MR of Lipids in Biological Processes & Disease States
Chris Boesch1

1University Bern, Switzerland

Synopsis

Lipid metabolism is crucial for the proper functioning of the human body and in turn also the precursor for major diseases like stroke and myocardial infarction. Better understanding of lipid metabolism is a prerequisite for a prevention of these diseases which are growing to an pandemic problem. In addition, mobile lipids are dependent on the occurrence of necrosis or apoptosis in cancer cells and concentrations of phospholipid-intermediates indicate increased membrane turnover in tumors. Physiological, patho-physiological, and methodological aspects of MRI/MRS studies of lipid metabolism in humans shall be discussed.

Highlights

* Lipid metabolism is an essential factor for an efficient functioning of the human body but also for the occurrence of fatal diseases
* Some of the lipid-related diseases are pandemic and represent a serious threat for the patients and for the health care systems in most countries
* Lipid metabolism is related to cancer biology, in particular phospholipid intermediates and mobile lipids
* MRI and MRS are well suited to study lipid metabolism in the human body
* The strength of MR imaging is its ability to show the distribution of lipid compartments
* The strength of MR spectroscopy is the differentiation of different types of lipids, either based on their chemical (e.g. unsaturated/saturated) and physical (e.g. intra- vs. extramyo-cellular) nature


Target Audience, Objectives

For an audience of clinicians, clinical scientists, and MR-methodologists, the potential of MR imaging and spectroscopy shall be illustrated to study lipid metabolism in vivo. In particular, it shall be shown how many fatal diseases like stroke or myocardial infarction are an endpoint of a derailed lipid metabolism and that MR-studies are a crucial key to a better understanding of these essential processes. In turn, a well-functioning lipid metabolism is vital for an efficient and healthy energy management of the body. In a broader sense, lipid metabolism is also involved in the biology of cancer cells where mobile lipids are observed and the metabolism of phospholipids can be used to look into tumor growth.


Summary

Lipid metabolism is essential for the well-being of humans and at the same time the precursor for fatal diseases like stroke and myocardial infarction if it derails. Human energy metabolism and all functions which are related to it would fail without a functioning lipid metabolism. In our imaging community, lipids are too often reduced to their function as potential image contrast for others, apparently more important tissues. Since the groundbreaking paper of Randle et al (1) the scientific community is aware that lipid metabolism is strongly related to diabetes, insulin resistance, and the "metabolic syndrome". While diabetes and insulin resistance are well defined entities, the "metabolic syndrome" is more helpful in epidemiology where large populations and their health status shall be described over time. These epidemiological studies show (2-6) that this group of diseases causes a major threat to the patients and also to the health care systems of many countries, particularly for the industrial ones but not at all exclusively. In turn, lipid metabolism is an essential part of our well-being and for excellent athletic performance. These two sides of lipid metabolism are nicely seen in the "athletes paradox" (7) where high levels of intra-myocellular lipids (IMCL) are typical for well-trained, insulin-sensitive athletes while in sedentary subjects, high IMCL levels are related to insulin resistance and thus to a higher risk of cardiovascular diseases.

Magnetic resonance is perfectly suited to support studies on lipid metabolism in humans (8-10). One advantage is the wealth of information that can be obtained by MRI and in particular MRS. In addition, there are also ethical and practical reasons why MRI/MRS are preferred for studies of lipid metabolism which require often repeated measurements in mostly healthy subjects. While immediately life-threatening diseases justify invasive methods and/or increased radiation doses, nutritional studies in healthy subjects benefit from the non-invasive and safe MR procedure in particular if time-series before and after an intervention are required.

MRI allows for a determination of whole-body composition, i.e. the regional measurement of lipid compartments, skeletal muscle mass, and other tissues (10-12). This type of imaging became very important when it was hypothesized that visceral adipose tissue (VAT) is correlated to insulin resistance. It's spatial vicinity to the uptake of nutrition in the gut and the portal vein seem to assign VAT a specific role in the lipid metabolism and the ability of the body to react on the effect of insulin. Fat specific MRI sequences or selective excitation (11-14) allow for an observation and quantitation of fat in various organs, in particular in the liver where MRS is accepted as gold standard particularly for low levels of intrahepatic lipids (IHCL) yet without the spatial information of the imaging sequences.

