Skip to main content
SpringerLink
Log in

Molecular In Vivo Imaging of Bone Marrow Adipose Tissue

  • Molecular Biology of Bone Marrow Fat Adiposity (B van der Eerden, Section Editor)
  • Published:
Current Molecular Biology Reports Aims and scope Submit manuscript

Abstract

Purpose of Review

The in vivo study of molecular processes in human bone marrow is important for both diagnostics and understanding of disease pathophysiology. Traditionally, the hematopoietic component of the bone marrow has been a research focus, but recently, the role of bone marrow adipose tissue has been gaining interest in many applications. The purpose of the present review is to give an overview of existing imaging modalities allowing in vivo molecular imaging of bone marrow adipose tissue in humans with an emphasis on technical aspects: the characteristics of the extracted parameters and their application in bone marrow adipose tissue.

Recent Findings

Magnetic resonance (MR) imaging (MRI) and spectroscopy (MRS) are the most frequently used imaging methods for the examination of bone marrow adipose tissue as they provide rich soft tissue contrast and come without ionizing radiation. Existing MR methods allow the extraction of many different measures including proton density fat fraction, fatty acid characteristics, and diffusion and perfusion properties. However, many available techniques have to be carefully adjusted to be used in the investigation of the fat signal component, especially in the presence of trabecular bone. Dual-energy computed tomography (DECT) is an emerging technique—not yet widely available—which appears to be a promising alternative to MR for rapid fat fraction assessment. Positron emission tomography (PET) allows additional functional metabolic imaging and therefore provides valuable additional information (e.g., glucose uptake) to MR-based parameters at the cost of ionizing radiation.

Summary

Bone marrow imaging still appears to be a niche with remaining technical challenges using existing imaging modalities. A good working knowledge of the underlying physical and technical principles is required as most techniques are yet not available out of the box and may need to be adjusted to fit the requirements for bone marrow adipose tissue imaging. In summary, MR, DECT, and PET enable the measurement of several inherently different parameters in in vivo molecular imaging of bone marrow adipose tissue. The growing interest for molecular imaging markers of bone marrow, thanks to its high metabolic and clinical significance, may eventually lead to new developments, as well as improvements of emerging techniques as soon as they become more broadly available.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1

Similar content being viewed by others

References

Papers of particular interest, published recently, have been highlighted as: • Of importance •• Of major importance

  1. Scheller EL, Rosen CJ. What’s the matter with MAT? Marrow adipose tissue, metabolism, and skeletal health. Ann N Y Acad Sci. 2014;1311:14–30.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  2. Devlin MJ, Rosen CJ. The bone-fat interface: basic and clinical implications of marrow adiposity. Lancet Diabetes Endocrinol. 2015;3:141–7.

    Article  PubMed  CAS  Google Scholar 

  3. Scheller EL, Doucette CR, Learman BS, Cawthorn WP, Khandaker S, Schell B, et al. Region-specific variation in the properties of skeletal adipocytes reveals regulated and constitutive marrow adipose tissues. Nat Commun. 2015;6:7808.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  4. Motyl KJ, Guntur AR, Carvalho AL, Rosen CJ. Energy metabolism of bone. Toxicol Pathol. 2017;45:887–93.

    Article  PubMed  CAS  Google Scholar 

  5. Horowitz MC, Berry R, Holtrup B, Sebo Z, Nelson T, Fretz JA, et al. Bone marrow adipocytes. Adipocyte. 2017;6:193–204.

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  6. Schwartz AV. Marrow fat and bone: review of clinical findings. Front Endocrinol. 2015;6:40.

    Article  CAS  Google Scholar 

  7. Veldhuis-Vlug AG, Rosen CJ. Clinical implications of bone marrow adiposity. J Intern Med. 2017;283:121–39. https://doi.org/10.1111/joim.12718.

    Article  Google Scholar 

  8. Zhou BO, Yu H, Yue R, Zhao Z, Rios JJ, Naveiras O, et al. Bone marrow adipocytes promote the regeneration of stem cells and haematopoiesis by secreting SCF. Nat Cell Biol. 2017;19:891–903.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  9. Hardouin P, Marie PJ, Rosen CJ. New insights into bone marrow adipocytes: report from the first European meeting on bone marrow adiposity (BMA 2015). Bone. 2016;93:212–5.

    Article  PubMed  Google Scholar 

  10. van der Eerden B, van Wijnen A. Meeting report of the 2016 bone marrow adiposity meeting. Adipocyte. 2017;6:304–13.

