A number of neuropsychiatric disorders, including psychotic spectrum disorders (PSD), have been associated with developmental changes in brain structure and function. Adolescence is a period of special importance, with alterations of synaptic pruning and myelination trajectories proposed as neural mechanisms underlying PSD. There is also a growing interest in ways that neurodevelopmental changes may be leveraged as treatment targets. Unfortunately, such efforts are limited by the technology currently available for monitoring microstructural change. Neuroimaging is ideal for investigating in-vivo developmental changes, due to its non- invasive nature. However, the measures used are often indirect, and the extent to which they are sensitive to neural microstructure is not always clear. Accordingly, the imaging methods community continues to develop increasingly sophisticated techniques to improve our estimation of tissue characteristics, but there is often substantial delay in translating new methodologies to clinical populations. One modality that has the potential to improve our understanding of brain microstructure is multishell diffusion weighted imaging (mDWI). One emerging mDWI method is neurite orientation dispersion and density imaging (NODDI), which can yield sophisticated estimates of microstructural architecture. In particular, NODDI allows estimation of three factors relevant to development: neurite orientation, reflecting dendritic density and the complexity of dendritic branching, neurite density, which is correlated with myelination, and cellular density. Although these measures are relevant to many neuropsychiatric disorders, this technique has not been broadly adopted, with little existing work using NODDI in PSD and no work in adolescent or young adult patients. This project will employ NODDI as well as standard structural grey and white matter imaging measures in a sample of healthy adolescents and adolescents with PSD (age 12-18), in order to establish the utility of NODDI as a measure of synaptic pruning and myelination. First, the degree to which NODDI measures are similar or different to standard measures of grey matter thickness and white matter integrity will be assessed. Secondly, whether NODDI measures are sensitive to differences in pruning across adolescence by comparing cross sectional age related differences between groups. And the final assessment will be whether NODDI is more or differently sensitive than standard measures by testing if it is more predictive of chronological age, functional connectivity, and patient status. If successful, this project would establish evidence that NODDI provides unique information that may be valuable for investigating neuropsychiatric disorders, and further, that the measure can detect maturational differences between diagnostic groups, which could impact how clinical researchers perform diffusion imaging moving forward. In addition to the impact on the larger clinical imaging field, these analyses can also have an impact on the field of psychosis in particular, by helping to fully and accurately characterize microstructural neurodevelopment to target new avenues of treatment for psychosis.
There is a growing interest in considering how neurodevelopmental trajectories may differ in neuropsychiatric disorders such as schizophrenia, and further, how developmental changes may potentially be leveraged as treatment targets. However, current neuroimaging measures used are indirect, and the extent to which they accurately represent the underlying neural microstructure (and developmental changes in microstructure) is not always clear; although new methods are being developed, they are not being translated into clinical populations. Here we intend to employ one recently developed method, neurite orientation dispersion and density imaging (NODDI), which uses multi-shell diffusion weighted imaging data to putatively make better estimates of microstructural architecture, and deploy it to understand the differences in microstructural development in adolescents with psychotic spectrum disorders.
