Skip to main content
SpringerLink
Log in

The Role of Advanced Imaging in the Management of Brain Metastases

  • Chapter
  • First Online:
Central Nervous System Metastases

  • 665 Accesses

Abstract

Imaging plays a major role in the management of brain metastases, both to diagnose metastases in the pretreatment period and to differentiate recurrent metastasis from radiation change in the posttreatment period. Since approximately half of brain metastases are solitary at initial presentation, imaging is important to differentiate metastasis from other neoplastic lesions, including primary brain tumors and nonneoplastic lesions. Magnetic resonance (MR) perfusion, particularly dynamic susceptibility contrast, MR spectroscopy, and diffusion-weighted imaging have all been extensively studied to assess the tumoral and peritumoral region to aid in this differential diagnosis. Susceptibility-weighted imaging has shown promise in diagnosing hemorrhagic metastases, including melanoma.

In the posttreatment period, the primary role of imaging is to differentiate recurrent or progressive metastatic disease from radiation injury. Enhancing lesions, reflecting radiation injury, can be seen in more than one-third of cases after stereotactic radiosurgery and can be difficult to differentiate from recurrent metastasis on conventional imaging. Although most occur within 2 years of radiosurgery, they can occur more than 5 years after treatment. Advanced imaging, particularly MR perfusion, MR spectroscopy, and positron emission tomography (PET), has been shown to help differentiate true disease progression from radiation injury.

This chapter will review these advanced imaging techniques in detail, with respect to both the pretreatment and posttreatment periods.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 249.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Soffietti R, Cornu P, Delattre JY, Grant R, Graus F, Grisold W, et al. EFNS guidelines on diagnosis and treatment of brain metastases: report of an EFNS Task Force. Eur J Neurol. 2006;13:674–81.

    Article  CAS  PubMed  Google Scholar 

  2. Delattre JY, Krol G, Thaler HT, Posner JB. Distribution of brain metastases. Arch Neurol. 1988;45:741–4.

    Article  CAS  PubMed  Google Scholar 

  3. Arvold ND, et al. Updates in the management of brain metastases. Neuro Oncol. 2016;18:1043–65.

    Article  PubMed  PubMed Central  Google Scholar 

  4. Lamba N, Muskens IS, DiRisio AC, Meijer L, Briceno V, Edrees H, et al. Stereotactic radiosurgery versus whole-brain radiotherapy after intracranial metastasis resection: a systematic review and meta-analysis. Radiat Oncol. 2017;12:106.

    Article  PubMed  PubMed Central  Google Scholar 

  5. Kohutek ZA, Yamada Y, Chan TA, Brennan CW, Tabar V, Gutin PH, et al. Long-term risk of radionecrosis and imaging changes after stereotactic radiosurgery for brain metastases. J Neurooncol. 2015;125:149–56.

    Article  PubMed  PubMed Central  Google Scholar 

  6. Sneed PK, Mendez J, Vemer-van den Hoek JG, Seymour ZA, Ma L, Molinaro AM, et al. Adverse radiation effect after stereotactic radiosurgery for brain metastases: incidence, time course, and risk factors. J Neurosurg. 2015;123:373–86.

    Article  CAS  PubMed  Google Scholar 

  7. Schuttrumpf LH, Niyazi M, Nachbichler SB, Manapov F, Jansen N, Siefert A, et al. Prognostic factors for survival and radiation necrosis after stereotactic radiosurgery alone or in combination with whole brain radiation therapy for 1–3 cerebral metastases. Radiat Oncol. 2014;9:105.

    Article  PubMed  PubMed Central  Google Scholar 

  8. Fujimoto D, von Eyben R, Gibbs IC, Chang SD, Li G, Harsha GR, et al. Imaging changes over 18 months following stereotactic radiosurgery for brain metastases: both late radiation necrosis and tumor progression can occur. J Neurooncol. 2018;136:207–12.

    Article  PubMed  Google Scholar 

  9. Dequesada IM, Quisling RG, Yachnis A, Friedman WA. Can standard magnetic resonance imaging reliably distinguish recurrent tumor from radiation necrosis after radiosurgery for brain metastases? A radiographic-pathological study. Neurosurgery. 2008;63:898–903.

    Article  PubMed  Google Scholar 

  10. Patel TR, McHugh BJ, Bi WL, Minja FJ, Knisely JP, Chiang VL. A comprehensive review of MR imaging changes following radiosurgery to 500 brain metastases. AJNR Am J Neuroradiol. 2011;32:1885–92.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Tawbi HA, Forsyth PA, Algazi A, Hamid O, Hodi FS, Moschos SJ, et al. Combined nivolumab and ipilimumab in melanoma metastatic to the brain. N Engl J Med. 2018;379:722–30.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Goldberg SB, Gettinger SN, Mahajan A, Chiang AC, Herbst RS, Sznol M, et al. Pembrolizumab for patients with melanoma or non-small-cell lung cancer and untreated brain metastases: early analysis of a non-randomised, open-label, phase 2 trial. Lancet Oncol. 2016;17:976–83.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Colaco RJ, Martin P, Kluger HM, Yu JB, Chiang VL. Does immunotherapy increase the rate of radiation necrosis after radiosurgical treatment of brain metastases? J Neurosurg. 2016;125:17–23.

    Article  CAS  PubMed  Google Scholar 

  14. Okada H, Weller M, Huang R, Finocchiaro G, Gilbert MR, Wick W, et al. Immunotherapy response assessment in neuro-oncology: a report of the RANO working group. Lancet Oncol. 2015;16:e534–42.

    Article  PubMed  PubMed Central  Google Scholar 

  15. Law M, Cha S, Knopp EA, Johnson G, Arnett J, Litt AW. High-grade gliomas and solitary metastases: differentiation by using perfusion and proton spectroscopic MR imaging. Radiology. 2002;222:715–21.

    Article  PubMed  Google Scholar 

  16. Chiang IC, Kuo YT, Lu CY, Yeung KW, Lin WC, Sheu FO, et al. Distinction between high-grade gliomas and solitary metastases using peritumoral 3-T magnetic resonance spectroscopy, diffusion, and perfusion imagings. Neuroradiology. 2004;46:619–27.

    Article  PubMed  Google Scholar 

  17. Hakyemez B, Erdogan C, Gokalp G, Dusak A, Parlak M. Solitary metastases and high-grade gliomas: radiological differentiation by morphometric analysis and perfusion-weighted MRI. Clin Radiol. 2010;65:15–20.