    Article  PubMed  PubMed Central  Google Scholar 

  11. Moulopoulos LA, Koutoulidis V. Bone marrow MRI: a pattern-based approach; 2015. p. 1–172.

    Google Scholar 

  12. Khoo MMY, Tyler PA, Saifuddin A, Padhani AR. Diffusion-weighted imaging (DWI) in musculoskeletal MRI: a critical review. Skelet Radiol. 2011;40:665–81.

    Article  Google Scholar 

  13. MacEwan IJ, Glembotski NE, D'Lima D, Bae W, Masuda K, Rashidi HH, et al. Proton density water fraction as a biomarker of bone marrow cellularity: validation in ex vivo spine specimens. Magn Reson Imaging. 2014;32:1097–101.

    Article  PubMed  Google Scholar 

  14. Hu HH, Kan HE. Quantitative proton MR techniques for measuring fat. NMR Biomed. 2013;26:1609–29.

    Article  PubMed  CAS  Google Scholar 

  15. Berglund J, Ahlström H, Kullberg J. Model-based mapping of fat unsaturation and chain length by chemical shift imaging-phantom validation and in vivo feasibility. Magn Reson Med. 2012;68:1815–27.

    Article  PubMed  CAS  Google Scholar 

  16. Karampinos DC, Ruschke S, Dieckmeyer M, Diefenbach M, Franz D, Gersing AS, et al. Quantitative MRI and spectroscopy of bone marrow. J Magn Reson Imaging. 2017;7:448.

    Google Scholar 

  17. Reeder SB, Hu HH, Sirlin CB. Proton density fat-fraction: a standardized mr-based biomarker of tissue fat concentration. J Magn Reson Imaging. 2012;36:1011–4.

    Article  PubMed  PubMed Central  Google Scholar 

  18. Pansini VM, Monnet A, Salleron J, Penel G, Migaud H, Cotten A. Reproducibility of 1H MR spectroscopy of hip bone marrow at 3 tesla. J Magn Reson Imaging. 2012;36:1445–9.

    Article  PubMed  Google Scholar 

  19. Li X, Kuo D, Schafer AL, Porzig A, Link TM, Black D, et al. Quantification of vertebral bone marrow fat content using 3 tesla MR spectroscopy: reproducibility, vertebral variation, and applications in osteoporosis. J Magn Reson Imaging. 2011;33:974–9.

    Article  PubMed  PubMed Central  Google Scholar 

  20. Singhal V, Miller KK, Torriani M, Bredella MA. Short- and long-term reproducibility of marrow adipose tissue quantification by 1H-MR spectroscopy. Skelet Radiol. 2016;45:221–5.

    Article  Google Scholar 

  21. • Dieckmeyer M, Ruschke S, Cordes C, Yap SP, Kooijman H, Hauner H, et al. The need for T2 correction on MRS-based vertebral bone marrow fat quantification: implications for bone marrow fat fraction age dependence. NMR Biomed. 2015;28:432–9. This study shows the confounding effect of T2 weighting on MRS measurements in vertebral bone marrow and why PDFF should be measured instead of sFF.

    Article  PubMed  CAS  Google Scholar 

  22. Arentsen L, Yagi M, Takahashi Y, Bolan PJ, White M, Yee D, et al. Validation of marrow fat assessment using noninvasive imaging with histologic examination of human bone samples. Bone. 2015;72:118–22.

    Article  PubMed  Google Scholar 

  23. Hernando D, Sharma SD, Aliyari Ghasabeh M, et al. Multisite, multivendor validation of the accuracy and reproducibility of proton-density fat-fraction quantification at 1.5T and 3T using a fat-water phantom. Magn Reson Med. 2016; https://doi.org/10.1002/mrm.26228.

  24. Martin J, Nicholson G, Cowin G, Ilente C, Wong W, Kennedy D. Rapid determination of vertebral fat fraction over a large range of vertebral bodies. J Med Imaging Radiat Oncol. 2014;58:155–63.

    Article  PubMed  Google Scholar 

  25. • Baum T, Yap SP, Dieckmeyer M, Ruschke S, Eggers H, Kooijman H, et al. Assessment of whole spine vertebral bone marrow fat using chemical shift-encoding based water-fat MRI. J Magn Reson Imaging. 2015;42:1018–23. Study on whole spine quantitative PDFF mapping achieving an absolute precision error of 1.7%.