MRS gained a particular role in the observation of insulin resistance when it was recognized that intra- and extramyocellular lipids (IMCL/EMCL) can be observed separately (15,16) and that there level is related to insulin resistance in sedentary subjects (17-19). A large number of studies used this technique to observe effects of physical activity, nutritional changes, and many other influences (9,20). IMCL was discussed as major cause for insulin resistance, neglecting the fact that this explanation would contradict the "athletic paradox", i.e. observation that well-trained, insulin-sensitive athletes show particularly high levels of IMCL (7,21,22). Meanwhile, the interpretation shifted from "IMCL is a cause of insulin resistance" more towards "insulin resistance causes an immobilization of IMCL, leading to permanently high IMCL levels" - in contrast to insulin-sensitive athletes who can store IMCL in large quantities and then use them within a couple of minutes to hours when they are needed for energy production. Lipid content was also studied in liver (intrahepatocellular lipids, IHCL) and the heart (intracardiomyocellular lipids, ICCL) and effects of physical activity on the different tissues were evaluated (13,23,24). A comparison of cardiac lipid levels (ICCL) with plasma data and IHCL (25) showed that no correlation was observable between the different compartments; therefore, a non-invasive observation of these biomarkers by MRS is essential since all contain specific, not exchangeable information on the lipid metabolism. The determination of hepatic lipids IHCL is an increasingly important diagnostic too since the non-alcoholic-fatty liver disease (NAFLD) becomes an increasing problem for many countries (26).

Various new culprits of insulin resistance were presented, in particular intermediate products (27-29) like the diacylglycerols (DAG) or sphingolipids. When metabolites in the micromolar range are discussed, other methods than in vivo MRS are required to test such hypotheses; nonetheless, MRS can reveal information on the lipid composition since several positions in the lipid molecules are observable and allow for a determination of average chain length, degree of unsaturation, and poly-unsaturation. In particular sophisticated multi-dimensional MR spectra (spatial selection combined with and 2D-spectroscopy) are promising to disentangle the lipid composition (30,31); however, the technical implementation on clinical scanners is demanding. These findings can contribute indirectly to a better understanding of the intermediates and the resulting composition of lipid metabolism.

Lipid droplets are of increasing interest and recognized as important organelles (28,32). Diffusion-weighted MR spectroscopy has the potential to measure subcellular dimensions (33); however, since lipids and in particular IMCL are diffusing generally very slowly, extremely strong gradients are required which are up to now only available in animal systems (34). Investigations of the droplet size have been suggested since the geometry of the lipid droplet - mitochondrial complex is highly relevant and might be related to insulin resistance.

Acetylcarnitine is a metabolite at the entrance to the tricarboxylic acid cycle (TCA cycle, also known as Krebs cycle or citric acid cycle) with various functions, including buffering of acetyl-coA and transport of acyl chains from lipids. 1H-MRS allows the observation of acetylcarnitine in skeletal muscle particularly after physical exercise (35) and it has been shown that the concentrations at rest are related to insulin resistance (36). This opens a new window towards the link between lipid and energy metabolism since the entrance to the TCA cycle is a major metabolic step before energy carrying ATP is produced in the aerobic pathway.

Labeled 13C substrates help to measure the activity of the TCA cycle and are thus particularly suited for studies of the energy metabolism and effects of insulin resistance on this essential pathway (14). However, these elegant methods are not yet in wide-spread use and also not particularly focused on lipid metabolism. The usage of hyperpolarized 13C in MRI/MRS is extremely promising (14) for studies of the metabolites of the glycolysis down to the entrance of the TCA cycle (pyruvate, lactate, alanine, bicarbonate). How far these methods will help in the measurement of the TCA cycle activity and lipid metabolism is not yet fully fathomed.

The typical fat accumulation in the human body is white adipose tissue (WAT), and its role is often underestimated since it is much more than the most efficient storage of energy but also a producer of hormones etc. Brown adipose tissue (BAT) came into the focus of the scientific community when it was clear that it is metabolically very active and can burn calories for the production of heat. Several MR based methods have been suggested for an observation of BAT (12); however, its application is not yet wide-spread.

Beyond the function of lipids in the energy metabolism and related diseases, MRS observations of mobile lipids in cancer (31,37) are extremely attractive and might lead to a better understanding of the tumor generation and effects of treatment. The observation of mobile lipids seems to be particularly promising for the detection of treatment-induced apoptosis vs. necrosis (37). The increased membrane turnover in tumors is also responsible for concentration changes of phospholipid intermediates during tumor growth (38-40).

To summarize, lipid metabolism is relevant for physical activity and well-being as well as for pandemic diseases. A better understanding of the lipid metabolism based on a collaboration of physiologists, endocrinologists, radiologists, and MR-methodologists is essential and topical. The existing MR equipment can help to solve urgent questions - and opens a new field of radiological applications beyond the classical imaging diagnosis. A combination of the wealth of MR-modalities with metabolic MR-studies really promises to provide a "one-stop-shop" for studies in humans.

Acknowledgements

Support by the Swiss National Science Foundation (#310030-149779).