    Article  CAS  PubMed  Google Scholar 

  18. Cha S, Lupo JM, Chen MH, Lamborn KR, McDermott MW, Berger MS, et al. Differentiation of glioblastoma multiforme and single brain metastasis by peak height and percentage of signal intensity recovery derived from dynamic susceptibility-weighted contrast-enhanced perfusion MR imaging. AJNR Am J Neuroradiol. 2007;28:1078–84.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Vallee A, Guillevin C, Wager M, Delwail V, Guillevin R, Vallee J-N. Added value of spectroscopy to perfusion MRI in the differential diagnostic performance of common malignant brain tumors. AJNR Am J Neuroradiol. 2018;39:1423–31.

    CAS  PubMed  PubMed Central  Google Scholar 

  20. Jung BC, Arevalo-Perez J, Lyo JK, Holodny AI, Karimi S, Young RJ, et al. Comparison of glioblastomas and brain metastases using dynamic contrast-enhanced perfusion MRI. J Neuroimaging. 2016;26:240–6.

    Article  PubMed  Google Scholar 

  21. Sunwoo L, Yun TJ, You SH, Yoo RE, Kang KM, Choi SH, et al. Differentiation of glioblastoma from brain metastasis: qualitative and quantitative analysis using arterial spin labeling MR imaging. PLoS One. 2016;11:e0166662.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  22. Barajas RF, Chang JS, Sneed PK, Segal MR, McDermott MW, Cha S. Distinguishing recurrent intra-axial metastatic tumor from radiation necrosis following gamma knife radiosurgery using dynamic susceptibility-weighted contrast-enhanced perfusion MR imaging. AJNR Am J Neuroradiol. 2009;30:367–72.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Jakubovic R, Sahgal A, Soliman H, Milwid R, Zhang L, Eilaghi A, et al. Magnetic resonance imaging-based tumour perfusion parameters are biomarkers predicting response after radiation to brain metastases. Clin Oncol (R Coll Radiol). 2014;26:704–12.

    Article  CAS  Google Scholar 

  24. Hatzoglou V, Yang TJ, Omura A, et al. A prospective trial of dynamic contrast-enhanced MRI perfusion and fluorine-18 FDG PET-CT in differentiating brain tumor progression from radiation injury after cranial irradiation. Neuro Oncol. 2016;18:873–80.

    Article  CAS  PubMed  Google Scholar 

  25. Lai G, Mahadevan A, Hackney D, Warnke PC, Nigim F, Kasper E, et al. Diagnostic accuracy of PET, SPECT, and arterial spin-labeling in differentiating tumor recurrence from necrosis in cerebral metastasis after stereotactic radiosurgery. AJNR Am J Neuroradiol. 2015;36:2250–5.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Almeida-Freitas DB, Pinho MC, Otaduy MC, et al. Assessment of irradiated brain metastases using dynamic contrast-enhanced magnetic resonance imaging. Neuroradiology. 2014;56:437–43.

    PubMed  Google Scholar 

  27. Weber MA, Thilmann C, Lichy MP, Gunther M, Delorme S, Zuna I, et al. Assessment of irradiated brain metastases by means of arterial spin-labeling and dynamic susceptibility-weighted contrast-enhanced perfusion MRI: initial results. Invest Radiol. 2004;39:277–87.

    Article  PubMed  Google Scholar 

  28. Balmaceda C, Critchell D, Mao X, et al. Multisection 1H magnetic resonance spectroscopic imaging assessment of glioma response to chemotherapy. J Neurooncol. 2006;76:185–91.

    Article  CAS  PubMed  Google Scholar 

  29. Vigneron D, Bollen A, McDermott M, et al. Three-dimensional magnetic resonance spectroscopic imaging of histologically confirmed brain tumors. Magn Reson Imaging. 2001;19:89–101.

    Article  CAS  PubMed  Google Scholar 

  30. Fan G, Sun B, Wu Z, Guo Q, Guo Y. In vivo single-voxel proton MR spectroscopy in the differentiation of high-grade gliomas and solitary metastases. Clin Radiol. 2004;59:77–85.

    Article  CAS  PubMed  Google Scholar 

  31. Moller-Hartmann W, Herminghaus S, Krings T, Marquardt G, Lanfermann H, Pilatus U, et al. Clinical application of proton magnetic resonance spectroscopy in the diagnosis of intracranial mass lesions. Neuroradiology. 2002;44:371–81.

    Article  CAS  PubMed  Google Scholar 

  32. Opstad KS, Murphy MM, Wilkins PR, Bell BA, Griffiths JR, Howe FA. Differentiation of metastases from high-grade gliomas using short echo time 1H spectroscopy. J Magn Reson Imaging. 2004;20:187–92.

    Article  PubMed  Google Scholar 

  33. Devos A, Lukas L, Suykens JA, Vanhamme L, Tate AR, Howe FA, et al. Classification of brain tumours using short echo time 1H MR spectra. J Magn Reson. 2004;170:164–75.

    Article  CAS  PubMed  Google Scholar 

  34. Chernov MF, Ono Y, Kubo O, Hori T. Comparison of 1H-MRS detected metabolic characteristics in single metastatic brain tumors of different origin. Brain Tumor Pathol. 2006;23:35–40.

    Article  CAS  PubMed  Google Scholar 

  35. Huang BY, Kwock L, Castillo M, Smith JK. Association of choline levels and tumor perfusion in brain metastases assessed with proton MR spectroscopy and dynamic susceptibility contrast-enhanced perfusion weighted MRI. Technol Cancer Res Treat. 2010;9:327–37.

    Article  CAS  PubMed  Google Scholar 

  36. Weybright P, Sundgren PC, Maly P, Hassan DG, Nan B, Rohrer S, et al. Differentiation between brain tumor recurrence and radiation injury using MR spectroscopy. Am J Roentgenol. 2005;185:1471–6.

    Article  Google Scholar 

  37. Elias AE, Carlos RC, Smith EA, Frechtling D, George B, Maly P, et al. MR spectroscopy using normalized and non-normalized metabolite ratios for differentiating recurrent brain tumor from radiation injury. Acad Radiol. 2011;18:1101–8.

    Article  PubMed  Google Scholar 

  38. Truong MT, St Clair EG, Donahue BR, Rush SC, Miller DC, Formenti SC, et al. Results of surgical resection for progression of brain metastases previously treated by gamma knife radiosurgery. Neurosurgery. 2006;59:86–97.