    Article  PubMed  Google Scholar 

  26. Karampinos DC, Melkus G, Baum T, Bauer JS, Rummeny EJ, Krug R. Bone marrow fat quantification in the presence of trabecular bone: initial comparison between water-fat imaging and single-voxel MRS. Magn Reson Med. 2013;71:1158–65.

    Article  CAS  Google Scholar 

  27. Gee CS, Nguyen JTK, Marquez CJ, et al. Validation of bone marrow fat quantification in the presence of trabecular bone using MRI. J Magn Reson Imaging. 2014;42:539–44.

    Article  PubMed  PubMed Central  Google Scholar 

  28. Karampinos DC, Ruschke S, Dieckmeyer M, Eggers H, Kooijman H, Rummeny EJ, et al. Modeling of T2* decay in vertebral bone marrow fat quantification. NMR Biomed. 2015;28:1535–42.

    Article  PubMed  CAS  Google Scholar 

  29. Ruschke S, Pokorney A, Baum T, Eggers H, Miller JH, Hu HH, et al. Measurement of vertebral bone marrow proton density fat fraction in children using quantitative water-fat MRI. Magn Reson Mater Phys Biol Med. 2017;30:449–60.

    Article  CAS  Google Scholar 

  30. Le Ster C, Gambarota G, Lasbleiz J, Guillin R, Decaux O, Saint Jalmes H. Breath-hold MR measurements of fat fraction, T1, and T2* of water and fat in vertebral bone marrow. J Magn Reson Imaging. 2016;44:549–55.

    Article  PubMed  Google Scholar 

  31. Le Ster C, Lasbleiz J, Kannengiesser S, Guillin R, Gambarota G, Saint Jalmes H. A fast method for the quantification of fat fraction and relaxation times: comparison of five sites of bone marrow. Magn Reson Imaging. 2017;39:157–61.

    Article  PubMed  Google Scholar 

  32. Hamilton G, Hamilton G, Yokoo T, et al. In vivo characterization of the liver fat 1H MR spectrum. NMR Biomed. 2011;24:784–90.

    Article  PubMed  Google Scholar 

  33. Troitskaia A, Fallone BG, Yahya A. Long echo time proton magnetic resonance spectroscopy for estimating relative measures of lipid unsaturation at 3 T. J Magn Reson Imaging. 2013;37:944–9.

    Article  PubMed  Google Scholar 

  34. Bingölbali A, Fallone BG, Yahya A. Comparison of optimized long echo time STEAM and PRESS proton MR spectroscopy of lipid olefinic protons at 3 Tesla. J Magn Reson Imaging. 2015;41:481–6.

    Article  PubMed  Google Scholar 

  35. Fallone CJ, McKay RT, Yahya A. Long TE STEAM and PRESS for estimating fat olefinic/methyl ratios and relative ω-3 fat content at 3T. J Magn Reson Imaging. 2017;24:238.

    Google Scholar 

  36. Xu K, Sigurdsson S, Gudnason V, Hue T, Schwartz A, Li X. Reliable quantification of marrow fat content and unsaturation level using in vivo MR spectroscopy. Magn Reson Med. 2017;19:109.

    Google Scholar 

  37. Le Bihan D, Breton E, Lallemand D, Grenier P, Cabanis E, Laval-Jeantet M. MR imaging of intravoxel incoherent motions: application to diffusion and perfusion in neurologic disorders. Radiology. 1986;161:401–7.

    Article  PubMed  Google Scholar 

  38. • Dieckmeyer M, Ruschke S, Eggers H, Kooijman H, Rummeny EJ, Kirschke JS, et al. ADC quantification of the vertebral bone marrow water component: removing the confounding effect of residual fat. Magn Reson Med. 2016;46:601. Study showing the confounding effect of the lipid signal in quantitative diffusion-weighted MRI.

    Google Scholar 

  39. Steidle G, Eibofner F, Schick F. Quantitative diffusion imaging of adipose tissue in the human lower leg at 1.5 T. Magn Reson Med. 2011;65:1118–24.

    Article  PubMed  CAS  Google Scholar 

  40. Dietrich O, Geith T, Reiser MF, Baur Melnyk A (2015) Diffusion imaging of the vertebral bone marrow. NMR Biomed n/a–n/a.

  41. Biffar A, Dietrich O, Sourbron S, Duerr H-R, Reiser MF, Baur Melnyk A. Diffusion and perfusion imaging of bone marrow. Eur J Radiol. 2010;76:323–8.

