Assessment of Myelin Changes by Quantitative MRI

Despite its excellent sensitivity, conventional magnetic resonance imaging (MRI) fails to provide more detailed insight into the pathological substrate of various types of white matter diseases. This also reflects in a poor correlation of signal abnormalities with clinical functions. Quantitative MRI is expected to allow for a more in depth analysis of tissue composition by measuring the individual biophysical parameters involved in the complex process of MR signal formation. Current quantitative methods, however, are frequently limited to in vitro studies, and a comprehensive study of quantitative parameters in normal and diseased states of white matter has not yet been performed. The aim of the proposed project therefore is to adapt currently proposed methods or to develop new sequences to determine fundamental biophysical MR parameters in vivo, which are directly related or coupled to the amount of myelin. We will focus on five parameters of the commonly used two-pool model which separates water protons by their mobility into a myelin-related pool and a bulk water pool: These are the myelin-pool fraction, the magnetization transfer rate, the magnetization transfer ratio and the apparent and native longitudinal relaxation rate. For obtaining the first parameter, we will implement a method which analyses the short T2-component from a CPMG sequence and a second method which analyses the response from multiple inversion pulses. All other parameters will be obtained with the FastPACE technique. Possible improvements will be related to multislice capability, acquisition time, specific absorption rate and non-ideal conditions of RF saturation. Phantom measurements and numerical simulations incorporating the coupled Bloch equations and spectral effects of RF pulses will serve to improve and validate these methods. We will measure above parameters in forty healthy volunteers to obtain normative data as a function of age, gender and anatomic region. In parallel, these parameters will be determined in normal appearing white matter and lesions of fifty patients suffering from multiple sclerosis and microangiopathy as two models of white matter disorders. We speculate to find disease specific differences of reproducible biophysical parameters. Their quantitation should serve to monitor disease evolution including the effects of various types of treatment in the future.

Magnetic resonance imaging (MRI) has contributed tremendously to our understanding of various white matter diseases including multiple sclerosis and dementia. This is mostly related to the superior sensitivity of MRI, i.e the capability to depict changes to the cerebral white matter that is not discernible with other imaging modalities. However, conventional MRI falls short in fully explaining the pathophysiologic changes which underlie the signal intensity changes observable with a conventional approach. Even more importantly, the clinical consequences of these changes cannot be predicted in most instances. The research project therefore focused on a biophysical model for myelin (a kind of "insulation sheet" for neural conduction) to explain and predict the magnetic resonance (MR) appearance of white matter changes. A basic feature of that model is the phenomenon of magnetization transfer (MT), a mechanism that is responsible for a continuous exchange of energy between myelin associated protons and tissue water. In this project, we applied quantitative MR techniques that provide a measure of the relative magnitude of MT. This was based on the assumption that MT reflects the amount of myelin. Further, following upon a biophysical model for myelin, we developed a new MR method that allows estimating the relative myelin content on clinical MR scanners. This method potentially proves useful in characterising white matter disorders and ideally would allow monitoring de- and remyelination. This may not only facilitate determination of lesion severity but could also have therapeutic implications. We used quantitative MR techniques to study accumulating white matter damage in patients suffering from Alzheimer`s disease, the most frequent cause of dementia in elderly people. We demonstrated that MT imaging techniques help to detect white matter change a few months prior to subsequent cognitive decline. In addition, we demonstrated that MT imaging significantly add to better characterise and classify the composition of so-called white matter lesions. These are frequently observed in healthy elderly people and been related to depression, cognitive decline, and gait disorders. Finally, we used this special technique to test if the normal appearing white matter in normal elderly people with matter hyperintensities really deserves its designation.