    Article  PubMed  Google Scholar 

  39. Chernov MF, Hayashi M, Izawa M, Usukura M, Yoshida S, Ono Y, et al. Multivoxel proton MRS for differentiation of radiation-induced necrosis and tumor recurrence after gamma knife radiosurgery for brain metastases. Brain Tumor Pathol. 2006;23:19–27.

    Article  CAS  PubMed  Google Scholar 

  40. Chernov M, Hayashi M, Izawa M, Ochiai T, Usukura M, Abe K, et al. Differentiation of the radiation-induced necrosis and tumor recurrence after gamma knife radiosurgery for brain metastases: importance of multi-voxel proton MRS. Minim Invasive Neurosurg. 2005;48:228–34.

    Article  CAS  PubMed  Google Scholar 

  41. Kimura T, Sako K, Tanaka K, Gotoh T, Yoshida H, Aburano T, et al. Evaluation of the response of metastatic brain tumors to stereotactic radiosurgery by proton magnetic resonance spectroscopy, 201TlCl single-photon emission computerized tomography, and gadolinium-enhanced magnetic resonance imaging. J Neurosurg. 2004;100:835–41.

    Article  PubMed  Google Scholar 

  42. Chuang MT, Liu YS, Tsai YS, Chen YC, Wang CK. Differentiating radiation-induced necrosis from recurrent brain tumor using MR perfusion and spectroscopy: a meta-analysis. PLoS One. 2016;11:e0141438.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  43. Rock JP, Hearshen D, Scarpace L, Croteau D, Gutierrez J, Fisher JL, et al. Correlations between magnetic resonance spectroscopy and image-guided histopathology, with special attention to radiation necrosis. Neurosurgery. 2002;51:912–9.

    PubMed  Google Scholar 

  44. Yamasaki F, Kurisu K, Satoh K, Arita K, Sugiyama K, Ohtaki M, et al. Apparent diffusion coefficient of human brain tumors at MR imaging. Radiology. 2005;235:985–91.

    Article  PubMed  Google Scholar 

  45. Kinuko K, Inoue Y, Nakayama K, Shakudo M, Morino M, Ohata K, et al. The role of diffusion-weighted imaging in patients with brain tumors. AJNR Am J Neuroradiol. 2001;22:1081–8.

    Google Scholar 

  46. Sugahara T, Korogi Y, Kochi M, Ikushima I, Shigematu Y, Hirai T, et al. Usefulness of diffusion-weighted MRI with echo-planar technique in the evaluation of cellularity in gliomas. J Magn Reson Imaging. 1999;9:53–60.

    Article  CAS  PubMed  Google Scholar 

  47. Wieduwilt MJ, Valles F, Issa S, Behler CM, Hwang J, McDermott M, et al. Immunochemotherapy with intensive consolidation for primary CNS lymphoma: a pilot study and prognostic assessment by diffusion-weighted MRI. Cancer Res Treat. 2012;18:1146–55.

    CAS  Google Scholar 

  48. Lee EJ, Lee SK, Agid R, Bae JM, Keller A, Terbrugge K. Preoperative grading of presumptive low-grade astrocytomas on MR imaging: diagnostic value of minimum apparent diffusion coefficient. AJNR Am J Neuroradiol. 2008;29:1872–7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Guo AC, Cummings TJ, Dash RC, Provenzale JM. Lymphomas and high-grade astrocytomas: comparison of water diffusibility and histologic characteristics. Radiology. 2002;224:177–83.

    Article  PubMed  Google Scholar 

  50. Lee KC, Moffat BA, Schott AF, Layman R, Ellingworth S, Juliar R, et al. Prospective early response imaging biomarker for neoadjuvant breast cancer chemotherapy. Cancer Res Treat. 2007;13:443–50.

    CAS  Google Scholar 

  51. Huang WY, Wen JB, Wu G, Yin B, Li JJ, Geng DY. Diffusion-weighted imaging of metastatic brain tumors: comparison with histologic type and tumor cellularity. AJNR Am J Neuroradiol. 2006;37:2010–8.

    Article  Google Scholar 

  52. Wang W, Steward CE, Desmond PM. Diffusion tensor imaging in glioblastoma multiforme and brain metastases: the role of p, q, L, and fractional anisotropy. AJNR Am J Neuroradiol. 2009;30:203–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Bauer AH, Erly W, Moser FG, Maya M, Nael K. Differentiation of solitary brain metastasis from glioblastoma multiforme: a predictive multiparametric approach using combined MR diffusion and perfusion. Neuroradiology. 2015;57:697–703.

    Article  PubMed  Google Scholar 

  54. Holly KS, Barker BJ, Murcia D, Bennett R, Kalakoti P, Ledbetter C. High-grade gliomas exhibit higher peritumoral fractional anisotropy and lower mean diffusivity than intracranial metastases. Front Surg. 2017;4:18.

    Article  PubMed  PubMed Central  Google Scholar 

  55. Wang S, Kim S, Chawla S, Wolf RL, Zhang WG, O’Rourke DM, et al. Differentiation between glioblastomas and solitary brain metastases using diffusion tensor imaging. Neuroimage. 2009;44:653–60.

    Article  PubMed  Google Scholar 

  56. Wang S, Kim SJ, Poptani H, Woo JH, Mohan S, Jin R, et al. Diagnostic utility of diffusion tensor imaging in differentiating glioblastomas from brain metastases. AJNR Am J Neuroradiol. 2014;35:928–34.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Bette S, Huber T, Wiestler B, Beockh-Behrens T, Gempt J, Ringel F, et al. Analysis of fractional anisotropy facilitates differentiation of glioblastoma and brain metastases in a clinical setting. Eur J Radiol. 2016;85:2181–7.

    Article  Google Scholar 

  58. Byrnes TJ, Barrick TR, Bell BA, Clark CA. Diffusion tensor imaging discriminates between glioblastoma and cerebral metastases in vivo. NMR Biomed. 2011;24:54–60.

    Article  PubMed  Google Scholar 

  59. Caravan I, Ciortea CA, Contis A, Lebovici A. Diagnostic value of apparent diffusion coefficient in differentiating between high-grade gliomas and brain metastases. Acta Radiol. 2018;59:599–605.