References

References

1. Randle P, Garland P, Hales C, Newsholme EA. The glucose fatty-acid cycle. Its role in insulin sensitivity and the metabolic disturbances of diabetes mellitus. Lancet 1963;1:785-789.

2. Air EL, Kissela BM. Diabetes, the metabolic syndrome, and ischemic stroke: epidemiology and possible mechanisms. Diabetes Care 2007;30:3131-3140.

3. McCullough AJ. Epidemiology of the metabolic syndrome in the USA. J Dig Dis 2011;12:333-340.

4. Grundy SM. Metabolic syndrome: a multiplex cardiovascular risk factor. J Clin Endocrinol Metab 2007;92:399-404.

5. Mottillo S, Filion KB, Genest J, Joseph L, Pilote L, Poirier P, Rinfret S, Schiffrin EL, Eisenberg MJ. The metabolic syndrome and cardiovascular risk a systematic review and meta-analysis. J Am Coll Cardiol 2010;56:1113-1132.

6. Shulman GI. Ectopic fat in insulin resistance, dyslipidemia, and cardiometabolic disease. N Engl J Med 2014;371:1131-1141.

7. Goodpaster BH, He J, Watkins S, Kelley DE. Skeletal muscle lipid content and insulin resistance: evidence for a paradox in endurance-trained athletes. J Clin Endocrinol Metab 2001;86:5755-5761.

8. Boesch C. Musculoskeletal Spectroscopy. J Magn Reson Imaging 2007;25:321-338.

9. Boesch C, Machann J, Vermathen P, Schick F. Role of proton MR for the study of muscle lipid metabolism. NMR Biomed 2006;19:968-988.

10. Heymsfield SB, Hu HH, Shen W, Carmichael O. Emerging Technologies and their Applications in Lipid Compartment Measurement. Trends Endocrinol Metab 2015;26:688-698.

11. Machann J, Horstmann A, Born M, Hesse S, Hirsch FW. Diagnostic imaging in obesity. Best Pract Res Clin Endocrinol Metab 2013;27:261-277.

12. Hu HH, Kan HE. Quantitative proton MR techniques for measuring fat. NMR Biomed 2013;26:1609-1629.

13. Reeder SB, Cruite I, Hamilton G, Sirlin CB. Quantitative assessment of liver fat with magnetic resonance imaging and spectroscopy. J Magn Reson Imaging 2011;34:729-749.

14. Han W, Chuang KH, Chang YT, Olivo M, Velan SS, Bhakoo K, Townsend D, Radda GK. Imaging metabolic syndrome. EMBO Mol Med 2010;2:196-210.

15. Schick F, Eismann B, Jung WI, Bongers H, Bunse M, Lutz O. Comparison of localized proton NMR signals of skeletal muscle and fat tissue in vivo: Two lipid compartments in muscle tissue. Magn Reson Med 1993;29:158-167.

16. Boesch C, Slotboom H, Hoppeler H, Kreis R. In vivo determination of intra-myocellular lipids in human muscle by means of localized 1H-MR-spectroscopy. Magn Reson Med 1997;37:484-493.

17. Stein, D. T., Szczepaniak, L. S., Dobbins, R., Malloy, C. R., and McGarry, J. D. Skeletal muscle triglyceride stores are increased in insulin resistance [abstract]. Diabetes 1997;46-Suppl1:23A.

18. Krssak M, Petersen KF, Dresner A, DiPietro L, Vogel SM, Rothman DL, Shulman GI, Roden M. Intramyocellular lipid concentrations are correlated with insulin sensitivity in humans: a 1H NMR spectroscopy study. Diabetologia 1999;42:113-116.

19. Jacob S, Machann J, Rett K, Brechtel K, Volk A, Renn W, Maerker E, Matthaei S, Schick F, Claussen CD, Haring HU. Association of increased intramyocellular lipid content with insulin resistance in lean nondiabetic offspring of type 2 diabetic subjects. Diabetes 1999;48:1113-1119.

20. Pola A, Sadananthan SA, Yaligar J, Nagarajan V, Han W, Kuchel PW, Velan SS. Skeletal muscle lipid metabolism studied by advanced magnetic resonance spectroscopy. Prog NMR Spectroscopy 2012;65:66-76.

21. Thamer C, Machann J, Bachmann O, Haap M, Dahl D, Wietek B, Tschritter O, Niess A, Brechtel K, Fritsche A, Claussen C, Jacob S, Schick F, Haring HU, Stumvoll M. Intramyocellular lipids: anthropometric determinants and relationships with maximal aerobic capacity and insulin sensitivity. J Clin Endocrinol Metab 2003;88:1785-1791.

