Skip to main content

Advertisement

Log in

Assessment of Melanin Content and its Influence on Susceptibility Contrast in Melanoma Metastases

  • Original Article
  • Published:
Clinical Neuroradiology Aims and scope Submit manuscript

Abstract

Purpose

To quantify the influence of melanin content on magnetic susceptibility of cerebral melanoma metastases.

Methods

Patients with non-hemorrhagic metastases were included based on the absence of susceptibility blooming artifacts. Susceptibility maps were calculated from 3D gradient echo data, using Laplacian-based phase unwrapping, sophisticated harmonic artefact reduction for phase data (V-SHARP) with varying spherical kernel sizes for background field removal and the iLSQR algorithm for the inversion of phase data. Susceptibility maps were referenced to cerebrospinal fluid. Non-hemorrhagic metastases were identified on contrast-enhanced T1-weighted images and susceptibility weighted images. Metastases masks were drawn on T1-weighted post-contrast images and used to compute mean susceptibility values of each metastasis.

Results

A total of 33 non-hemorrhagic melanoma brain metastases in 20 patients were quantitatively evaluated. Metastases without and with hyperintense signal on T1-weighted images, which corresponds to the melanin content, showed median susceptibility values of −0.028 ppm and −0.020 ppm, respectively. The susceptibility differences between metastases without and with T1-weighted hyperintense signal was not statistically significant (p ≥ 0.05).

Conclusion

Non-hemorrhagic cerebral melanoma metastases showed weak diamagnetic susceptibility values and susceptibility did not significantly correlate to T1-weighted signals. Therefore, melanin does not seem to be a major contributor to susceptibility in cerebral melanoma metastases.

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

Similar content being viewed by others

References:

  1. Barnholtz-Sloan JS, Sloan AE, Davis FG, Vigneau FD, Lai P, Sawaya RE. Incidence proportions of brain metastases in patients diagnosed (1973 to 2001) in the Metropolitan Detroit Cancer Surveillance System. J Clin Oncol. 2004;22:2865–72.

    PubMed  Google Scholar 

  2. Brożyna AA, Jóźwicki W, Roszkowski K, Filipiak J, Slominski AT. Melanin content in melanoma metastases affects the outcome of radiotherapy. Oncotarget. 2016;7:17844–53.

    PubMed  PubMed Central  Google Scholar 

  3. Fearnley JM, Lees AJ. Ageing and Parkinson’s disease: substantia nigra regional selectivity. Brain. 1991;114:2283–301.

    PubMed  Google Scholar 

  4. Escott EJ. A variety of appearances of malignant melanoma in the head: a review. Radiographics. 2001;21:625–39.

    CAS  PubMed  Google Scholar 

  5. Woodruff WW Jr., Djang WT, McLendon RE, Heinz ER, Voorhees DR. Intracerebral malignant melanoma: high-field-strength MR imaging. Radiology. 1987;165:209–13.

    PubMed  Google Scholar 

  6. Atlas SW, Grossman RI, Gomori JM, Guerry D, Hackney DB, Goldberg HI, Zimmerman RA, Bilaniuk LT. MR imaging of intracranial metastatic melanoma. J Comput Assist Tomogr. 1987;11:577–82.

    CAS  PubMed  Google Scholar 

  7. Isiklar I, Leeds NE, Fuller GN, Kumar AJ. Intracranial metastatic melanoma: correlation between MR imaging characteristics and melanin content. AJR Am J Roentgenol. 1995;165:1503–12.

    CAS  PubMed  Google Scholar 

  8. Enochs WS, Hyslop WB, Bennett HF, Brown RD 3rd, Koenig SH, Swartz HM. Sources of the increased longitudinal relaxation rates observed in melanotic melanoma. An in vitro study of synthetic melanins. Invest Radiol. 1989;24:794–804.

    CAS  PubMed  Google Scholar 

  9. Gramsch C, Göricke SL, Behrens F, Zimmer L, Schadendorf D, Krasny A, Forsting M, Schlamann MU. Isolated cerebral susceptibility artefacts in patients with malignant melanoma: metastasis or not? Eur Radiol. 2013;23:2622–7.

    PubMed  Google Scholar 

  10. Parizel PM, Makkat S, Van Miert E, Van Goethem JW, van den Hauwe L, De Schepper AM. Intracranial hemorrhage: principles of CT and MRI interpretation. Eur Radiol. 2001;11:1770–83.

    CAS  PubMed  Google Scholar 

  11. Haacke EM, Liu S, Buch S, Zheng W, Wu D, Ye Y. Quantitative susceptibility mapping: current status and future directions. Magn Reson Imaging. 2015;33:1–25.

    PubMed  Google Scholar 

  12. Chen W, Gauthier SA, Gupta A, Comunale J, Liu T, Wang S, Pei M, Pitt D, Wang Y. Quantitative susceptibility mapping of multiple sclerosis lesions at various ages. Radiology. 2014;271:183–92.

