medigraphic.com

2016, Number 3

<< Back Next >>

Anales de Radiología México 2016; 15 (3)

Apparent diffusion coefficient in magnetic resonance of atypical and malignant meningiomas

Cristancho-Rojas CN, Casares-Cruz K, Reina-Moreno DP, Rembao-Bojórquez D

Language: Spanish
References: 36
Page: 194-204
PDF size: 469.43 Kb.


ABSTRACT

Meningiomas are the most common extra-axial neoplasms in the central nervous system. Their histological classification in 3 grades according to the World Health Organization: benign (I), atypical (II), and malignant (III) wich predicts the biological behavior and progressionfree survival. The image study of choice is magnetic resonance.
Objetive: measure and determine the mean values of the apparent diffusion coefficient in atypical and malignant meningiomas, and evaluate its usefulness in preoperative distinction of those subtypes.
Material and Method: we conducted a retrospective, observational study at Instituto Nacional de Neurología y Neurocirugía Manuel Velasco Suarez de Mexico (INNN), from January 2011 to July 2015, including patients with diagnosis of grade II or III meningiomas in the pathology archive who also had magnetic resonance and diffusion studies in the picture archiving and communication system (PACS).
Results: we identified 84 patients, 67 with histological diagnosis of atypical meningiomas and 17 with malignant meningiomas. The mean value of the apparent diffusion coefficient measured in patients with grade II meningiomas was 0.820 × 10-3 mm2/s (± 0.150) and in those with grade III meningiomas it was 0.770 × 10-3 mm2/s (± 0.125).
Conclusions: there were no statistically significant differences between apparent diffusion coefficient values for atypical and malignant subtypes (p = 0.336), although comparing them with the literature available, our mean values are similar to those reported by other authors and lower than those found in those obtained from benign meningiomas.


REFERENCES

  1. Louis DN, Ohgaki H, Wiestler OD, Cavenee WK. WHO Classification of Tumors of the Central Nervous System. Albany, NY, World Health Organization Publications Center 2007.

  2. Wiemels J, Wrensch M, Claus E B. Epidemiology and etiology of meningioma. J Neurooncol 2010;99:307–314.

  3. Vernooij MW, Ikram MA, Tanghe HL, Vincent AJ, Hofman A, Krestin GP, Niessen WJ, et al. Incidental findings on brain MRI in the general population. N Engl J Med 2007;357:1821–1828.

  4. Krampla W, Newrkla S, Pfisterer W, Jungwirth S, Fischer P, Leitha T, et al. Frequency and risk factors for meningioma in clinically healthy 75-year-old patients: results of the Transdanube Ageing Study (VITA). J Cancer 2004;100:1208–1212.

  5. Takahashi JA, Ueba T, Hashimoto N, Nakashima Y, Katsuki N. The combination of mitotic and Ki-67 indices as a useful method for predicting short-term recurrence of meningiomas. Surgical Neurology 2004;61(2):149-155.

  6. Vranic A, Popovic M, Cör A, Prestor B, Pizem J. Mitotic count, brain invasion, and location are independent predictors of recurrence-free survival in primary atypical and malignant meningiomas: a study of 86 patients. J Neurosurgery 2010;67(4):1124-32.

  7. Riemenschneider MJ, Perry A, Reifenberger G. Histological classification and molecular genetics of meningiomas. The Lancet Neurology 2006;5(12):1045–54.

  8. Sadetzki S, Modan B, Chetrit A, Freedman L. An iatrogenic epidemic of benign meningioma. Am J Epidemiol 2000;151:266–272.

  9. Tsujita N, Kai N, Fujita Y, Hiai Y, Hirai T, Kitajima M, et al. Interimager variability in ADC measurement of the human brain. R. Magn Reson Med Sci 2014;13(2):81-7.

  10. John H. Rees, Meningeal Neoplasms, Chapter 30. Thomas P. Naidich, Mauricio Castillo, Soonmee Cha, James G. Smirniotopoulos; Imaging of the Brain. 2013 by Saunders, an imprint of Elsevier Inc.

  11. Lee Y, Liu J, Patel S, Cloughesy T, Lai A, Farooqi H, et al. Genomic landscape of meningiomas. Brain Pathol 2010;20:751–762.

  12. Roser F, Samii M, Ostertag H, Bellinzona M. The Ki-67 proliferation antigen in meningiomas. Experience in 600 cases. Acta Neurochirurgica 2004;146(1):37-44.

  13. Sughrue ME, Sanai N, Shangari G, Parsa AT, Berger MS, McDermott MW. Outcome and survival following primary and repeat surgery for World Health Organization grade III meningiomas. J Neurosurg 2010;113:202-209.

  14. Sughrue ME, Kane AJ, Shangari G, Rutkowski MJ, McDermott MW, Berger MS, et al. The relevance of Simpson grade i and ii resection in modern neurosurgical treatment of World Health Organization grade i meningiomas. J Neurosurg 2010;113:1020-1035.

