Malignant Astrocytic Tumors: Clinical Importance of Apparent Diffusion Coefficient in Prediction of Grade and Prognosis

Purpose: To retrospectively assess the apparent diffusion coefficient (ADC) for prediction of malignancy and prognosis of malignant astrocytic tumors.

Materials and Methods: The institutional review board approved this study and did not require patient informed consent. Findings from 37 consecutive patients (21 men, 16 women; mean age, 43 years) with pathologically proved malignant astrocytic tumors that included 22 glioblastomas (GBMs) and 15 anaplastic astrocytomas (AAs) were retrospectively evaluated. The minimum ADC value of each tumor was preoperatively determined from several regions of interest defined in the tumor, preferably with avoidance of cystic or necrotic components, on ADC maps derived from isotropic diffusion-weighted images. Surgical intervention, followed by radiation therapy, was undertaken in all cases according to hospital protocol. Immunohistologically, Ki-67 labeling index (LI), indicating cell proliferation, was also determined. The patients were classified into two groups, progressive and stable, according to the 2-year observation after the initial treatment. Correlation analysis (Pearson product moment correlation), Student t test, Welch test, receiver operating characteristic analysis, and Kaplan-Meier method with log-rank test were used for statistical evaluation.

Results: There was a significant negative correlation between minimum ADC and Ki-67 LI (r = −0.562, P < .001). The mean minimum ADC (0.834 × 10−3 mm2 · sec−1) of GBM was significantly lower than that (1.06 × 10−3 mm2 · sec−1) of AA (P < .001, Student t test). The mean minimum ADC (0.80 × 10−3 mm2 · sec−1) of the progressive group was significantly lower than that (1.037 × 10−3 mm2 · sec−1) of the stable group (P < .001). The cutoff value of 0.90 × 10−3 mm2 · sec−1 for minimum ADC for differentiation of patients with a favorable prognosis from those with a poor prognosis provided the best combination of sensitivity (79%) and specificity (81%) (receiver operating characteristic analysis). The significant difference in the prognosis between two groups classified by using this cutoff value of minimum ADC was noted (P = .002, log-rank test).

Conclusion: The minimum ADC of malignant astrocytomas can provide additional information about their clinical malignancy related to posttreatment prognosis.