    PubMed  PubMed Central  Google Scholar 

  13. Liu T, Eskreis-Winkler S, Schweitzer AD, Chen W, Kaplitt MG, Tsiouris AJ, Wang Y. Improved subthalamic nucleus depiction with quantitative susceptibility mapping. Radiology. 2013;269:216–23.

    PubMed  PubMed Central  Google Scholar 

  14. Wharton S, Bowtell R. Effects of white matter microstructure on phase and susceptibility maps. Magn Reson Med. 2015;73:1258–69.

    PubMed  Google Scholar 

  15. Langkammer C, Schweser F, Krebs N, Deistung A, Goessler W, Scheurer E, Sommer K, Reishofer G, Yen K, Fazekas F, Ropele S, Reichenbach JR. Quantitative susceptibility mapping (QSM) as a means to measure brain iron? A post mortem validation study. Neuroimage. 2012;62:1593–9.

    PubMed  PubMed Central  Google Scholar 

  16. Deistung A, Schweser F, Wiestler B, Abello M, Roethke M, Sahm F, Wick W, Nagel AM, Heiland S, Schlemmer HP, Bendszus M, Reichenbach JR, Radbruch A. Quantitative susceptibility mapping differentiates between blood depositions and calcifications in patients with Glioblastoma. PLoS One. 2013;8:e57924. https://doi.org/10.1371/journal.pone.0057924

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Liu S, Mok K, Neelavalli J, Cheng YC, Tang J, Ye Y, Haacke EM. Improved MR Venography using quantitative susceptibility-weighted imaging. J Magn Reson Imaging. 2014;40:698–708.

    PubMed  Google Scholar 

  18. Prock T, Collins DJ, Dzik-Jurasz ASK, Leach MO. An algorithm for the optimum combination of data from arbitrary magnetic resonance phased array probes. Phys Med Biol. 2002;47:N39–46.

    CAS  PubMed  Google Scholar 

  19. Smith SM. Fast robust automated brain extraction. Hum Brain Mapp. 2002;17:143–55.

    PubMed  PubMed Central  Google Scholar 

  20. Li W, Avram AV, Wu B, Xiao X, Liu CL. Integrated Laplacian-based phase unwrapping and background phase removal for quantitative susceptibility mapping. NMR Biomed. 2014;27:219–27.

    PubMed  Google Scholar 

  21. Wu B, Li W, Guidon A, Liu CL. Whole brain susceptibility mapping using compressed sensing. Magn Reson Med. 2012;67:137–47.

    PubMed  Google Scholar 

  22. Li W, Wu B, Liu CL. Quantitative susceptibility mapping of human brain reflects spatial variation in tissue composition. Neuroimage. 2011;55:1645–56.

    PubMed  PubMed Central  Google Scholar 

  23. Li W, Wang N, Yu F, Han H, Cao W, Romero R, Tantiwongkosi B, Duong TQ, Liu C. A method for estimating and removing streaking artifacts in quantitative susceptibility mapping. Neuroimage. 2015;108:111–22.

    PubMed  Google Scholar 

  24. Straub S, Schneider TM, Emmerich J, Freitag MT, Ziener CH, Schlemmer HP, Ladd ME, Laun FB. Suitable reference tissues for quantitative susceptibility mapping of the brain. Magn Reson Med. 2017;78:204–14.

    PubMed  Google Scholar 

  25. Patenaude B, Smith SM, Kennedy DN, Jenkinson M. A Bayesian model of shape and appearance for subcortical brain segmentation. Neuroimage. 2011;56:907–22.

    PubMed  PubMed Central  Google Scholar 

  26. Deistung A, Schäfer A, Schweser F, Biedermann U, Turner R, Reichenbach JR. Toward in vivo histology: a comparison of quantitative susceptibility mapping (QSM) with magnitude-, phase-, and R2*-imaging at ultra-high magnetic field strength. Neuroimage. 2013;65:299–314.

    PubMed  Google Scholar 

  27. Nolden M, Zelzer S, Seitel A, Wald D, Müller M, Franz AM, Maleike D, Fangerau M, Baumhauer M, Maier-Hein L, Maier-Hein KH, Meinzer HP, Wolf I. The Medical Imaging Interaction Toolkit: challenges and advances. Int J Comput Assist Radiol Surg. 2013;8:607–20.

    PubMed  Google Scholar 

  28. Ellingson BM, Zaw T, Cloughesy TF, Naeini KM, Lalezari S, Mong S, Lai A, Nghiemphu PL, Pope WB. Comparison between intensity normalization techniques for dynamic susceptibility contrast (DSC)-MRI estimates of cerebral blood volume (CBV) in human gliomas. J Magn Reson Imaging. 2012;35:1472–7.