    Article  PubMed  Google Scholar 

  60. Lee EJ, TerBrugge K, Mikulis D, Choi DS, Bae JM, Lee SK. Diagnostic value of peritumoral minimum apparent diffusion coefficient for differentiation of glioblastoma multiforme from solitary metastatic lesions. AJR Am J Roentgenol. 2011;196:71–6.

    Article  PubMed  Google Scholar 

  61. Lemercier P, Paz Maya S, Patrie JT, Flors L, Leiva-Salinas C. Gradient of apparent diffusion coefficient values in peritumoral edema helps in differentiation of glioblastoma from solitary metastatic lesions. AJR Am J Roentgenol. 2014;203:163–9.

    Article  PubMed  Google Scholar 

  62. Lu S, Ahn D, Johnson G, Cha S. Peritumoral diffusion tensor imaging of high-grade gliomas and metastatic brain tumors. AJNR Am J Neuroradiol. 2003;24:937–41.

    PubMed  PubMed Central  Google Scholar 

  63. Lu S, Ahn D, Johnson G, Law M, Zagzag D, Grossman RI. Diffusion-tensor MR imaging of intracranial neoplasia and associated peritumoral edema: introduction of the tumor infiltration index. Radiology. 2004;232:221–8.

    Article  PubMed  Google Scholar 

  64. Pavlisa G, Rados M, Pavlisa G, Pavic L, Potocki K, Mayer D. The differences of water diffusion between brain tissue infiltrated by tumor and peritumoral vasogenic edema. Clin Imaging. 2009;33:96–101.

    Article  PubMed  Google Scholar 

  65. Kono K, Inoue Y, Nakayama K, Shakudo M, Mornio M, Ohata K, et al. The role of diffusion-weighted imaging in patients with brain tumors. AJNR Am J Neuroradiol. 2001;22:1081–8.

    CAS  PubMed  PubMed Central  Google Scholar 

  66. Tsougos I, Svolos P, Kousi E, Fountas K, Theodorou K, Fezoulidis I, et al. Differentiation of glioblastoma multiforme from metastatic brain tumor using proton magnetic resonance spectroscopy, diffusion and perfusion metrics at 3 T. Cancer Imaging. 2012;12:423–36.

    Article  PubMed  PubMed Central  Google Scholar 

  67. Suh CH, Kim HS, Jung SC, Kim SJ. Diffusion-weighted imaging and diffusion tensor imaging for differentiating high-grade glioma from solitary brain metastasis: a systematic review and meta-analysis. AJNR Am J Neuroradiol. 2018;39:1208–14.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  68. She D, Yang X, Xing Z, Cao D. Differentiating hemangioblastomas from brain metastases using diffusion-weighted imaging and dynamic susceptibility contrast-enhanced perfusion-weighted MR imaging. AJNR Am J Neuroradiol. 2016;37:1844–50.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  69. Hayashida Y, Hirai T, Morishita S, Kitajima M, Murakami R, Korogi Y, et al. Diffusion-weighted imaging of metastatic brain tumors: comparison with histologic type and tumor cellularity. AJNR Am J Neuroradiol. 2006;27:1419–25.

    CAS  PubMed  PubMed Central  Google Scholar 

  70. Jung WS, Park CH, Hong CK, Suh SH, Ahn SJ. Diffusion-weighted imaging of brain metastasis from lung cancer: correlation of MRI parameters with the histologic type and gene mutation status. AJNR Am J Neuroradiol. 2018;39:273–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  71. Ahn SJ, Park M, Bang S, Cho E, Ahn SG, Suh SH, et al. Apparent diffusion coefficient histogram in breast cancer brain metastases may predict their biological subtype and progression. Sci Rep. 2018;8:12767.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  72. Kim SH, Cha ES, Kim HS, Kang BJ, Choi JJ, Jung JH, et al. Diffusion-weighted imaging of breast cancer: correlation of the apparent diffusion coefficient value with prognostic factors. J Magn Reson Imaging. 2009;30:615–20.

    Article  PubMed  Google Scholar 

  73. Martincich L, Deantoni V, Bertotto I, Redana S, Kubatzki F, Sarotto I, et al. Correlations between diffusion-weighted imaging and breast cancer biomarkers. Eur Radiol. 2012;22:1519–28.

    Article  PubMed  Google Scholar 

  74. Tsao M, Xu W, Sahgal A. A meta-analysis evaluating stereotactic radiosurgery, whole-brain radiotherapy, or both for patients presenting with a limited number of brain metastases. Cancer. 2012;118:2486–93.

    Article  PubMed  Google Scholar 

  75. Yamamoto M, Serizawa T, Shuto T, Akabane A, Higuchi Y, Kawagishi J, et al. Stereotactic radiosurgery for patients with multiple brain metastases (JLGK0901): a multi-institutional prospective observational study. Lancet Oncol. 2014;15:387–95.

    Article  PubMed  Google Scholar 

  76. Farjam R, Tsien CI, Feng FY, Gomez-Hassan D, Hayman JA, Lawrence TS, et al. Investigation of the diffusion abnormality index as a new imaging biomarker for early assessment of brain tumor response to radiation therapy. Neuro Oncol. 2014;16:131–9.

    Article  CAS  PubMed  Google Scholar 

  77. Lee CC, Wintermark M, Xu Z, Yen CP, Schlesinger D, Sheehan JP. Application of diffusion-weighted magnetic resonance imaging to predict the intracranial metastatic tumor response to gamma knife radiosurgery. J Neurooncol. 2014;118:351–61.

    Article  PubMed  Google Scholar 

  78. Tomura N, Narita K, Izumi J, Suzuki A, Anbai A, Otani T, et al. Diffusion changes in a tumor and peritumoral tissue after stereotactic irradiation for brain tumors: possible prediction of treatment response. J Comput Assist Tomogr. 2006;30:496–500.

    Article  PubMed  Google Scholar 

  79. Huang CF, Chou HH, Tu HT, Yang MS, Lee JK, Lin LY. Diffusion magnetic resonance imaging as an evaluation of the response of brain metastases treated by stereotactic radiosurgery. Surg Neurol. 2008;69:62–8.

    Article  PubMed  Google Scholar 

  80. Knitter JR, Erly WK, Stea BD, Lemole GM, Germano IM, Doshi AH, et al. Interval change in diffusion and perfusion MRI parameters for the assessment of pseudoprogression in cerebral metastases treated with stereotactic radiation. AJR Am J Roentgenol. 2018;211:168–75.