    Article  PubMed  Google Scholar 

  42. Biffar A, Schmidt GP, Sourbron S, D'Anastasi M, Dietrich O, Notohamiprodjo M, et al. Quantitative analysis of vertebral bone marrow perfusion using dynamic contrast-enhanced MRI: initial results in osteoporotic patients with acute vertebral fracture. J Magn Reson Imaging. 2011;33:676–83.

    Article  PubMed  Google Scholar 

  43. Schick F, Forster J, Einsele H, Weiss B, Lutz O, Claussen CD. Magnetization transfer in hemopoietic bone marrow examined by localized proton spectroscopy. Magn Reson Med. 1995;34:792–802.

    Article  PubMed  CAS  Google Scholar 

  44. Yoshioka H, Onaya H, Anno I, Takahashi H, Niitsu M, Itai Y. Fat tissue: relationship between chemical shift and magnetization transfer. Radiology. 1995;195:573–5.

    Article  PubMed  CAS  Google Scholar 

  45. Amano Y, Kumazaki T. Magnetization transfer imaging of bone marrow with and without fat suppression. Acad Radiol. 1997;4:812–5.

    Article  PubMed  CAS  Google Scholar 

  46. Amano Y, Kumazaki T. Correlation between water content and magnetization transfer ratio of the water component in bone marrow using gradient-echo imagings: normal case study. Skelet Radiol. 1998;27:484–7.

    Article  CAS  Google Scholar 

  47. McCollough CH, Leng S, Yu L, Fletcher JG. Dual- and multi-energy CT: principles, technical approaches, and clinical applications. Radiology. 2015;276:637–53.

    Article  PubMed  PubMed Central  Google Scholar 

  48. Lee S, Choi Y-N, Kim H-J. Quantitative material decomposition using spectral computed tomography with an energy-resolved photon-counting detector. Phys Med Biol. 2014;59:5457–82.

    Article  PubMed  Google Scholar 

  49. van Hamersvelt RW, Schilham AMR, Engelke K, den Harder AM, de Keizer B, Verhaar HJ, et al. Accuracy of bone mineral density quantification using dual-layer spectral detector CT: a phantom study. Eur Radiol. 2017;27:4351–9.

    Article  PubMed  PubMed Central  Google Scholar 

  50. Mei K, Schwaiger BJ, Kopp FK, Ehn S, Gersing AS, Kirschke JS, et al. Bone mineral density measurements in vertebral specimens and phantoms using dual-layer spectral computed tomography. Sci Rep. 2017;7:17519.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  51. Pache G, Krauss B, Strohm P, Saueressig U, Blanke P, Bulla S, et al. Dual-energy CT virtual noncalcium technique: detecting posttraumatic bone marrow lesions—feasibility study. Radiology. 2010;256:617–24.

    Article  PubMed  Google Scholar 

  52. Zbijewski W, Sisniega A, Stayman JW, Thawait G, Packard N, Yorkston J, et al. Dual-energy imaging of bone marrow edema on a dedicated multi-source cone-beam CT system for the extremities. Proc SPIE Int Soc Opt Eng. 2015;9412:94120V.

    PubMed  PubMed Central  Google Scholar 

  53. • Bredella MA, Daley SM, Kalra MK, Brown JK, Miller KK, Torriani M. Marrow adipose tissue quantification of the lumbar spine by using dual-energy CT and single-voxel (1)H MR spectroscopy: a feasibility study. Radiology. 2015;277:230–5. In this study, Bredella et al. validate DECT for rapid bone marrow fat fraction quantification against MRS.

    Article  PubMed  PubMed Central  Google Scholar 

  54. Hui SK, Arentsen L, Sueblinvong T, Brown K, Bolan P, Ghebre RG, et al. A phase I feasibility study of multi-modality imaging assessing rapid expansion of marrow fat and decreased bone mineral density in cancer patients. Bone. 2015;73:90–7.

    Article  PubMed  Google Scholar 

  55. Arentsen L, Hansen KE, Yagi M, Takahashi Y, Shanley R, McArthur A, et al. Use of dual-energy computed tomography to measure skeletal-wide marrow composition and cancellous bone mineral density. J Bone Miner Metab. 2017;35:428–36.

    Article  PubMed  CAS  Google Scholar 

  56. Fletcher JW, Djulbegovic B, Soares HP, Siegel BA, Lowe VJ, Lyman GH, et al. Recommendations on the use of 18F-FDG PET in oncology. J Nucl Med. 2008;49:480–508.

