, layer fMRI has never been applied to understand how pain is processed by the human brain. This is important because pain is processed across a distributed set of regions and our understanding of the pain pathways in the human brain remains limited. Here, we propose to study the organization of the core pain system and its functional connectivity with other pain-processing regions.