Olivier M. Girard1
1Aix-Marseille Univ, CNRS, CRMBM, Marseille, France
Synopsis
This
lecture will cover the basic principles of magnetization transfer (MT) imaging
techniques targeted toward immobile macromolecules in brain and describe how
these techniques may inform on the local tissue microstructure. Following this lecture, the attendees should 1/
understand the origin of the magnetization transfer signal within heterogeneous
systems such as brain tissues, 2/ understand simplified biophysical modelling
aiming at describing myelinated white matter in the context of MT imaging; and
3/ understand how the orientation of the myelinated axons may affect MT
measurements and how this may influence other contrasts (T1, T2) measured in
the brain.
Target audience
MRI
scientists and engineers interested in brain microstructure and Magnetization
Transfer techniques. Clinicians interested in advanced myelin imaging techniques.Summary of the presentation
Magnetization
Transfer (MT) refers to a relatively broad range of MRI experiments allowing to
image specific molecules in vivo using MRI. MT relies on indirect detection, by
measuring the magnetization of the detectable free water proton pool (with
relatively long T2) and relying on transfer of magnetization between the molecules
of interest and the free water. In this lecture we refer to MT as targeted to immobile
macromolecules; the latter being defined by their broad resonance lines which
are associated with motion restricted molecules (long motional correlation
time) as well as ultra-short transverse relaxation time (T2 in the range of tens
of µs) and are often referred to as the semisolid and/or bound proton pool. According
to this definition it is generally non-trivial to get a simple and intuitive
mental picture of the involved compounds, since macromolecules are not defined according
to their intrinsic size (e.g. expressed in atomic mass units) but rather by
their molecular mobility which depends on external factors such as the
viscosity of the local environment and the overall tissue architecture at the
microscopic (e.g. atomic scale) and the mesoscopic (e.g. cellular scale) scales.
Within the scope of brain applications, it has been shown over the years that
MT imaging is particularly sensitive to the myelin sheath, which is a large supra-molecular
assembly made from the oligodendrocyte cell membrane and containing large
amount of lipid chains arranged in a liquid crystalline phase. More recently a refinement of MT, namely the
inhomogeneous MT (ihMT), has demonstrated an improved signal specificity toward
myelin due to its unique sensitivity to dipolar order and its associated
relaxation time (T1D) which is particularly long in the liquid-crystal phase.
Hence it is
not surprising that MT MRI has emerged as a mean to assess the tissue microstructure,
especially for brain. That being said, it remains challenging to extract tissue
information that may be directly interpreted in terms of relevant parameters
defining the tissue microstructure (such as the absolute macromolecular content
or the averaged size, diameter, or the orientation of the myelin sheath or axons).
However, from a wider perspective, one could define the field of MRI microstructure
as methods enabling access to information which characterize the tissue at the
sub-voxel (i.e micro to mesoscopic) scale. This requires biophysical modeling
of the tissue as well as MR physics modelling of the MRI signal, such that one
could infer the biophysical parameters from the measured signal. According to
this general definition, quantitative MT (qMT) approaches may thus be
considered as microstructural modalities. qMT provides access to several
parameters of interest such as the relative macromolecular concentration (as
expressed by the relative size of the macromolecular proton pool magnetization,
normalized by the fee water pool magnetization), the width of the
macromolecular lineshape (inversely proportional to the macromolecular T2) or
the exchange rate of magnetization between the proton pools. Although these
parameters pertain to a simplified biophysical model, that typically aggregates
all water proton in a single pool, and similarly for all macromolecules, such quantitative
parameters may inform on the local physio-pathological processes. More advanced
modelling of the white matter and the myelin sheath and associated exchange
processes have also been developed and may provide a refined understanding of
the exchange processes, and on the influence of MT mechanisms on relaxation
data.
The following lecture will cover the basics
principles of MT and associated biophysical modelling enabling measurement of
the tissue macromolecular content. In addition, more advanced modelling dedicated
to white matter will be covered.Acknowledgements
I thank my
colleagues, collaborators, and all other researchers with whom I have had
highly stimulating and helpful scientific discussions about MT and brain microstructure.References
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