Journal of Korean Neurosurgical Society

The Korean Neurosurgical Society (대한신경외과학회)
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The Use of MR Perfusion Imaging in the Evaluation of Tumor Progression in Gliomas

  • Snelling, Brian (Department of Neurological Surgery, University of Miami Miller School of Medicine) ;
  • Shah, Ashish H. (Department of Neurological Surgery, University of Miami Miller School of Medicine) ;
  • Buttrick, Simon (Department of Neurological Surgery, University of Miami Miller School of Medicine) ;
  • Benveniste, Ronald (Department of Neurological Surgery, University of Miami Miller School of Medicine)
  • Received : 2016.02.01
  • Accepted : 2016.08.30
  • Published : 2017.01.01
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Abstract

Objective : Diagnosing tumor progression and pseudoprogression remains challenging for many clinicians. Accurate recognition of these findings remains paramount given necessity of prompt treatment. However, no consensus has been reached on the optimal technique to discriminate tumor progression. We sought to investigate the role of magnetic resonance perfusion (MRP) to evaluate tumor progression in glioma patients. Methods : An institutional retrospective review of glioma patients undergoing MRP with concurrent clinical follow up visit was performed. MRP was evaluated in its ability to predict tumor progression, defined clinically or radiographically, at concurrent clinical visit and at follow up visit. The data was then analyzed based on glioma grade and subtype. Resusts : A total of 337 scans and associated clinical visits were reviewed from 64 patients. Sensitivity, specificity, positive and negative predictive value were reported for each tumor subtype and grade. The sensitivity and specificity for high-grade glioma were 60.8% and 87.8% respectively, compared to low-grade glioma which were 85.7% and 89.0% respectively. The value of MRP to assess future tumor progression within 90 days was 46.9% (sensitivity) and 85.0% (specificity). Conclusion : Based on our retrospective review, we concluded that adjunct imaging modalities such as MRP are necessary to help diagnose clinical disease progression. However, there is no clear role for stand-alone surveillance MRP imaging in glioma patients especially to predict future tumor progression. It is best used as an adjunctive measure in patients in whom progression is suspected either clinically or radiographically.

