Imaging Fat in Muscle
Dimitrios Karampinos1

1Department of Diagnostic and Interventional Radiology, Technical University of Munich, Germany

Synopsis

The present educational lecture will provide an overview of the technical aspects of measuring skeletal muscle fat fraction and will discuss recent applications of measuring muscle fat fraction in neuromuscular disorders, orthopedics, metabolic diseases and aging.

Objective

The present educational lecture aims to introduce the importance of measuring fat in skeletal muscle and to provide an overview of techniques available for imaging fat in skeletal muscle and their application in neuromuscular disorders, orthopedics, metabolic diseases and aging.

Clinical need

Skeletal muscle is primarily composed of water, proteins and fat. Water and fat can be found within or outside the myocytes (i.e. the muscle cells). Therefore, skeletal muscle lipids can be further divided into intramyocellular and extramyocellular lipids. Fatty infiltration relates to the increased accumulation of lipids in skeletal muscle and can be quantified by measuring the skeletal muscle fat fraction. Skeletal muscle fatty infiltration has a direct impact on muscle function due to the accompanying reduction of contractile volume. The skeletal muscle fat fraction is therefore an important imaging marker of pathophysiological changes and of disease progression in neuromuscular disorders, orthopedics, metabolic dysfunction and aging.

Techniques for measuring muscle fat

Chemical shift encoding techniques constitute the state-of-the-art methods for imaging skeletal muscle fat fraction. The present lecture first focuses on the technical aspects of the application of chemical shift encoding techniques in healthy and diseased skeletal muscle in order to extract the proton density fat fraction as a standardized imaging marker of fat content. Confounding effects in the measurement of the skeletal muscle proton density fat fraction are introduced, including main magnetic field inhomogeneity effects, the presence of multiple peaks in the fat spectrum, T2* effects, T1-bias effects and eddy current effects. Specifically, previous works have addressed the need for noise efficient correction of T1-bias effects and have investigated the effect of susceptibility-induced EMCLs fat resonance shift on the measured fat fraction.

The segmentation of the individual skeletal muscles on the fat fraction maps in order to measure intramuscular fat fraction remains a significant challenge in the analysis of such data and a significant hurdle in the broader expansion of the application of fat fraction mapping in skeletal muscle. Relevant image analysis methods are therefore briefly discussed.

Applications for imaging muscle fat

Quantitative water-fat imaging has been compared to qualitative fat infiltration grading schemes used to characterize skeletal muscle fat infiltration, showing a strong correlation in the fat infiltration description results between the quantitative and qualitative approaches. In parallel, previous studies have highlighted the benefits of a quantitative assessment of muscle fat infiltration using a continuous imaging marker (i.e. the fat fraction) measured at high spatial resolution.

Chemical shift encoding techniques have been therefore becoming popular in measuring the fat fraction in diseased muscles affected by a wide range of pathologies. The most prominent application relates to the measurement of the muscle fat fraction primarily in the extremities as a metric of therapy outcome in patients with neuromuscular diseases. Additional examples include the application of skeletal muscle fat quantification techniques in orthopedic research and especially in patients with rotator cuff tendon injuries, knee osteoarthritis and back pain. Skeletal muscle fat quantification is also important target in relating the effects of obesity and insulin resistance to skeletal muscle function. There is finally an ongoing interest in quantifying muscle fatty degeneration and establishing imaging phenotyping methodologies in patients with sarcopenia, sarcopenia obesity and cancer cachexia, especially for the needs of disease risk assessment.

Acknowledgements

The present work was supported by the European Research Council (grant agreement No 677661, ProFatMRI) and Philips Healthcare.

References

No reference found.
Proc. Intl. Soc. Mag. Reson. Med. 27 (2019)