  15. Maier SE, Sun Y and Mulkern RV. Diffusion imaging of brain tumors. NMR Biomed 2010;23:849–864.

  16. Hagmann P, Jonasson L, Maeder P, Thiran JP, Wedeen VJ, and Meuli R. Understanding diffusion MR imaging techniques: from scalar diffusion-weighted imaging to diffusion tensor imaging and beyond. Radiographics 2006;26(1):S205–S223.

  17. Ahualli J. Aspectos generales de las secuencias de difusión de imagen en resonancia magnética. Revista Argentina de Radiología 2007;74(3):227-237.

  18. Yamasaki F, Sugiyama K and Kurisu K. Brain Tumors: Apparent Diffusion Coefficient at Magnetic Resonance Imaging. Chapter 22, Volume 8 of the series Methods of Cancer Diagnosis, Therapy and Prognosis pp. 279-296.

  19. Hsu EW, Aiken NR, and Blackband SJ. Nuclear magnetic resonance microscopy of single neurons under hypotonic perturbation. Am. J. Physiol.1996;271:C1895–C1900.

  20. Akio O, Hayakawaa K, Miyatib T, Maeda F. Imaging parameter effects in apparent diffusion coefficient determination of magnetic resonance imaging. European Journal of Radiology 2009;(77)1:185-188.

  21. Sasaki M, Yamada K, Watanabe Y, Matsui M, Ida M, Fujiwara S, et al. Variability in absolute apparent diffusion coefficient values across different platforms may be substantial: a multivendor, multi-institutional comparison study. Radiology 2008;249(2):624–30.

  22. Liu G, Chen ZY, Ma L, Lou X, Li SJ, Wang YL. Intracranial hemangiopericytoma: MR imaging findings and diagnostic usefulness of minimum ADC values. J Magn Reson Imaging 2013;38(5):1146–1151.

  23. Pavlisa G, Rados M, Pazanin L, Padovan RS, Ozretic D. Characteristics of typical and atypical meningiomas on ADC maps with respect to schwannomas. Clin Imaging 2008;32(1):22–27.

  24. 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;235:985–991.

  25. Nagar VA, Ye JR, Ng WH, Chan YH, Hui F, Lee CK, Lim CC. Diffusion-weighted MR imaging: diagnosing atypical or malignant meningiomas and detecting tumor dedifferentiation. AJNR 2008;29:1147–1152.

  26. Santelli L, Ramondo G, Puppa DA, et al. Diffusion- weighted imaging does not predict histological grading in meningiomas. Acta Neurochir (Wien) 2010;152(8):1315–1319.

  27. Sanverdi SE, Ozgen B, Oguz KK, Mut M, Dolgun A, Soylemezoglu F, et al. Is diffusion-weighted imaging useful in grading and differentiating histopathological subtypes of meningiomas?. Eur J Radiol 2012;81(9):2389–2395.

  28. Kono K, Inoue Y, Nakayama K, Shakudo M, Morino, M, Ohata K, et al. The role of diffusion weighted imaging in patients with brain tumors. Am. J. Neuroradiol 2001;22:1081–1088.

  29. Filippi CG, Edgar MA, Ulug AM, Prowda JC, Heier LA, and Zimmerman RD. Appearance of meningiomas on diffusion weighted images: correlating diffusion constants with histopathologic findings. Am. J. Neuroradiol 2001;22:65–72.

  30. Gupta A, Prabhu S, Sureka J, Chacko G. Role of diffusion weighted MRI in differentiating typical from atypical meningiomas at 1.5 and 3T MRI. The Egyptian Journal of Radiology and Nuclear Medicine 2013;44:635–640.

  31. Hakyemez B, Yildirim N, Gokalp G, Erdogan C, Parlak M. The contribution of diffusion-weighted MR imaging to distinguishing typical from atypical meningiomas. Neuroradiology 2006;48:513–520.

  32. Yin B, Liu L, Zhang BY, Li YX, Li Y, Geng DY. Correlating apparent diffusion coefficients with histopathologic findings on meningiomas. Eur J Radiol 2012;81(12):4050–6.

  33. Tang Y, Dundamadappa SK, Thangasamy S, Flood T, Moser R, Smith T, et al. Correlation of apparent diffusion coefficient with Ki-67 proliferation index in grading meningioma. AJR Am J Roentgenol 2014; 202(6):1303–1308.

  34. Surov A, Gottschling S, Mawrin C, Prell J, Spielmann R, Wienke A, Fiedler E. Diffusion-Weighted Imaging in Meningioma: Prediction of Tumor Grade and Association with Histopathological Parameters. Transl Oncol 2015;8(6):517–523.

  35. Toh CH, Castillo M, Wong AM, Wei KC, Wong HF, Ng SH, et al. Differentiation between classic and atypical meningiomas with use of diffusion tensor imaging. AJNR 2008;29:1630–1635.

  36. Wang S, Kim S, Zhang Y, et al. Determination of grade and subtype of meningiomas by using histogram analysis of diffusion-tensor imaging metrics. Radiology 2012;262:584–592.




2020     |     www.medigraphic.com