Application of Quantitative MRI Methods in Central Nervous System Diseases
Abstract
During the past couple of decades, conventional magnetic resonance
imaging (MRI) techniques have been increasingly used to assess alterations
in the central nervous system (CNS). Nowadays, a variety of conventional
MRI protocols are also routinely used to detect therapeutic effects of
different treatment strategies. These offer several important advantages,
such as the definition of disability level, the association of blood brain
barrier damage, spatial and temporal dissemination of brain lesions. In the
past few years, a host of non-conventional quantitative MRI techniques
have been introduced for the assessment of CNS diseases. These MRI
techniques appear to be reliable markers in monitoring pathologic processes
related to disease activity and clinical progression. They are able to reveal a
range of tissue changes that include oedema, inflammation, demyelination,
axonal loss, and degeneration. Therefore, in a disease with a high degree of
longitudinal variability of clinical signs and with no current adequate
biological markers of disease progression, non-conventional quantitative
MRI techniques provide a powerful tool to non-invasively investigate not
only the pathological substrates of overt lesions but also subtle global
changes that may affect the entire brain. Additionally, conventional MR
imaging gives only a cross-sectional qualitative information of different
tissues, while quantitative approaches offer the advantage of absolute rather
than relative characterization of the underlying biochemical composition of
the tissue. The determination of quantitative MRI data requires more
detailed approaches and a good understanding of basic MR phenomena.
Generally, it is performed by using and analysing a set of qualitative
images, where the signal intensity is controlled by the change of an MR
imaging parameter: inversion time, flip angle or repetition time for T1
relaxometry; echo time for T2 relaxometry and b-value for diffusionweighted
data. Then quantitative MR data can be calculated by mono- or
multi-exponentially fitting the signal change against these parameters. In
clinical perspective, T1 and T2 relaxation times depend on structural
characteristics such as local tissue density (i.e. water content), while
quantitative diffusion data provides an indirect measure of tissue structure
on a microscopic scale.