    PubMed  Google Scholar 

  29. Pizzichetta MA, Talamini R, Stanganelli I, Puddu P, Bono R, Argenziano G, Veronesi A, Trevisan G, Rabinovitz H, Soyer HP. Amelanotic/hypomelanotic melanoma: clinical and dermoscopic features. Brit J Dermatol. 2004;150:1117–24.

    CAS  Google Scholar 

  30. Franceschi AM, Moschos SJ, Anders CK, Glaubiger S, Collichio FA, Lee CB, Castillo M, Lee YZ. Use of Susceptibility-Weighted Imaging (SWI) in the Detection of Brain Hemorrhagic Metastases from Breast Cancer and Melanoma. J Comput Assist Tomogr. 2016;40:803–5.

    PubMed  PubMed Central  Google Scholar 

  31. Gaviani P, Mullins ME, Braga TA, Hedley-Whyte ET, Halpern EF, Schaefer PS, Henson JW. Improved detection of metastatic melanoma by T2(*)-weighted imaging. AJNR Am J Neuroradiol. 2006;27:605–8.

    CAS  PubMed  Google Scholar 

  32. Langkammer C, Krebs N, Goessler W, Scheurer E, Yen K, Fazekas F, Ropele S. Susceptibility induced gray-white matter MRI contrast in the human brain. Neuroimage. 2012;59:1413–9.

    PubMed  PubMed Central  Google Scholar 

  33. Wharton S, Bowtell R. Fiber orientation-dependent white matter contrast in gradient echo MRI. Proc Natl Acad Sci USA. 2012;109:18559–64.

    CAS  PubMed  Google Scholar 

  34. Drayer B, Burger P, Darwin R, Riederer S, Herfkens R, Johnson GA. MRI of Brain Iron. AJR Am J Roentgenol. 1986;147:103–10.

    CAS  PubMed  Google Scholar 

  35. Riley PA. Melanin. Int J Biochem Cell Biol. 1997;29:1235–9.

    CAS  PubMed  Google Scholar 

  36. Ito S, Jimbow K. Quantitative-analysis of Eumelanin and Pheomelanin in hair and melanomas. J Investig Dermatol. 1983;80:268–72.

    CAS  PubMed  Google Scholar 

  37. Bush WD, Garguilo J, Zucca FA, Albertini A, Zecca L, Edwards GS, Nemanich RJ, Simon JD. The surface oxidation potential of human neuromelanin reveals a spherical architecture with a pheomelanin core and a eumelanin surface. Proc Natl Acad Sci USA. 2006;103:14785–9.

    CAS  PubMed  Google Scholar 

  38. Enochs WS, Nilges MJ, Swartz HM. Purified human Neuromelanin, synthetic Dopamine melanin as a potential model pigment, and the normal human Substantia-Nigra—characterization by electron-Paramagnetic-resonance spectroscopy. J Neurochem. 1993;61:68–79.

    CAS  PubMed  Google Scholar 

  39. Zecca L, Gallorini M, Schünemann V, Trautwein AX, Gerlach M, Riederer P, Vezzoni P, Tampellini D. Iron, neuromelanin and ferritin content in the substantia nigra of normal subjects at different ages: consequences for iron storage and neurodegenerative processes. J Neurochem. 2001;76:1766–73.

    CAS  PubMed  Google Scholar 

  40. Trujillo P, Summers PE, Ferrari E, Zucca FA, Sturini M, Mainardi LT, Cerutti S, Smith AK, Smith SA, Zecca L, Costa A. Contrast mechanisms associated with Neuromelanin-MRI. Magn Reson Med. 2017;78:1790–800.

    CAS  PubMed  Google Scholar 

  41. Li Y, Xie Y, Wang Z, Zang N, Carniato F, Huang Y, Andolina CM, Parent LR, Ditri TB, Walter ED, Botta M, Rinehart JD, Gianneschi NC. Structure and function of iron-loaded synthetic melanin. ACS Nano. 2016;10:10186–94.

    CAS  PubMed  PubMed Central  Google Scholar 

  42. Enochs WS, Petherick P, Bogdanova A, Mohr U, Weissleder R. Paramagnetic metal scavenging by melanin: MR imaging. Radiology. 1997;204:417–23.

    CAS  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Till M. Schneider.

Ethics declarations

Conflict of interest

S. Straub, F.B. Laun, M.T. Freitag, C. Kölsche, A. von Deimling, M. Denoix, M. Bendszus, H.-P. Schlemmer, M.E. Ladd and T.M. Schneider declare that they have no competing interests.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Straub, S., Laun, F.B., Freitag, M.T. et al. Assessment of Melanin Content and its Influence on Susceptibility Contrast in Melanoma Metastases. Clin Neuroradiol 30, 607–614 (2020). https://doi.org/10.1007/s00062-019-00816-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00062-019-00816-x

Keywords

Navigation