Skip to main content

Advertisement

Log in

Correlation of bone marrow cellularity and metabolic activity in healthy volunteers with simultaneous PET/MR imaging

  • Scientific Article
  • Published:
Skeletal Radiology Aims and scope Submit manuscript

Abstract

Objective

To evaluate the correlation between bone marrow cellularity (BMC) and metabolic activity in healthy subjects and to see whether yellow marrow is indeed metabolically quiescent. Because metabolic activity can be assumed to reflect vascularity, we assessed the relationship between regional metabolic activity and geographic frequency of metastases as noted in the literature.

Materials and methods

Two hundred and twenty locations (ten in each side of the pelvis and proximal femur) were evaluated in 11 consecutive healthy volunteers with simultaneous PET/MR. BMC was calculated through precise water–fat fraction quantification with a 6-echo gradient echo. We analyzed correlations between cellularity and SUVr, age, and R2*. We also looked at the relation between our results and the reported prevalence of metastases.

Results

There was moderate but statistically significant correlation between BMC and metabolic activity (r = 0.636, p < 0.0001). Interestingly, the iliac and sacrum had higher metabolic activity relative to cellularity, whereas the femoral neck and lesser trochanter showed lower SUVr than other regions with the similar cellularity. The relatively lower metabolic status of the femoral neck conflicted with its reported high frequency of metastasis. Excluding regions with almost no remaining red marrow, cellularity showed inverse relationship with age (r = 0.476, p < 0.0001) and direct relationship with R2* (r = 0.532, p < 0.0010).

Conclusions

Metabolic activity of bone marrow was largely dependent on BMC while yellow marrow seems metabolically quiescent. The discrepancy between the assumed vascularity as determined by metabolic activity and reported sites of metastasis suggested that the process of bone metastasis may not depend entirely on vascularity.

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

Access this article

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

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

References

  1. Hwang S, Panicek DM. Magnetic resonance imaging of bone marrow in oncology, part 1. Skelet Radiol. 2007;36(10):913–20.

    Article  Google Scholar 

  2. Navarro SM, Matcuk GR, Patel DB, Skalski M, White EA, Tomasian A, et al. Musculoskeletal imaging findings of hematologic malignancies. Radiographics. 2017;37(3):881–900.

    Article  PubMed  Google Scholar 

  3. Basu S, Houseni M, Bural G, Chamroonat W, Udupa J, Mishra S, et al. Magnetic resonance imaging based bone marrow segmentation for quantitative calculation of pure red marrow metabolism using 2-deoxy-2-[F-18]fluoro-d-glucose-positron emission tomography: a novel application with significant implications for combined structure-function approach. Mol Imaging Biol. 2007;9(6):361–5.

    Article  PubMed  Google Scholar 

  4. Budzik JF, Lefebvre G, Forzy G, El Rafei M, Chechin D, Cotten A. Study of proximal femoral bone perfusion with 3D T1 dynamic contrast-enhanced MRI: a feasibility study. Eur Radiol. 2014;24(12):3217–23.

    Article  PubMed  Google Scholar 

  5. Krishnamurthy GT, Tubis M, Hiss J, Blahd WH. Distribution pattern of metastatic bone disease. A need for total body skeletal image. JAMA. 1977;237(23):2504–6.

    Article  CAS  PubMed  Google Scholar 

  6. Tubiana-Hulin M. Incidence, prevalence and distribution of bone metastases. Bone. 1991;12(Suppl 1):S9–10.

    Article  PubMed  Google Scholar 

  7. Choi J, Raghavan M. Diagnostic imaging and image-guided therapy of skeletal metastases. Cancer control. 2012;19(2):102–12.

    Article  PubMed  Google Scholar 

  8. Hardouin P, Rharass T, Lucas S. Bone marrow adipose tissue: to be or not to be a typical adipose tissue? Front Endocrinol (Lausanne). 2016;7:85.

    Article  Google Scholar 

  9. 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(2):546–52.

    Article  CAS  PubMed  Google Scholar 

  10. Schraml C, Schmid M, Gatidis S, Schmidt H, la Fougere 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(4):1048–56.

    Article  PubMed  Google Scholar 

  11. Nakamura-Ishizu A, Takizawa H, Suda T. The analysis, roles and regulation of quiescence in hematopoietic stem cells. Development. 2014;141(24):4656–66.

    Article  CAS  PubMed  Google Scholar 

  12. Suva LJ, Washam C, Nicholas RW, Griffin RJ. Bone metastasis: mechanisms and therapeutic opportunities. Nat Rev Endocrinol. 2011;7(4):208–18.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Lafage-Proust MH, Roche B, Langer M, Cleret D, Vanden Bossche A, Olivier T, et al. Assessment of bone vascularization and its role in bone remodeling. Bonekey rep. 2015;4:662.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Heinonen I, Kemppainen J, Kaskinoro K, Langberg H, Knuuti J, Boushel R, et al. Bone blood flow and metabolism in humans: effect of muscular exercise and other physiological perturbations. J Bone Miner Res. 2013;28(5):1068–74.

    Article  CAS  PubMed  Google Scholar 

  15. 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(9):1097–101.

    Article  PubMed  Google Scholar 

  16. Dixon WT. Simple proton spectroscopic imaging. Radiology. 1984;153(1):189–94.

    Article  CAS  PubMed  Google Scholar 

  17. Reeder SB, McKenzie CA, Pineda AR, Yu H, Shimakawa A, Brau AC, et al. Water–fat separation with IDEAL gradient-echo imaging. J Magn Reson Imaging. 2007;25(3):644–52.