    Article  PubMed  Google Scholar 

  81. Marom EM, McAdams HP, Erasmus JJ, Goodman PC, Culhane DK, Coleman RE, et al. Staging non-small cell lung cancer with whole-body PET. Radiology. 1999;212:803–9.

    Article  CAS  PubMed  Google Scholar 

  82. Ohno Y, Koyama H, Nogami M, Takenaka D, Yoshikawa T, Yoshimura M, et al. Whole-body MR imaging vs FDG-PET: comparison of accuracy of M-stage diagnosis for lung cancer patients. J Magn Reson Imaging. 2007;26:498–509.

    Article  PubMed  Google Scholar 

  83. Rohren EM, Provenzale JM, Barboriak DP, Coleman RE. Screening for cerebral metastases with FDG PET in patients undergoing whole-body staging of non-central nervous system malignancy. Radiology. 2003;226:181–7.

    Article  PubMed  Google Scholar 

  84. Kitajima K, Nakamoto Y, Okizuka H, Onishi Y, Senda M, Suganama N, et al. Accuracy of whole-body FDG-PET/CT for detecting brain metastases from non-central nervous system tumors. Ann Nucl Med. 2008;22:595–602.

    Article  PubMed  Google Scholar 

  85. Kruger S, Mottaghy FM, Buck AK, et al. Brain metastasis in lung cancer. Comparison of cerebral MRI and 18F-FDG-PET/CT for diagnosis in the initial staging. Nuklearmedizin. 2011;50:101–6.

    Article  CAS  PubMed  Google Scholar 

  86. Brink I, Schumacher T, Mix M, Ruhland S, Stoelben E, Digel W, et al. Impact of [18F]FDG-PET on the primary staging of small-cell lung cancer. Eur J Nucl Med Mol Imaging. 2004;31:1614–20.

    Article  CAS  PubMed  Google Scholar 

  87. Chung JK, Kim YK, Kim SK, Lee YJ, Paek S, Yeo JS, et al. Usefulness of 11C-methionine PET in the evaluation of brain lesions that are hypo- or isometabolic on 18F-FDG PET. Eur J Nucl Med Mol Imaging. 2002;29:176–82.

    Article  CAS  PubMed  Google Scholar 

  88. Momose T, Nariai T, Kawabe T, et al. Clinical benefit of 11C methionine PET imaging as a planning modality for radiosurgery of previously irradiated recurrent brain metastases. Clin Nucl Med. 2014;39:939–43.

    Article  PubMed  Google Scholar 

  89. Hutterer M, Nowosielski M, Putzer D, et al. [18F]-fluoro-ethyl-L-tyrosine PET: a valuable diagnostic tool in neuro-oncology, but not all that glitters is glioma. Neuro Oncol. 2013;15:341–51.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  90. Chao ST, Suh JH, Raja S, Lee S-Y, Barnett G. The sensitivity and specificity of FDG PET in distinguishing recurrent brain tumor from radionecrosis in patients treated with stereotactic radiosurgery. Int J Cancer. 2001;96:191–7.

    Article  CAS  PubMed  Google Scholar 

  91. Shankar LK, Hoffman JM, Bacharach S, et al. Consensus recommendations for the use of 18F-FDG PET as an indicator of therapeutic response in patients in National Cancer Institute Trials. J Nucl Med. 2006;47:1059–66.

    CAS  PubMed  Google Scholar 

  92. Horky LL, Hsiao EM, Weiss SE, Drappatz J, Gerbaudo VH. Dual phase FDG-PET imaging of brain metastases provides superior assessment of recurrence versus post-treatment necrosis. J Neurooncol. 2011;103:137–46.

    Article  PubMed  Google Scholar 

  93. Terakawa Y, Tsuyuguchi N, Iwai Y, et al. Diagnostic accuracy of 11C-methionine PET for differentiation of recurrent brain tumors from radiation necrosis after radiotherapy. J Nucl Med. 2008;49:694–9.

    Article  PubMed  Google Scholar 

  94. Tsuyuguchi N, Sunada I, Iwai Y, Yamanaka K, Tanaka K, Takami T, et al. Methionine positron emission tomography of recurrent metastatic brain tumor and radiation necrosis after stereotactic radiosurgery: is a differential diagnosis possible? J Neurosurg. 2003;98:1056–64.

    Article  PubMed  Google Scholar 

  95. Grosu AL, Astner ST, Riedel E, et al. An interindividual comparison of O-(2-[18F]fluoroethyl)-L-tyrosine (FET)- and L-[methyl-11C]methionine (MET)-PET in patients with brain gliomas and metastases. Int J Radiat Oncol Biol Phys. 2011;81:1049–58.

    Article  CAS  PubMed  Google Scholar 

  96. Cicone F, Minniti G, Romano A, et al. Accuracy of F-DOPA PET and perfusion-MRI for differentiating radionecrotic from progressive brain metastases after radiosurgery. Eur J Nucl Med Mol Imaging. 2015;42:103–11.

    Article  CAS  PubMed  Google Scholar 

  97. Lizarraga KJ, Allen-Auerbach M, Czernin J, DeSalles A, Yong WH, Phelps ME, et al. 18F-FDOPA PET for differentiating recurrent or progressive brain metastatic tumors from late or delayed radiation injury after radiation treatment. J Nucl Med. 2014;55:303–6.

    Article  CAS  Google Scholar 

  98. Galldiks N, Stoffels G, Filss CP, et al. Role of O-(2-(18)F-fluoroethyl)-L-tyrosine PET for differentiation of local recurrent brain metastases from radiation necrosis. J Nucl Med. 2012;53:1367–74.

    Article  CAS  PubMed  Google Scholar 

  99. Ceccon G, Lohmann P, Stoffels G, Judov N, Filss CP, Rapp M, et al. Dynamic O-(2-18F-fluoroethyl)-L-tyrosine positron emission tomography differentiates brain metastasis recurrence from radiation injury after radiotherapy. Neuro Oncol. 2017;19:281–8.

    CAS  PubMed  Google Scholar 

  100. Romagna A. Suspected recurrence of brain metastases after focused high dose radiotherapy: can [(18)F]FET-PET overcome diagnostic uncertainties? Radiat Oncol. 2016;11:139.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  101. Kebir S, Rauschenbach L, Galldiks N, Schlaak M, Hattingen E, Landsberg J, et al. Dynamic O-(2-[18F]fluoroethyl)-L-tyrosine PET imaging for the detection of checkpoint inhibitor-related pseudoprogression in melanoma brain metastases. Neuro Oncol. 2016;18:1462–4.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  102. Lohmann P, Kocher M, Ceccon G, et al. Combined FET PET/MRI radiomics differentiates radiation injury from recurrent brain metastasis. Neuroimage Clin. 2018;20:537–42.