    Article  PubMed  Google Scholar 

  57. Grant FD, Fahey FH, Packard AB, Davis RT, Alavi A, Treves ST. Skeletal PET with 18F-fluoride: applying new technology to an old tracer. J Nucl Med. 2008;49:68–78.

    Article  PubMed  Google Scholar 

  58. Comar D, Cartron J-C, Maziere M, Marazano C. Labelling and metabolism of methionine-methyl-<sup>11</sup>C. Eur J Nucl Med. 1976;1:11–4.

    Article  PubMed  CAS  Google Scholar 

  59. Deloar HM, Fujiwara T, Nakamura T, Itoh M, Imai D, Miyake M, et al. Estimation of internal absorbed dose of <emphasis type=“SmallCaps”>l</emphasis>−[methyl-<superscript>11</superscript>C]methionine using whole-body positron emission tomography. Eur J Nucl Med. 1998;25:629–33.

    Article  PubMed  CAS  Google Scholar 

  60. Lee S-G, Gangangari K, Kalidindi TM, Punzalan B, Larson SM, Pillarsetty NVK. Copper-64 labeled liposomes for imaging bone marrow. Nucl Med Biol. 2016;43:781–7.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  61. Paccou J, Hardouin P, Cotten A, Penel G, Cortet B. The role of bone marrow fat in skeletal health: usefulness and perspectives for clinicians. J Clin Endocrinol Metab. 2015;100:3613–21.

    Article  PubMed  CAS  Google Scholar 

  62. Cordes C, Baum T, Dieckmeyer M, Ruschke S, Diefenbach MN, Hauner H, et al. MR-based assessment of bone marrow fat in osteoporosis, diabetes, and obesity. Front Endocrinol. 2016;7:74.

    Article  Google Scholar 

  63. Kugel H, Jung C, Schulte O, Heindel W. Age- and sex-specific differences in the 1H-spectrum of vertebral bone marrow. J Magn Reson Imaging. 2001;13:263–8.

    Article  PubMed  CAS  Google Scholar 

  64. Griffith JF, Yeung DKW, Ma HT, Leung JCS, Kwok TCY, Leung PC. Bone marrow fat content in the elderly: a reversal of sex difference seen in younger subjects. J Magn Reson Imaging. 2012;36:225–30.

    Article  PubMed  Google Scholar 

  65. Roldan-Valadez E, Piña-Jimenez C, Favila R, Rios C. Gender and age groups interactions in the quantification of bone marrow fat content in lumbar spine using 3T MR spectroscopy: a multivariate analysis of covariance (Mancova). Eur J Radiol. 2013;82:e697–702.

    Article  PubMed  Google Scholar 

  66. Maciel JG, de Araújo IM, Carvalho AL, Simão MN, Bastos CM, Troncon LEA, et al. Marrow fat quality differences by sex in healthy adults. 2016; https://doi.org/10.1016/j.jocd.2016.08.002.

  67. Pansini V, Monnet A, Salleron J, Hardouin P, Cortet B, Cotten A. 3 tesla (1) H MR spectroscopy of hip bone marrow in a healthy population, assessment of normal fat content values and influence of age and sex. J Magn Reson Imaging. 2014;39:369–76.

    Article  PubMed  Google Scholar 

  68. Li X, Shet K, Xu K, Rodriguez JP, Pino AM, Kurhanewicz J, et al. Unsaturation level decreased in bone marrow fat of postmenopausal women with low bone density using high resolution magic angle spinning (HRMAS) 1 H NMR spectroscopy. Bone. 2017;105:87–92.

    Article  PubMed  Google Scholar 

  69. Cohen A, Shen W, Dempster DW, Zhou H, Recker RR, Lappe JM, et al. Marrow adiposity assessed on transiliac crest biopsy samples correlates with noninvasive measurement of marrow adiposity by proton magnetic resonance spectroscopy ((1)H-MRS) at the spine but not the femur. Osteoporos Int. 2015;26:2471–8.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  70. Mistry SD, Woods GN, Sigurdsson S, et al. Sex hormones are negatively associated with vertebral bone marrow fat. Bone. 2017;108:20–4.

    Article  PubMed  CAS  Google Scholar 

  71. Salas-Ramirez M, Tran-Gia J, Kesenheimer C, Weng AM, Kosmala A, Heidemeier A, et al. Quantification of fat fraction in lumbar vertebrae: correlation with age and implications for bone marrow dosimetry in molecular radiotherapy. Phys Med Biol. 2017;63:025029. https://doi.org/10.1088/1361-6560/aa9a28.

