Neuroinflammation caused by infection, oxidative stress or perinatal asphyxia leads to hypoxic ischemic encephalopathy (HIE) in term infants and white and gray matter (WM, GM) injury in preterm infants with potentially irreparable tissue damage, incurring life-long neurological burdens such as cerebral palsy. Habilitative therapies are often delayed until infants fail developmental milestones. A consensus panel recommended combined early neuroimaging and developmental testing for earlier referrals to therapy, potentially mitigating these risks. Therefore, it is essential the field explores methods for more sensitive and accurate quantification of brain injury in the developing neonatal brain. A practical and non-invasive technique to study microstructural tissue changes in the brain is diffusion MRI (dMRI). The primary goal of this F31 proposal is to determine, in term HIE and preterm infants, whether or not quantitative parameters derived from novel advanced dMRI techniques correlate to disease severity and predict long-term outcome. This will be supported by a research training plan targeted at didactic and hands-on training in diffusion physics and MRI (mentor: Jensen), neonatal neurodevelopment (mentor: Jenkins) and radiological assessment (mentor: Chatterjee). Project feasibility is enhanced through on-going collaborations among the Neuroscience, Neonatology and Radiology divisions, as well as its status as part of an on-going protocol within Dr. Jenkins? team with assistance from the Center for Biomedical Imaging (CBI) at MUSC.
AIM 1 and AIM 2 will analyze existing dMRI data using a technique known as diffusional kurtosis imaging (DKI) acquired in 50 term HIE and 23 preterm infants. In addition to DKI, prospective dMRI data will be collected utilizing another technique known as fiber ball imaging (FBI) in ongoing clinical imaging protocols in 30 term HIE neonates and 23 preterm infants. These dMRI methods will be compared and combined to predict short-term (0-3 month) and long-term (12 and 18-24 month) developmental outcomes routinely collected as standard-of-care. A more sophisticated dMRI analysis approach, automated fiber quantification (AFQ), will be investigated in AIM 3 to create subject specific white matter (WM) tract profiles. With these research aims, I will fulfill three, interconnected training goals. First, I will train in the physics of diffusion and how brain water diffusion is imaged with MRI, supported by the quantum mechanics and E&M that I will study. Second, I will learn about the physiology of neurodevelopment, the pathophysiology of ischemic injury to the brain parenchyma, and the clinical importance of advanced imaging biomarkers, including dMRI, in both term HIE and preterm infants. Finally, gaining experience in the statistical methods used in translational research will provide me with the knowledge to appropriately test hypothesis driven research. With these research and training opportunities alongside leading clinicians and researchers who are advancing clinical practice through MR imaging, I aim to become an adept translational MR physicist and independent investigator.
The primary goal of this research proposal is to demonstrate the potential of advanced diffusion MRI (dMRI) for improving clinical management of term and preterm neonatal brain injury by testing its ability to predict short- and long-term outcomes, and its relation to disease severity. dMRI allows the non-invasive evaluation of microstructure integrity in injured developing brain tissue with potentially greater diagnostic accuracy than current methods. We anticipate that these novel dMRI techniques may offer substantial improvements in prognostication for term and preterm patients suffering from neonatal brain injury.