    Article  PubMed  Google Scholar 

  18. Ma J. Dixon techniques for water and fat imaging. J Magn Reson Imaging. 2008;28(3):543–58.

    Article  PubMed  Google Scholar 

  19. Hernando D, Kellman P, Haldar JP, Liang ZP. Robust water/fat separation in the presence of large field inhomogeneities using a graph cut algorithm. Magn Reson Med. 2010;63(1):79–90.

    PubMed  PubMed Central  Google Scholar 

  20. Gheysens O, Postnov A, Deroose CM, Vandermeulen C, de Hoon J, Declercq R, et al. Quantification, variability, and reproducibility of basal skeletal muscle glucose uptake in healthy humans using 18F-FDG PET/CT. J Nucl Med. 2015;56(10):1520–6.

    Article  CAS  PubMed  Google Scholar 

  21. Tsujikawa T, Tsuyoshi H, Kanno M, Yamada S, Kobayashi M, Narita N, et al. Selected PET radiomic features remain the same. Oncotarget. 2018;9(29):20734–46.

    Article  PubMed  PubMed Central  Google Scholar 

  22. Picci P, Manfrini M, Fabbri N, Gambarotti M, Vanel D. Atlas of musculoskeletal tumors and tumorlike lesions. The Rizzoli case archive. Berlin: Springer; 2014. p. 251–2.

    Book  Google Scholar 

  23. Feng H, Wang J, Xu J, Chen W, Zhang Y. The surgical management and treatment of metastatic lesions in the proximal femur: a mini review. Medicine (Baltimore). 2016;95(28):e3892.

    Article  Google Scholar 

  24. Yao WJ, Hoh CK, Hawkins RA, Glaspy JA, Weil JA, Lee SJ, et al. Quantitative PET imaging of bone marrow glucose metabolic response to hematopoietic cytokines. J Nucl Med. 1995;36(5):794–9.

    CAS  PubMed  Google Scholar 

  25. Vande Berg BC, Lecouvet FE, Galant C, Simoni P, Malghem J. Normal variants of the bone marrow at MR imaging of the spine. Semin Musculoskelet Radiol. 2009;13(2):87–96.

    Article  PubMed  Google Scholar 

  26. Hernando D, Haldar JP, Sutton BP, Ma J, Kellman P, Liang ZP. Joint estimation of water/fat images and field inhomogeneity map. Magn Reson Med. 2008;59(3):571–80.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Rosenkrantz AB, Friedman K, Chandarana H, Melsaether A, Moy L, Ding YS, et al. Current status of hybrid PET/MRI in oncologic imaging. AJR Am J Roentgenol. 2016;206(1):162–72.

    Article  PubMed  Google Scholar 

  28. Moore SG, Dawson KL. Red and yellow marrow in the femur: age-related changes in appearance at MR imaging. Radiology. 1990;175(1):219–23.

    Article  CAS  PubMed  Google Scholar 

  29. 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(8):1326–38.

    Article  PubMed  Google Scholar 

  30. Vande Berg BC, Malghem J, Lecouvet FE, Maldague B. Magnetic resonance imaging of the normal bone marrow. Skelet Radiol. 1998;27(9):471–83.

    Article  CAS  Google Scholar 

  31. Paget S. The distribution of secondary growths in cancer of the breast. 1889. Cancer Metastasis Rev. 1989;8(2):98–101.

    CAS  PubMed  Google Scholar 

  32. Fidler IJ. The pathogenesis of cancer metastasis: the 'seed and soil' hypothesis revisited. Nat Rev Cancer. 2003;3(6):453–8.

    Article  CAS  PubMed  Google Scholar 

  33. Wehrli FW, Ford JC, Haddad JG. Osteoporosis: clinical assessment with quantitative MR imaging in diagnosis. Radiology. 1995;196(3):631–41.

    Article  CAS  PubMed  Google Scholar 

  34. Baum T, Yap SP, Karampinos DC, Nardo L, Kuo D, Burghardt AJ, et al. Does vertebral bone marrow fat content correlate with abdominal adipose tissue, lumbar spine bone mineral density, and blood biomarkers in women with type 2 diabetes mellitus? J Magn Reson Imaging. 2012;35(1):117–24.

    Article  PubMed  Google Scholar 

  35. Song HK, Wehrli FW, Ma J. Field strength and angle dependence of trabecular bone marrow transverse relaxation in the calcaneus. J Magn Reson Imaging. 1997;7(2):382–8.

    Article  CAS  PubMed  Google Scholar 

  36. Hofmann M, Bezrukov I, Mantlik F, Aschoff P, Steinke F, Beyer T, et al. MRI-based attenuation correction for whole-body PET/MRI: quantitative evaluation of segmentation- and atlas-based methods. J Nucl Med. 2011;52(9):1392–9.

    Article  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Chuan Huang.

Ethics declarations

Conflict of interest

The authors declare that they have no conflicts of interest.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.

Informed consent

Informed consent was obtained from all individual participants included in the study.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Fukuda, T., Huang, M., Janardhanan, A. et al. Correlation of bone marrow cellularity and metabolic activity in healthy volunteers with simultaneous PET/MR imaging. Skeletal Radiol 48, 527–534 (2019). https://doi.org/10.1007/s00256-018-3058-6

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00256-018-3058-6

Keywords

Navigation