Myelin plays a central role in determining MRI contrast in neuronal tissues, and, consequently, there are many MRI approaches measuring myelin content. This presentation will review several common approaches as well as some recent and developing approaches.
To provide an overview of current MRI methods that can be used to estimate myelin content in neuronal tissue. To this end, the lecture will cover:
Early MRI studies of human brain revealed strong contrast between white and gray matter, which suggested the importance of myelin in determining water proton nuclear magnetic relaxation rates. Since then, many experimental studies have aimed to model the role of myelin in MRI contrast, and corresponding method developments have aimed to establish robust MRI measures of myelin content. While some model details remain elusive, it is clear that myelin is a prominent contributor to water proton relaxation and several MRI methods have been demonstrated to quantitatively report on myelin content with a least some reasonable level of specificity.
Myelin is comprised of tightly wrapped layers of oligodendrocyte or Schwann cell membranes, with water residing in the relatively thin (~ 3 nm) intra- and extra-cellular spaces between adjacent membrane layers. Consequently, the water density per volume in myelin is relatively low, about 1/2 that in other soft tissue, and in this confined environment, water protons experience relatively frequent interactions with the non-aqueous components of myelin. These interactions result in a relatively rapid transverse and longitudinal relaxation of the water proton magnetization, and include a relatively large exchange of longitudinal magnetization between water and macromolecular protons, commonly referred to a magnetization transfer (MT). Each of these factors (low water density, rapid relaxation, large MT effect) can contribute contrast that reports on myelin content. Considering a more complete model of white matter or nerve, the relationships between these contrasts and myelin content becomes somewhat more complicated.
Water protons in white matter and nerve can be modeled in terms of three micro-anatomical compartments: intra-axonal (i.e., axoplasm), extra-axonal (space in between axons), and myelin. Macromolecular protons, although not directly observed in most MRI due to extremely fast relaxation of transverse magnetization, do affect water proton magnetization through MT. Including macromolecular protons therefore extends the compartmental model to six proton pools with coupling of longitudinal magnetization between the water and macromolecule pools in each anatomical compartment. Inter-compartmental water exchange, particularly between myelin and each of the other two water compartments, may also be relevant, resulting in a six-pool model with at least five coupling pathways. While attempts have been made to parameterize this model (1-3), it is far too complex to directly inform on clinically-practical MRI. Instead, the role of myelin in MRI contrast is best appreciated in terms of a simpler model.
For measurement of transverse relaxation (that is, both T2 and T2* time constants), it is reasonable to ignore the macromolecular protons because their transverse magnetization is effectively zero and time invariant. Further, it is common to ignore the inter-compartmental water exchange on the assumption that it is relatively slow compared with the transverse relaxation. The faster relaxing myelin water signal can then be distinguished from intra- and extra-axonal water signals by multi-exponential signal analysis (4). The most common use of this model is for multi-exponential T2 analysis of multiple spin echo images (5-7), through which the term myelin water fraction (MWF) was coined (5). Multiple experimental studies support the conclusion that MWF is a correlative measure of myelin content (8-15). More recently, similar multi-exponential T2* analysis has been applied to multiple gradient echo images (16-20). The T2*approach has the advantage of using a simpler and more easily accelerated pulse sequence, but comes with the additional complication of needing to correct for macroscopic field variations and, potentially, susceptibility induced frequency shifts (21-24). For either T2 or T2*, there are two shortcomings to this approach: 1) the signal to noise ratio requirement of the multi-exponential analysis are high, and 2) the assumption of slow inter-compartmental water may not always hold, resulting in an systematic underestimation of myelin content by MWF measurement (25-29). This exchange effect is likely greater in smaller axons with thinner myelin, resulting in a possible axon-size dependence of the MWF measurement.
For measurement of longitudinal relaxation, there are a few options for model simplification. Applying the same slow-exchange, water-only model, MWF can be estimated by multi-exponential T1 analysis of inversion-recovery image data (30). However, because T1 > T2, the effects of inter-compartment water exchange can only be worse in this scenario. Also, when considering longitudinal magnetization, the macromolecular proton pool cannot, in general, be ignored. The water and macromolecular longitudinal magnetizations will respond differently to radio frequency (RF) pulses, and this will in-turn effect the MRI signal through MT (31-32). One can try to avoid this effect through appropriate sequence timings, although, as noted below, if the MT effect is also strongly dependent upon myelin, its confound in T1-MWF measurements may not be a practical problem.
Alternatively, rather than trying to mitigate the MT effect, one can make it the target signal, with the reasoning the myelin is the dominate contributing anatomical compartment. This can be implemented in a number of ways, but two common approaches are: 1) saturating the macromolecular proton magnetization independently of the water magnetization using off-resonance RF and then observing the MT effect on the water magnetization, or 2) saturating or inverting the water magnetization independently of the macromolecular magnetization and then, again, observing the effect MT effect on the water magnetization. Of course, myelin is not the only source of MT contrast, but MT contrast has been shown to correlate with myelin content (12,33-35), and a more recent variation on MT contrast known as inhomogeneous MT (ihMT) may offer a greater level of specificity to myelin (36-38).
A third approach for relating myelin to longitudinal relaxation, which is a logical extension of the MT model, is to assume that MT is relatively fast and the dominant contributor to water proton T1. If one again assumes that the dominant source of MT is myelin, then with this model a measure of 1/T1 (=R1) is proportional to the concentration of myelin (39-41) and even appropriately calibrated T1-contrast can do the same (42–44). This model too is an oversimplification, but has gained popularity as a fast, high resolution approach to mapping myelin, particularly in the cortex (45-47).
In summary, myelin is a prominent contributor to both longitudinal and transverse relaxation as well as overall proton density, and so any number of quantitative measures of these characteristic can be related to myelin content. Presently, there is no one approach that is decidedly better than the others, but multi-exponential T2 and quantitative MT likely use the most well founded models and have been the most experimentally well supported, while R1 measures, although perhaps less specific to myelin, offer faster and higher resolution acquisitions. For further reading on the material, the reader is directed to a collection of recent review articles related to probing brain microstructure with MRI (48-50).
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