    Article  Google Scholar 

  72. Aoki T, Yamaguchi S, Kinoshita S, Hayashida Y, Korogi Y. Quantification of bone marrow fat content using iterative decomposition of water and fat with echo asymmetry and least-squares estimation (IDEAL): reproducibility, site variation and correlation with age and menopause. Br J Radiol. 2016;89:20150538.

    Article  PubMed  PubMed Central  Google Scholar 

  73. Sambuceti G, Brignone M, Marini C, Massollo M, Fiz F, Morbelli S, et al. Estimating the whole bone-marrow asset in humans by a computational approach to integrated PET/CT imaging. Eur J Nucl Med Mol Imaging. 2012;39:1326–38.

    Article  PubMed  Google Scholar 

  74. •• Schraml C, Schmid M, Gatidis S, Schmidt H, la Fougère C, Nikolaou K, et al. Multiparametric analysis of bone marrow in cancer patients using simultaneous PET/MR imaging: correlation of fat fraction, diffusivity, metabolic activity, and anthropometric data. J Magn Reson Imaging. 2015;42:1048–56. Schraml et al. instigate for the first time connections between bone marrow metabolic function using PET and MR imaging parameters.

    Article  PubMed  Google Scholar 

  75. Patsch JM, Li X, Baum T, Yap SP, Karampinos DC, Schwartz AV, et al. Bone marrow fat composition as a novel imaging biomarker in postmenopausal women with prevalent fragility fractures. J Bone Miner Res. 2013;28:1721–8.

    Article  PubMed  PubMed Central  Google Scholar 

  76. Breault SR, Heye T, Bashir MR, Dale BM, Merkle EM, Reiner CS, et al. Quantitative dynamic contrast-enhanced MRI of pelvic and lumbar bone marrow: effect of age and marrow fat content on pharmacokinetic parameter values. AJR Am J Roentgenol. 2013;200:W297–303.

    Article  PubMed  Google Scholar 

  77. Krings A, Rahman S, Huang S, Lu Y, Czernik PJ, Lecka-Czernik B. Bone marrow fat has brown adipose tissue characteristics, which are attenuated with aging and diabetes. Bone. 2012;50:546–52.

    Article  PubMed  CAS  Google Scholar 

  78. Lee P, Brychta RJ, Collins MT, Linderman J, Smith S, Herscovitch P, et al. Cold-activated brown adipose tissue is an independent predictor of higher bone mineral density in women. Osteoporos Int. 2013;24:1513–8.

    Article  PubMed  CAS  Google Scholar 

Download references

Funding

Thomas Baum received grant support from the Technical University of Munich, Faculty of Medicine (KKF H01). Dimitrios C. Karampinos received grant support from Philips Healthcare.

Author information

Authors and Affiliations

  1. Department of Diagnostic and Interventional Radiology, Klinikum rechts der Isar, Technical University of Munich, Ismaninger Str. 22, 81675, Munich, Germany

    Stefan Ruschke, Maximilian N. Diefenbach, Daniela Franz & Dimitrios C. Karampinos

  2. Department of Diagnostic and Interventional Neuroradiology, Klinikum rechts der Isar, Technical University of Munich, Ismaninger Str. 22, Munich, 81675, Germany

    Thomas Baum

Authors
  1. Stefan Ruschke
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Maximilian N. Diefenbach
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Daniela Franz
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Thomas Baum
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Dimitrios C. Karampinos
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Stefan Ruschke.

Ethics declarations

All reported studies/experiments with human or animal subjects performed by the authors have been previously published and complied with all applicable ethical standards (including the Helsinki declaration and its amendments, institutional/national research committee standards, and international/national/institutional guidelines).

Conflict of Interest

Stefan Ruschke, Maximilian N. Diefenbach, Daniela Franz, and Thomas Braum declare no conflicts of interest. Dimitrios C. Karampinos reports grants from Philips Healthcare, during the conduct of study and outside the submitted work.

Human and Animal Rights and Informed Consent

This article does not contain any studies with human or animal subjects performed by any of the authors.

Additional information

This article is part of the Topical Collection on Molecular Biology of Bone Marrow Fat Adiposity

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Ruschke, S., Diefenbach, M.N., Franz, D. et al. Molecular In Vivo Imaging of Bone Marrow Adipose Tissue. Curr Mol Bio Rep 4, 25–33 (2018). https://doi.org/10.1007/s40610-018-0092-z

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40610-018-0092-z

Keywords

Search

Navigation