A feasibility study of novel technologies to minimize motion-induced biases in functional and structural MRI of young, opioid-affected cohorts

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PROJECT SUMMARY Opioid exposure, both prenatally and in early childhood, is associated with elevated risk for attention deficit hyperactivity disorder (ADHD), anxiety, low academic performance, and poor health. A major knowledge gap exists in understanding how opioid exposure impacts early brain development, giving rise to risk for adverse developmental outcomes. Neuroimaging studies in young children, ages 3-5, offer an opportunity to quantify developmental processes that are likely implicated in the differing trajectories of opioid-exposed children compared to their non-exposed peers. Unfortunately, the accuracy and reliability of neuroimaging methods in this cohort are not well-established. It is now well known that both structural and functional neuroimaging measures are prone to errors induced by subject motion. Moreover, it is known that many of the comorbid features of opioid exposure are likely to increase children’s in-scanner motion. This is on top of the existing challenges in achieving compliance for imaging studies with healthy, awake children in this age range. In total, this raises substantial concern that existing neuroimaging methods are not sufficiently motion-robust to be used in studies of children ages 3-5. We propose to address these concerns with a feasibility study, comparing the existing methods developed for the Adolescent Brain Cognitive Development (ABCD) study with novel methods we will develop and optimize for young children. We will evaluate our methods in a sample of 100 children, ages 3-5, recruited from the community in Philadelphia that has been hardest hit by the opioid crisis. We will test whether our novel technologies improve the quality of the raw imaging data, and reduce motion biases in the derived morphometric and functional measures. By collecting a broad set of measures on children’s environments (family drug use, family mental health, stress, social support), cognition, and mental health, we will determine predictors of successful imaging in order to inform sampling strategies in future studies of opioid exposure and brain development. Children whose data is more likely to be unusable will need to be oversampled, or statistically up-weighted, to ensure they are appropriately represented in the final sample. Preliminary data will also generate effect sizes for links between opioid exposure and neurocognitive development to inform decisions about imaging sample sizes in future studies. In sum, the primary outcomes of this work will be novel, validated structural and functional neuroimaging imaging methods for young children, and critical feasibility data to inform the design of future large-scale multi-center studies addressing developmental questions, particularly those related to opioid exposure.