© RSNA, 2006


  • 1 Kleihues P, Cavenee WK. World Health Organization classification of tumours: pathology and genetics of tumours of the central nervous system. Lyon, France: International Agency for Research on Cancer, 2000. Google Scholar
  • 2 Salcman M. Glioblastoma multiforme and anaplastic astrocytoma. In: Kaye AH, Law ER Jr, eds. Brain tumors: an encyclopedic approach. 2nd ed. London, England: Churchill Livingstone, 2001. Google Scholar
  • 3 Kiss R, Dewitte O, Decaestecker C, et al. The combined determination of proliferative activity and cell density in the prognosis of adult patients with supratentorial high-grade astrocytic tumors. Am J Clin Pathol 1997; 107(3): 321–331. Crossref, MedlineGoogle Scholar
  • 4 Torp SH, Granli US. Proliferative activity in human glioblastomas assessed by various techniques. APMIS 2001;109(12):865–869. Crossref, MedlineGoogle Scholar
  • 5 Torp SH. Diagnostic and prognostic role of Ki67 immunostaining in human astrocytomas using four different antibodies. Clin Neuropathol 2002;21(6):252–257. MedlineGoogle Scholar
  • 6 Neder L, Colli BO, Machado HR, Carlotti CG Jr, Santos AC, Chimelli L. MIB-1 labeling index in astrocytic tumors: a clinicopathologic study. Clin Neuropathol 2004;23(6):262–270. MedlineGoogle Scholar
  • 7 Gupta RK, Cloughesy TF, Sinha U, et al. Relationships between choline magnetic resonance spectroscopy, apparent diffusion coefficient and quantitative histopathology in human glioma. J Neurooncol 2000;50(3):215–226. Crossref, MedlineGoogle Scholar
  • 8 Gupta RK, Sinha U, Cloughesy TF, Alger JR. Inverse correlation between choline magnetic resonance spectroscopy signal intensity and the apparent diffusion coefficient in human glioma. Magn Reson Med 1999;41(1):2–7. Crossref, MedlineGoogle Scholar
  • 9 Bulakbasi N, Guvenc I, Onguru O, Erdogan E, Tayfun C, Ucoz T. The added value of the apparent diffusion coefficient calculation to magnetic resonance imaging in the differentiation and grading of malignant brain tumors. J Comput Assist Tomogr 2004;28(6):735–746. Crossref, MedlineGoogle Scholar
  • 10 Bulakbasi N, Kocaoglu M, Ors F, Tayfun C, Ucoz T. Combination of single-voxel proton MR spectroscopy and apparent diffusion coefficient calculation in the evaluation of common brain tumors. AJNR Am J Neuroradiol 2003;24(2):225–233. MedlineGoogle Scholar
  • 11 Gauvain KM, McKinstry RC, Mukherjee P, et al. Evaluating pediatric brain tumor cellularity with diffusion-tensor imaging. AJR Am J Roentgenol 2001;177(2):449–454. Crossref, MedlineGoogle Scholar
  • 12 Lam WW, Poon WS, Metreweli C. Diffusion MR imaging in glioma: does it have any role in the pre-operation determination of grading of glioma? Clin Radiol 2002;57(3):219–225. Crossref, MedlineGoogle Scholar
  • 13 Muti M, Aprile I, Principi M, et al. Study on the variations of the apparent diffusion coefficient in areas of solid tumor in high grade gliomas. Magn Reson Imaging 2002;20(9):635–641. Crossref, MedlineGoogle Scholar
  • 14 Sugahara T, Korogi Y, Kochi M, et al. Usefulness of diffusion-weighted MRI with echo-planar technique in the evaluation of cellularity in gliomas. J Magn Reson Imaging 1999;9(1):53–60. Crossref, MedlineGoogle Scholar
  • 15 Guo AC, Cummings TJ, Dash RC, Provenzale JM. Lymphomas and high-grade astrocytomas: comparison of water diffusibility and histologic characteristics. Radiology 2002;224(1):177–183. LinkGoogle Scholar
  • 16 Oken MM, Creech RH, Tormey DC, et al. Toxicity and response criteria of the Eastern Cooperative Oncology Group. Am J Clin Oncol 1982;5(6):649–655. Crossref, MedlineGoogle Scholar
  • 17 Calvar JA, Meli FJ, Romero C, et al. Characterization of brain tumors by MRS, DWI and Ki-67 labeling index. J Neurooncol 2005;72(3):273–280. Crossref, MedlineGoogle Scholar
  • 18 Tamiya T, Kinoshita K, Ono Y, Matsumoto K, Furuta T, Ohmoto T. Proton magnetic resonance spectroscopy reflects cellular proliferative activity in astrocytomas. Neuroradiology 2000;42(5):333–338. Crossref, MedlineGoogle Scholar
  • 19 Oh J, Henry RG, Pirzkall A, et al. Survival analysis in patients with glioblastoma multiforme: predictive value of choline-to-N-acetylaspartate index, apparent diffusion coefficient, and relative cerebral blood volume. J Magn Reson Imaging 2004;19(5):546–554. Crossref, MedlineGoogle Scholar
  • 20 Aprile I, Muti M, Principi M, et al. A magnetic resonance comparative study between enhancement, rCBV and ADC in brain glioblastomas. Radiol Med (Torino) 2002;104(1-2):87–91. MedlineGoogle Scholar
  • 21 Yang D, Korogi Y, Sugahara T, et al. Cerebral gliomas: prospective comparison of multivoxel 2D chemical-shift imaging proton MR spectroscopy, echoplanar perfusion and diffusion-weighted MRI. Neuroradiology 2002;44(8):656–666. Crossref, MedlineGoogle Scholar

Article History

Published in print: 2006