    Article  PubMed  PubMed Central  Google Scholar 

  103. Zhang W, Ma XX, Ji YM, Kang XS, Li CF. Haemorrhage detection in brain metastases of lung cancer patients using magnetic resonance imaging. J Int Med Res. 2009;37(4):1139–44.

    Article  CAS  PubMed  Google Scholar 

  104. de Rochefort L, Brown R, Prince MR, Wang Y. Quantitative MR susceptibility mapping using piece-wise constant regularized inversion of the magnetic field. Magn Reson Med. 2008;60(4):1003–9.

    Article  PubMed  Google Scholar 

  105. Schweser F, Deistung A, Lehr BW, Reichenbach JR. Differentiation between diamagnetic and paramagnetic cerebral lesions based on magnetic susceptibility mapping. Med Phys. 2010;37(10):5165–78.

    Article  PubMed  Google Scholar 

  106. Hamilton R, Krauze M, Romkes M, Omolo B, Konstantinopoulos P, Reinhart T, et al. Pathologic and gene expression features of metastatic melanomas to the brain. Cancer. 2013;119(15):2737–46.

    Article  CAS  PubMed  Google Scholar 

  107. Gaviani P, Mullins ME, Braga TA, Hedley-Whyte ET, Halpern EF, Schaefer PS, et al. Improved detection of metastatic melanoma by T2∗-weighted imaging. Am J Neuroradiol. 2006;27(3):605–8.

    CAS  PubMed  PubMed Central  Google Scholar 

  108. Sehgal V, Delproposto Z, Haddar D, Haacke EM, Sloan AE, Zamorano LJ, et al. Susceptibility-weighted imaging to visualize blood products and improve tumor contrast in the study of brain masses. J Magn Reson Imaging. 2006;24(1):41–51.

    Article  PubMed  Google Scholar 

  109. Gramsch C, Goricks SL, Behrens F, Zimmer L, Schadendorf D, Krasny A, et al. Isolated cerebral susceptibility artefacts in patients with malignant melanoma: metastasis or not? Eur Radiol. 2013;23:2622–7.

    Article  PubMed  Google Scholar 

  110. Franceschi AM, Moschos SJ, Anders CK, Glaubiger S, Collichio FA, Lee CB, et al. Utility of susceptibility weighted imaging (SWI) in the detection of brain hemorrhagic metastases from breast cancer and melanoma. J Comput Assist Tomogr. 2016;40(5):803–5.

    Article  PubMed  PubMed Central  Google Scholar 

  111. Deike-Hofmann K, Thunemann D, Breckwoldt MO, Schwarz D, Radbruch A, Enk A, et al. Sensitivity of different MRI sequences in the early detection of melanoma brain metastases. PLoS One. 2018;13(3):e0193946.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  112. Roongpiboonsopit D, Kuijf HJ, Charidimou A, Xiong L, Vashkevich A, Martinez-Ramirez S, et al. Evolution of cerebral microbleeds after cranial irradiation in medulloblastoma patients. Neurology. 2017;88(8):789–96.

    Article  PubMed  PubMed Central  Google Scholar 

  113. Passos J, Nzwalo H, Valente M, Marques J, Azevedo A, Netto E, et al. Microbleeds and cavernomas after radiotherapy for paediatric primary brain tumors. J Neurol Sci. 2017;372:413–6.

    Article  PubMed  Google Scholar 

  114. Nandjgam RNK, Viswanathan A, Delgado P, Skehan ME, Smith EE, Rosand J, et al. MR imaging detection of cerebral microbleeds: effect of susceptibility-weighted imaging, section thickness, and field strength. AJNR Am J Neuroradiol. 2009;30(2):338–43.

    Article  Google Scholar 

  115. Tanjino T, Kanasaki Y, Tahara T, Michimoto K, Kodani K, Kakite S, et al. Radiation-induced microbleeds after cranial irradiation: evaluation by phase-sensitive magnetic resonance imaging with 3.0 tesla. Yonago Acta Med. 2013;56(1):7–12.

    Google Scholar 

  116. Cutsforth-Gregory JK, Lanzino G, Link MJ, Brown RD Jr, Flemming KD. Characterization of radiation-induced cavernous malformations and comparison with a nonradiation cavernous malformation cohort. J Neurosurg. 2015;122(5):1214–22.

    Article  PubMed  Google Scholar 

  117. Roddy E, Sear K, Felton E, Tamrazi B, Gauvain K, Torkildson J, et al. Presence of cerebral microbleeds is associated with worse executive function in pediatric brain tumor survivors. Neuro Oncol. 2016;18(11):1548–58.

    PubMed  PubMed Central  Google Scholar 

  118. Ghia AJ, Tward JD, Anker CJ, Boucher KM, Jensen RL, Shrieve DC. Radiosurgery for melanoma brain metastases: the impact of hemorrhage on local control. J Radiosurg SBRT. 2014;3(1):43–50.

    PubMed  PubMed Central  Google Scholar 

  119. Redmond AJ, Diluna ML, Herbert R, Moliterno JA, Desai R, Knisely JP, et al. Gamma knife surgery for the treatment of melanoma metastases: the effect of intratumoral hemorrhage on survival. J Neurosurg. 2008;109:99–105.

    Article  PubMed  Google Scholar 

  120. Kalfas F, Ronchini N, Godowicz TT, Cavazzani P, Severi P. Peritumoral and intratumoral hemorrhage after stereotactic radiosurgery for renal cell carcinoma metastasis to the brain. J Radiosurg SBRT. 2011;1(2):163–8.

    PubMed  PubMed Central  Google Scholar 

  121. Sykova E, Jendelova P. In vivo tracking of stem cells in brain and spinal cord injury. Prog Brain Res. 2007;161:367–83.

    Article  CAS  PubMed  Google Scholar 

  122. Zhang X, de Chickera SN, Willert C, Economopoulos V, Noad J, Rohani R, et al. Cellular magnetic resonance imaging of monocyte-derived dendritic cell migration from healthy donors and cancer patients as assessed in a scid mouse model. Cytotherapy. 2011;13(10):1234–48.