Keywords

References

  1. Aiken AH, Chang SM, Larson D, Butowski N, Cha S : Longitudinal magnetic resonance imaging features of glioblastoma multiforme treated with radiotherapy with or without brachytherapy. Int J Radiat Oncol Biol Phys 72 : 1340-1346, 2008 https://doi.org/10.1016/j.ijrobp.2008.02.078
  2. Artzi M, Bokstein F, Blumenthal DT, Aizenstein O, Liberman G, Corn BW, et al. : Differentiation between vasogenic-edema versus tumor-infiltrative area in patients with glioblastoma during bevacizumab therapy: a longitudinal MRI study. Eur J Radiol 83 : 1250-1256, 2014 https://doi.org/10.1016/j.ejrad.2014.03.026
  3. Arvinda HR, Kesavadas C, Sarma PS, Thomas B, Radhakrishnan VV, Gupta AK, et al. : Glioma grading: sensitivity, specificity, positive and negative predictive values of diffusion and perfusion imaging. J Neurooncol 94 : 87-96, 2009 https://doi.org/10.1007/s11060-009-9807-6
  4. Barajas RF Jr, Chang JS, Segal MR, Parsa AT, McDermott MW, Berger MS, et al. : Differentiation of recurrent glioblastoma multiforme from radiation necrosis after external beam radiation therapy with dynamic susceptibility-weighted contrast-enhanced perfusion MR imaging. Radiology 253 : 486-496, 2009 https://doi.org/10.1148/radiol.2532090007
  5. Bisdas S, Naegele T, Ritz R, Dimostheni A, Pfannenberg C, Reimold M, et al. : Distinguishing recurrent high-grade gliomas from radiation injury: a pilot study using dynamic contrast-enhanced MR imaging. Acad Radiol 18 : 575-583, 2011 https://doi.org/10.1016/j.acra.2011.01.018
  6. Bobek-Billewicz B, Stasik-Pres G, Hebda A, Majchrzak K, Kaspera W, Jurkowski M : Anaplastic transformation of low-grade gliomas (WHO II) on magnetic resonance imaging. Folia Neuropathol 52 : 128-140, 2014
  7. Bobek-Billewicz B, Stasik-Pres G, Majchrzak H, Zarudzki L : Differentiation between brain tumor recurrence and radiation injury using perfusion, diffusion-weighted imaging and MR spectroscopy. Folia Neuropathol 48 : 81-92, 2010
  8. Chung WJ, Kim HS, Kim N, Choi CG, Kim SJ : Recurrent glioblastoma: optimum area under the curve method derived from dynamic contrastenhanced T1-weighted perfusion MR imaging. Radiology 269 : 561- 568, 2013 https://doi.org/10.1148/radiol.13130016
  9. Danchaivijitr N, Waldman AD, Tozer DJ, Benton CE, Brasil Caseiras G, Tofts PS, et al. : Low-grade gliomas: do changes in rCBV measurements at longitudinal perfusion-weighted MR imaging predict malignant transformation? Radiology 247 : 170-178, 2008 https://doi.org/10.1148/radiol.2471062089
  10. Di Costanzo A, Scarabino T, Trojsi F, Popolizio T, Bonavita S, de Cristofaro M, et al. : Recurrent glioblastoma multiforme versus radiation injury: a multiparametric 3-T MR approach. Radiol Med 119 : 616-624, 2014 https://doi.org/10.1007/s11547-013-0371-y
  11. Fatterpekar GM, Galheigo D, Narayana A, Johnson G, Knopp E : Treatment-related change versus tumor recurrence in high-grade gliomas: a diagnostic conundrum--use of dynamic susceptibility contrast-enhanced (DSC) perfusion MRI. AJR Am J Roentgenol 198 : 19-26, 2012 https://doi.org/10.2214/AJR.11.7417
  12. Gomez-Rio M, Rodriguez-Fernandez A, Ramos-Font C, Lopez-Ramirez E, Llamas-Elvira JM : Diagnostic accuracy of 201Thallium-SPECT and 18FFDG-PET in the clinical assessment of glioma recurrence. Eur J Nucl Med Mol Imaging 35 : 966-975, 2008 https://doi.org/10.1007/s00259-007-0661-5
  13. Guillevin R, Herpe G, Verdier M, Guillevin C : Low-grade gliomas: The challenges of imaging. Diagn Interv Imaging 95 : 957-963, 2014 https://doi.org/10.1016/j.diii.2014.07.005
  14. Hlaihel C, Guilloton L, Guyotat J, Streichenberger N, Honnorat J, Cotton F : Predictive value of multimodality MRI using conventional, perfusion, and spectroscopy MR in anaplastic transformation of low-grade oligodendrogliomas. J Neurooncol 97 : 73-80, 2010 https://doi.org/10.1007/s11060-009-9991-4
  15. Kahn D, Follett KA, Bushnell DL, Nathan MA, Piper JG, Madsen M, et al. : Diagnosis of recurrent brain tumor: value of 201Tl SPECT vs 18F-fluorodeoxyglucose PET. AJR Am J Roentgenol 163 : 1459-1465, 1994 https://doi.org/10.2214/ajr.163.6.7992747
  16. Kim HS, Goh MJ, Kim N, Choi CG, Kim SJ, Kim JH : Which combination of MR imaging modalities is best for predicting recurrent glioblastoma? Study of diagnostic accuracy and reproducibility. Radiology 273 : 831-843, 2014 https://doi.org/10.1148/radiol.14132868
  17. Kim YH, Oh SW, Lim YJ, Park CK, Lee SH, Kang KW, et al. : Differentiating radiation necrosis from tumor recurrence in high-grade gliomas: assessing the efficacy of 18F-FDG PET, 11C-methionine PET and perfusion MRI. Clin Neurol Neurosurg 112 : 758-765, 2010 https://doi.org/10.1016/j.clineuro.2010.06.005
  18. Law M, Young RJ, Babb JS, Peccerelli N, Chheang S, Gruber ML, et al. : Gliomas: predicting time to progression or survival with cerebral blood volume measurements at dynamic susceptibility-weighted contrastenhanced perfusion MR imaging. Radiology 247 : 490-498, 2008 https://doi.org/10.1148/radiol.2472070898
  19. Macdonald DR, Cascino TL, Schold SC Jr, Cairncross JG : Response criteria for phase II studies of supratentorial malignant glioma. J Clin Oncol 8 : 1277-1280, 1990 https://doi.org/10.1200/JCO.1990.8.7.1277
  20. Narang J, Jain R, Arbab AS, Mikkelsen T, Scarpace L, Rosenblum ML, et al. : Differentiating treatment-induced necrosis from recurrent/progressive brain tumor using nonmodel-based semiquantitative indices derived from dynamic contrast-enhanced T1-weighted MR perfusion. Neuro Oncol 13 : 1037-1046, 2011 https://doi.org/10.1093/neuonc/nor075
  21. Prat R, Galeano I, Lucas A, Martinez JC, Martin M, Amador R, et al. : Relative value of magnetic resonance spectroscopy, magnetic resonance perfusion, and 2-(18F) fluoro-2-deoxy-D-glucose positron emission tomography for detection of recurrence or grade increase in gliomas. J Clin Neurosci 17 : 50-53, 2010 https://doi.org/10.1016/j.jocn.2009.02.035
  22. Raimbault A, Cazals X, Lauvin MA, Destrieux C, Chapet S, Cottier JP : Radionecrosis of malignant glioma and cerebral metastasis: A diagnostic challenge in MRI. Diagn Interv Imaging 95 : 985-1000, 2014 https://doi.org/10.1016/j.diii.2014.06.013
  23. Seeger A, Braun C, Skardelly M, Paulsen F, Schittenhelm J, Ernemann U, et al. : Comparison of three different MR perfusion techniques and MR spectroscopy for multiparametric assessment in distinguishing recurrent high-grade gliomas from stable disease. Acad Radiol 20 : 1557-1565, 2013 https://doi.org/10.1016/j.acra.2013.09.003
  24. Shah AH, Snelling B, Bregy A, Patel PR, Tememe D, Bhatia R, et al. : Discriminating radiation necrosis from tumor progression in gliomas: a systematic review what is the best imaging modality? J Neurooncol 112 : 141-152, 2013 https://doi.org/10.1007/s11060-013-1059-9
  25. Wen PY, Macdonald DR, Reardon DA, Cloughesy TF, Sorensen AG, Galanis E, et al. : Updated response assessment criteria for high-grade gliomas: response assessment in neuro-oncology working group. J Clin Oncol 28 : 1963-1972, 2010 https://doi.org/10.1200/JCO.2009.26.3541

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