Skeletal muscle makes up around 40% of adult
human body mass and plays a vital role in health and function. It is a highly
ordered structure, the fundamental units of which are three main fibre types: Type
1 fibres (mechanically slow and rely on oxidative metabolism), Type 2b/x fibre
(mechanically fast and dependent upon glycolytic energy generation), and Type 2a fibres
having intermediate properties (1).
The distribution, density and dimensions of
these myofibres, which we expect to influence water-based MRI signals, depend
strongly on muscle type, age, physical training and disease status. The
pathological hallmarks of neuromuscular diseases: oedema, atrophy, fat infiltration
and fibrosis, are also accessible to MRI measurement. Thus quantitative MRI is
an ideal tool to probe muscle quality and function in health and disease.
Many studies have addressed muscle-water T1, T2, magnetisation
transfer, fat content and diffusion (1) properties and their dependence upon
age, gender, exercise status. For example, we have shown in healthy 21.5-81y
old adults a small but significant dependence of lower-limb muscle T2, fat
fraction and magnetisation transfer ratio (MTR) upon age and body weight, and
for MTR gender (2). There were also small inter-muscle variations, also evident
in quantitative magnetisation transfer measurements (3), presumably reflecting differences
in fibre-type distribution and quality.
Similarly, many groups have investigated the potential of
MRI to quantify muscle disease effects, which is becoming increasingly important
with the growing need for effective trial outcome measures to test new
therapies in muscle-wasting conditions (4). For instance, we have shown reduced
MTR in denervated muscles in peripheral neuropathies (5, 6) and longitudinal changes
in fat-fraction, T2 and MTR in Inclusion Body Myositis offering highly
responsive potential trial end points (6).
Both to establish tools to assess muscle physiological
function, and to validate potential surrogate trial outcome measures, it is necessary
to determine the relationship between MRI measures and muscle function. This
has been achieved by, e.g., correlation with machine myometry, where approximately
linear relationships are seen between effective muscle cross sectional area on
MRI, and muscle torque (6). MRI measures have also been compared with clinical
measures of function, such as ocular excursion to assess the condition of
extra-ocular muscles (7), and six minute walk distance used to assess
ambulation in dystrophic conditions (8); MRI may often provide a superior
operator-and subject-effort independent, objective and disease-responsive surrogate
functional measure.
While muscle fat content determined by Dixon-type
measurements is a valuable indicator of disease severity in itself (6, 8), the
presence of lipid complicates the acquisition and interpretation of data
intended to probe specifically muscle water properties. A number of approaches
have been proposed, particularly for obtaining fat content-independent muscle
water T2 values (9, 10).
MRI continues to provide new measures of muscle quality and
function. The increasing availability of image-acceleration methods, and more
powerful gradient systems, may increase clinical application and provide even
more sensitive measures of pathology, particularly of early-stage disease.
References
1. Strijkers GJ, DROST MR, NICOLAY K. Diffusion imaging in muscle. In:
Diffusion MRI: Theory, Methods, and Applications. Oxford University
Press; 2011:672–689.
2. Morrow, J.M., Sinclair, C.D., Fischmann, A., Reilly, M.M., Hanna,
M.G., Yousry, T.A. and Thornton, J.S., 2014. Reproducibility, and age,
body-weight and gender dependency of candidate skeletal muscle MRI outcome
measures in healthy volunteers. European Radiology, 24(7), pp.1610-1620.
3. Sinclair, C. D. J., Samson, R. S., Thomas, D. L., Weiskopf, N.,
Lutti, A., Thornton, J. S. and Golay, X. (2010), Quantitative magnetization
transfer in in vivo healthy human skeletal muscle at 3 T. Magn Reson Med, 64:
1739–1748. doi: 10.1002/mrm.22562
4. Hollingsworth, K.G., de Sousa, P.L., Straub, V. and Carlier, P.G.,
2012. Towards harmonization of protocols for MRI outcome measures in skeletal
muscle studies: consensus recommendations from two TREAT-NMD NMR workshops, 2
May 2010, Stockholm, Sweden, 1–2 October 2009, Paris, France. Neuromuscular
Disorders, 22, pp.S54-S67.
5. Sinclair, C.D.J., Morrow, J.M., Miranda, M.A., Davagnanam,
I., Cowley, P.C., Mehta, H., Hanna, M.G., Koltzenburg, M., Yousry, T.A.,
Reilly, M.M. and Thornton, J.S., 2012. Skeletal muscle MRI magnetisation
transfer ratio reflects clinical severity in peripheral neuropathies. Journal
of Neurology, Neurosurgery & Psychiatry, 83(1), pp.29-32.
6. Morrow, J.M., Sinclair, C.D., Fischmann, A., Machado,
P.M., Reilly, M.M., Yousry, T.A., Thornton, J.S. and Hanna, M.G., 2016. MRI
biomarker assessment of neuromuscular disease progression: a prospective
observational cohort study. The Lancet Neurology, 15(1), pp.65-77.
7. Pitceathly, R.D., Morrow, J.M., Sinclair, C.D., Woodward,
C., Sweeney, M.G., Rahman, S., Plant, G.T., Ali, N., Bremner, F., Davagnanam,
I. and Yousry, T.A., 2016. Extra-ocular muscle MRI in genetically-defined
mitochondrial disease. European radiology, 26(1), pp.130-137.
8. Willis,
T.A., Hollingsworth, K.G., Coombs, A., Sveen, M.L., Andersen, S., Stojkovic,
T., Eagle, M., Mayhew, A., de Sousa, P.L., Dewar, L. and Morrow, J.M.,
Sinclair, C.D.J, Thornton, J.S., Bushby, K.,
Lochmüller, H., Hanna, M.G., Hogrel, J.Y., Carlier, P.G., Vissing, J.,
Straub, V. 2013. Quantitative muscle MRI as an assessment tool for monitoring
disease progression in LGMD2I: a multicentre longitudinal study. PloS one,
8(8), p.e70993.
9. Janiczek, R.L., Gambarota, G., Sinclair, C.D., Yousry,
T.A., Thornton, J.S., Golay, X. and Newbould, R.D., 2011. Simultaneous T2 and
lipid quantitation using IDEAL-CPMG. Magnetic resonance in medicine, 66(5),
pp.1293-1302.
10. Azzabou, N., Loureiro de Sousa, P., Caldas, E. and
Carlier, P.G., 2015. Validation of a generic approach to muscle water T2
determination at 3T in fat-infiltrated skeletal muscle. Journal of Magnetic
Resonance Imaging, 41(3), pp.645-653.