    Article  CAS  PubMed  Google Scholar 

  123. de Chickera S, Willert C, Mallet C, Foley R, Foster P, Dekaban GA. Cellular MRI as a suitable, sensitive non-invasive modality for correlating in vivo migratory efficiencies of different dendritic cell populations with subsequent immunological outcomes. Int Immunol. 2012;24(1):29–41.

    Article  CAS  PubMed  Google Scholar 

  124. Dekaban GA, Snir J, Shrum B, de Chickera S, Willert C, Merrill M, et al. Semiquantitation of mouse dendritic cell migration in vivo using cellular MRI. J Immunother. 2009;32(3):240–51.

    Article  PubMed  Google Scholar 

  125. Shapiro EM, Medford-Davis LN, Fahmy TM, Dunbar CE, Koretsky AP. Antibody-mediated cell labeling of peripheral T cells with micron-sized iron oxide particles (MPIOs) allows single cell detection by MRI. Contrast Media Mol Imaging. 2007;2(3):147–53.

    Article  CAS  PubMed  Google Scholar 

  126. Foster PJ, Dunn EA, Karl KE, Snir JA, Nycz CM, Harvey AJ, et al. Cellular magnetic resonance imaging: in vivo imaging of melanoma cells in lymph nodes of mice. Neoplasia. 2008;10(3):207–16.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  127. Perera M, Ribot EJ, Percy DB, McFadden C, Simedrea C, Palmieri D, et al. In vivo magnetic resonance imaging for investigating the development and distribution of experimental brain metastases due to breast cancer. Transl Oncol. 2012;5(3):217–25.

    Article  PubMed  PubMed Central  Google Scholar 

  128. Ribot EJ, Foster PJ. In vivo MRI discrimination between live and lysed iron-labelled cells using balanced steady state free precession. Eur Radiol. 2012;22(9):2027–34.

    Article  CAS  PubMed  Google Scholar 

  129. Canella B, Raine CS. The adhesion molecule and cytokine profile of multiple sclerosis lesions. Ann Neurol. 1995;37:424–35.

    Article  Google Scholar 

  130. Polman CH, O’Connor PW, Havrdova E, Hutchinson M, Kappos L, Miller DH, et al. A randomized, placebo-controlled trial of natalizumab for relapsing multiple sclerosis. N Engl J Med. 2006;354:889–910.

    Article  Google Scholar 

  131. Piraino PS, Yednock TA, Freedman SB, Pleiss MA, Vandevert C, Thorsett ED, et al. Prolonged reversal of chronic experimental allergic encephalomyelitis using a small molecule inhibitor of alpha4 integrin. J Neuroimmunol. 2002;131:147–59.

    Article  CAS  PubMed  Google Scholar 

  132. Carbonell WS, Ansorge O, Sibson N, Muschel R. The vascular basement membrane as “soil” in brain metastasis. PLoS One. 2009;4:e5857.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  133. Kusters B, Leenders WP, Wesseling P, Smits D, Verrijp K, Ruiter DJ, et al. Vascular endothelial growth factor-A(165) induces progression of melanoma brain metastases without induction of sprouting angiogenesis. Cancer Res. 2002;62:341–5.

    CAS  PubMed  Google Scholar 

  134. Laubli H, Borsig L. Selecting as mediators of lung metastasis. Cancer Microenviron. 2010;3:97–105.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  135. Ludwig RJ, Boehme B, Podda M, Henschler R, Jager E, Tandi C, et al. Endothelial P-selectin as a target of heparin action in experimental melanoma lung metastasis. Cancer Res. 2004;64:2743–50.

    Article  CAS  PubMed  Google Scholar 

  136. Khatib AM, Kontogiannea M, Fallavollita L, Jamison B, Meterissian S, Brodt P. Rapid induction of cytokine and E-selectin expression in the liver in response to metastatic tumor cells. Cancer Res. 1999;59:1356–61.

    CAS  PubMed  Google Scholar 

  137. Vidal-Vanaclocha F, Fantuzzi G, Mendoza L, Fuentes AM, Anasagasti MJ, Martin J, et al. IL-18 regulates IL-1beta-dependent hepatic melanoma metastasis via vascular cell adhesion molecule-1. Proc Natl Acad Sci U S A. 2000;97:734–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  138. McAteer MA, Sibson NR, von Zur Muhlen C, Schneider JE, Lowe AS, Warrick N, et al. In vivo magnetic resonance imaging of acute brain inflammation using microparticles of iron oxide. Nat Med. 2007;13:1253–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  139. Serres S, Soto MS, Hamilton A, McAteer MA, Carbonell WS, Robson MD, et al. Molecular MRI enables early and sensitive detection of brain metastases. Proc Natl Acad Sci U S A. 2012;109(17):6674–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  140. Zach L, Guez D, Last D, Daniels D, Grober Y, Nissim O, et al. Delayed contrast extravasation MRI for depicting tumor and non-tumoral tissues in primary and metastatic brain tumors. PLoS One. 2012;7:e52008.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  141. Jain RK. Molecular regulation of vessel maturation. Nat Med. 2003;9(6):685–93.

    Article  CAS  PubMed  Google Scholar 

  142. Aronen HJ, Gazit IE, Louis DN, Buchbinder BR, Pardo FS, Weisskoff RM, et al. Cerebral blood volume maps of gliomas: comparison with tumor grade and histologic findings. Radiology. 1994;191:41–51.

    Article  CAS  PubMed  Google Scholar 

  143. Cha S, Johnson G, Wadghiri YZ, Jin O, Babb J, Zagzag D, et al. Dynamic, contrast-enhanced perfusion MRI in mouse gliomas correlation with histopathology. Magn Reson Med. 2003;49:848–55.

    Article  PubMed  Google Scholar 

  144. Hompland T, Gulliksrud K, Ellingsen C, Rofstad EK. Assessment of the interstitial fluid pressure of tumors by dynamic contrast-enhanced magnetic resonance imaging with contrast agents of different molecular weights. Acta Oncol. 2013;52:627–35.

    Article  CAS  PubMed  Google Scholar 

  145. Wong CS, Van der Kogel AJ. Mechanisms of radiation injury to the central nervous system implications for neuroprotection. Mol Interv. 2004;4:273–84.