22. Decombaz J, Schmitt B, Ith M, Decarli B, Diem P, Kreis R, Hoppeler H, Boesch C. Post-exercise fat intake repletes intramyocellular lipids, but no faster in trained than in sedentary subjects. Am J Physiol 2001;281:R760-R769.

23. Bucher J, Kruesi M, Zueger T, Ith M, Stettler C, Diem P, Boesch C, Kreis R, Christ E. The effect of a single bout of a 2h aerobic exercise on ectopic lipids in skeletal muscle, liver and the myocardium. Diabetologia 2014;57:1001-1005.

24. Bizino MB, Hammer S, Lamb HJ. Metabolic imaging of the human heart: clinical application of magnetic resonance spectroscopy. Heart 2014;100:881-890.

25. McGavock JM, Lingvay I, Zib I, Tillery T, Salas N, Unger R, Levine BD, Raskin P, Victor RG, Szczepaniak LS. Cardiac steatosis in diabetes mellitus: a 1H-magnetic resonance spectroscopy study. Circulation 2007;116:1170-1175.

26. Cohen JC, Horton JD, Hobbs HH. Human fatty liver disease: old questions and new insights. Science 2011;332:1519-1523.

27. Amati F. Revisiting the diacylglycerol-induced insulin resistance hypothesis. Obes Rev 2012;13-Suppl2:40-50.

28. Bosma M, Kersten S, Hesselink MK, Schrauwen P. Re-evaluating lipotoxic triggers in skeletal muscle: relating intramyocellular lipid metabolism to insulin sensitivity. Prog Lipid Res 2012;51:36-49.

29. Samuel VT, Shulman GI. Mechanisms for insulin resistance: common threads and missing links. Cell 2012;148:852-871.

30. Furuyama JK, Nagarajan R, Roberts CK, Lee CC, Hahn TJ, Thomas MA. A pilot validation of multi-echo based echo-planar correlated spectroscopic imaging in human calf muscles. NMR Biomed 2014;27:1176-1183.

31. Thomas MA, Lipnick S, Velan SS, Liu X, Banakar S, Binesh N, Ramadan S, Ambrosio A, Raylman RR, Sayre J, DeBruhl N, Bassett L. Investigation of breast cancer using two-dimensional MRS. NMR Biomed 2009;22:77-91.

32. He J, Goodpaster BH, Kelley DE. Effects of weight loss and physical activity on muscle lipid content and droplet size. Obes Res 2004;12:761-769.

33. Brandejsky V, Kreis R, Boesch C. Restricted or severely hindered diffusion of intramyocellular lipids in human skeletal muscle shown by in vivo proton MR spectroscopy. Magn Reson Med 2012;67:310-316.

34. Cao P, Fan SJ, Wang AM, Xie VB, Qiao Z, Brittenham GM, Wu EX. Diffusion magnetic resonance monitors intramyocellular lipid droplet size in vivo. Magn Reson Med 2014;73:59-69.

35. Kreis R, Jung B, Rotman S, Slotboom J, Boesch C. Non-invasive observation of acetyl-group buffering by 1H-MR spectroscopy in exercising human muscle. NMR Biomed 1999;12:471-476.

36. Lindeboom L, Nabuurs CI, Hoeks J, Brouwers B, Phielix E, Kooi ME, Hesselink MK, Wildberger JE, Stevens RD, Koves T, Muoio DM, Schrauwen P, Schrauwen-Hinderling VB. Long-echo time MR spectroscopy for skeletal muscle acetylcarnitine detection. J Clin Invest 2014;124:4915-4925.

37. Delikatny EJ, Chawla S, Leung DJ, Poptani H. MR-visible lipids and the tumor microenvironment. NMR Biomed 2011;24:592-611.

38. Arias-Mendoza F, Payne GS, Zakian K, Stubbs M, O'Connor OA, Mojahed H, Smith MR, Schwarz AJ, Shukla-Dave A, Howe F, Poptani H, Lee SC, Pettengel R, Schuster SJ, Cunningham D, Heerschap A, Glickson JD, Griffiths JR, Koutcher JA, Leach MO, Brown TR. Noninvasive phosphorus magnetic resonance spectroscopic imaging predicts outcome to first-line chemotherapy in newly diagnosed patients with diffuse large B-cell lymphoma. Acad Radiol 2013;20:1122-1129.

39. Podo F. Tumour phospholipid metabolism. NMR Biomed 1999;12:413-439.

40. Podo F, Canevari S, Canese R, Pisanu ME, Ricci A, Iorio E. MR evaluation of response to targeted treatment in cancer cells. NMR Biomed 2011;24:648-672.




Proc. Intl. Soc. Mag. Reson. Med. 24 (2016)