Diseases of the central nervous system are a significant public health and economic problem, affecting nearly one in three Americans at some point in life, with a cost exceeding $500 billion per year. Both demyelination and axonal loss are common pathological features of most human neurological diseases/injuries including multiple sclerosis (MS), leukodystrophy, traumatic brain injury, as well as of normal aging and neurodegenerative diseases such as Parkinson's, Huntington's, amyotrophic lateral sclerosis, and Alzheimer's disease (AD). Axonal loss is considered the cause of permanent disability, while demyelination has been shown to be a reversible process. However, it is often unclear what degrees of demyelination and axonal loss are present in individual patients, and whether these neurodegenerative processes are successfully modified by a given therapeutic agent. Hence, quantitative, noninvasive biomarkers of both demyelination and axonal loss would improve accuracy of diagnosis, and they are essential for monitoring treatment response and effective patient management. Quantifying axonal loss and demyelination with MRI is our main objective. We recently introduced a white matter model that allows a direct physical interpretation of the non-Gaussian diffusion signal in white matter as measured with diffusional kurtosis imaging (DKI), a clinically feasible extension of diffusion tensor imaging (DTI). Analysis with this model yields specific white matter microstructural integrity metrics such as the intra- and extra-axonal diffusivities, the axonal water fraction (AWF) and tortuosity (?) of the extra-axonal space. Our modeling suggests that 1) the tortuosity ? correlates strongly with the thickness of the myelin sheath, and 2) AWF correlates strongly with the axonal density. We have confirmed these findings both analytically and numerically. In addition, we have demonstrated that measurements of AWF and tortuosity ? in MS and AD patients are compatible with the expected pathology in these patients. The main goals of this study are the histological validation of the prediction of our model, and preliminary evaluation of the utility o AWF and the tortuosity ? in monitoring disease progression and recovery. We will use the cuprizone mouse model of demyelination and axonal loss to test the following two specific aims: 1) To determine the relationship between the tortuosity ? and AWF estimated with in vivo DKI and the myelin thickness and axonal density measured by histopathology, and 2) To determine the longitudinal changes of tortuosity ? and AWF during cuprizone intoxication and recovery period. If successful, this project will establish a novel noninvasive method for assessment of white matter degeneration that will significantly improve drug discovery and patient management, based on the MRI- measured tortuosity ? and AWF as objective quantitative biomarkers for demyelination and axonal loss.
Both demyelination and axonal loss are common pathological features of most human neurological diseases/injuries including Multiple Sclerosis, leukodystrophy, traumatic brain injury as well as of normal aging and neurodegenerative diseases such as Parkinson's, Huntington's, amyotrophic lateral sclerosis, and Alzheimer's disease. Quantitative, noninvasive biomarkers of both demyelination and axonal loss would improve accuracy of diagnosis, and they are essential for monitoring treatment response and effective patient management. Quantifying axonal loss and demyelination with MRI is the main objective of this proposal.
|Guglielmetti, C; Veraart, J; Roelant, E et al. (2016) Diffusion kurtosis imaging probes cortical alterations and white matter pathology following cuprizone induced demyelination and spontaneous remyelination. Neuroimage 125:363-77|
|Jelescu, Ileana O; Zurek, Magdalena; Winters, Kerryanne V et al. (2016) In vivo quantification of demyelination and recovery using compartment-specific diffusion MRI metrics validated by electron microscopy. Neuroimage 132:104-14|
|Jelescu, Ileana O; Veraart, Jelle; Adisetiyo, Vitria et al. (2015) One diffusion acquisition and different white matter models: how does microstructure change in human early development based on WMTI and NODDI? Neuroimage 107:242-56|