    Article  CAS  PubMed  Google Scholar 

  146. Zach L, Guez D, Last D, Daniels D, Grober Y, Nissim O, et al. Delayed contrast extravasation MRI: a new paradigm in neuro-oncology. Neuro Oncol. 2015;17:457–65.

    Article  CAS  PubMed  Google Scholar 

  147. Wang B, Zhang Y, Zhao B, Zhao P, Ge M, Gao M, et al. Postcontrast T1 mapping for differential diagnosis of recurrence and radionecrosis after gamma knife radiosurgery for brain metastasis. AJNR Am J Neuroradiol. 2018;39(6):1025–31.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  148. Chen W, Cloughesy T, Kamdar N, Satyamurthy N, Bergsneider M, Liau L, et al. Imaging proliferation in brain tumors with 18F-FLT PET: comparison with 18F-FDG. J Nucl Med. 2005;46(6):945–52.

    CAS  PubMed  Google Scholar 

  149. Chen W, Delaloye S, Silverman DH, Geist C, Czernin J, Sayre J, et al. Predicting treatment response of malignant gliomas to bevacizumab and irinotecan by imaging proliferation with [18F] fluorothymidine positron emission tomography: a pilot study. J Clin Oncol. 2007;25(30):4714–21.

    Article  CAS  PubMed  Google Scholar 

  150. Shields AF, Grierson JR, Dohmen BM, Machulla HJ, Stayanoff JC, Lawhorn-Crews JM, et al. Imaging proliferation in vivo with [F-18]FLT and positron emission tomography. Nat Med. 1998;4(11):1334–6.

    Article  CAS  PubMed  Google Scholar 

  151. Ribas A, Benz MR, Allen-Auerbach MS, Radu C, Chmielowski B, Seja E, et al. Imaging of CTLA4 blockade-induced cell replication with (18)F-FLT PET in patients with advanced melanoma treated with tremelimumab. J Nucl Med. 2010;51(3):340–6.

    Article  CAS  PubMed  Google Scholar 

  152. Schwarzenberg J, Czernin J, Cloughesy TF, Ellingson BM, Pope WB, Geist C, et al. 3′-Deoxy-3′-18F-fluorothymidine PET and MRI for early survival predictions in patients with recurrent malignant glioma treated with bevacizumab. J Nucl Med. 2012;53(1):29–36.

    Article  CAS  PubMed  Google Scholar 

  153. Wardak M, Schiepers C, Dahlbom M, Cloughesy T, Chen W, Satyamurthy N, et al. Discriminant analysis of (1)(8)F-fluorothymidine kinetic parameters to predict survival in patients with recurrent high-grade glioma. Clin Cancer Res. 2011;17(20):6553–62.

    Article  CAS  PubMed  Google Scholar 

  154. Schiepers C, Dahlbom M, Chen W, Cloughesy T, Czernin J, Phelps ME, et al. Kinetics of 3′-deoxy-3′-18F-fluorothymidine during treatment monitoring of recurrent high-grade glioma. J Nucl Med. 2010;51(5):720–7.

    Article  PubMed  Google Scholar 

  155. Nguyen NC, Yee MK, Tuchay AM, Kirkwood JM, Tawbi H, Mountz JM. Targeted therapy and immunotherapy response assessment with F-18 fluorothymidine positron-emission tomography/magnetic resonance imaging in melanoma brain metastasis: a pilot study. Front Oncol. 2018;8:18.

    Article  PubMed  PubMed Central  Google Scholar 

  156. O’Sullivan CC, Lindenberg M, Bryla C, Patronas N, Peer CJ, Amiri-Kordestani L, et al. ANG 1005 for breast cancer brain metastases: correlation between 18F-FLT-PET after first cycle and MRI in response assessment. Breast Cancer Res Treat. 2016;160(1):51–9.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  157. Cohen A, Shirvan A, Levin G, Grimberg H, Reshef A, Ziv I. From the Gla domain to a novel small-molecule detector of apoptosis. Cell Res. 2009;19(5):625–37.

    Article  CAS  PubMed  Google Scholar 

  158. Allen AM, Ben-Ami M, Reshef A, Steinmetz A, Kundel Y, Inbar E, et al. Assessment of response of brain metastases to radiotherapy by PET imaging of apoptosis with 18F-ML-10. Eur J Nucl Med Mol Imaging. 2012;39:1400–8.

    Article  PubMed  Google Scholar 

  159. Duarte PS, Marin JFG, De Carvalho JWA, Sapienza MR, Buchpiguel CA. Brain metastasis of medullary thyroid carcinoma without macroscopic calcification detected first on 68Ga-DOTATATE and then on 18F-Fluoride PET/CT. Clin Nucl Med. 2018;43(8):623–4.

    Article  PubMed  Google Scholar 

  160. Carreras C, Kulkarni HR, Baum RP. Rare metastases detected by 68Ga-somatostatin receptor PET/CT in patients with neuroendocrine tumors. Recent Results Cancer Res. 2013;194:379–84.

    Article  CAS  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Radiology, Division of Neuroradiology, NewYork-Presbyterian/Weill Cornell Medicine, New York, NY, USA

    Eaton Lin & Gloria C. Chiang

Authors
  1. Eaton Lin
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Gloria C. Chiang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Gloria C. Chiang .

Editor information

Editors and Affiliations

  1. Department of Neurological Surgery, NewYork-Presbyterian Hospital/Weill Cornell Medicine, Director - Brain Metastases Program, New York, NY, USA

    Rohan Ramakrishna

  2. Department of Neurology, NewYork-Presbyterian Hospital/Weill Cornell Medicine, New York, NY, USA

    Rajiv S. Magge

  3. Department of Neurological Surgery, NewYork-Presbyterian Hospital/Weill Cornell Medicine, New York, NY, USA

    Ali A. Baaj

  4. Department of Radiation Oncology, NewYork-Presbyterian Hospital/Weill Cornell Medicine, New York, NY, USA

    Jonathan P.S. Knisely

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Lin, E., Chiang, G.C. (2020). The Role of Advanced Imaging in the Management of Brain Metastases. In: Ramakrishna, R., Magge, R., Baaj, A., Knisely, J. (eds) Central Nervous System Metastases. Springer, Cham. https://doi.org/10.1007/978-3-030-42958-4_7

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-42958-4_7

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-42957-7

  • Online ISBN: 978-3-030-42958-4

  • eBook Packages: MedicineMedicine (R0)

Publish with us

Policies and ethics

Search

Navigation