Home Utility of Apparent Diffusion Coefficient Ratios in Distinguishing Common Pediatric Cerebellar Tumors
Post
Cancel

Utility of Apparent Diffusion Coefficient Ratios in Distinguishing Common Pediatric Cerebellar Tumors

Rationale and Objectives

The aim of this study was to identify clinically useful tumor/normal brain apparent diffusion coefficient (ADC) ratios for distinguishing common pediatric cerebellar tumors.

Materials and Methods

Review of medical records revealed 79 patients with cerebellar tumors who underwent preoperative magnetic resonance imaging, including diffusion-weighted imaging sequences, and surgery. There were 31 pilocytic astrocytomas, 27 medulloblastomas, 14 ependymomas, and seven atypical teratoid/rhabdoid tumors. ADC values were measured by placing regions of interest on the solid tumor and normal brain parenchyma by two reviewers. Tumor/normal brain ADC ratios were calculated.

Results

Mean ADC values of the pilocytic astrocytomas were greater than those of ependymomas, whose mean ADC values were greater than those of medulloblastomas and atypical teratoid/rhabdoid tumors. Using a tumor/normal brain ADC ratio threshold of 1.70 to distinguish pilocytic astrocytomas from ependymomas, sensitivity of 92% and specificity of 79% were achieved. A tumor/normal brain ADC ratio threshold of 1.20 enabled the sorting of ependymomas from medulloblastomas with sensitivity of 93% and specificity of 88%.

Conclusions

Tumor/normal brain ADC ratios allow the distinguishing of common pediatric cerebellar tumors.

Central nervous system tumors are the most common solid neoplasms of childhood . Approximately half of pediatric central nervous system tumors are located in the posterior fossa . Unlike tumors of the supratentorial compartment, pediatric cerebellar tumors are easier to distinguish from one another because of their location, appearance, and spread pattern and the age of the patient at presentation. Several studies have shown that diffusion characteristics of the common pediatric cerebellar tumors may be helpful in rendering an accurate preoperative diagnosis . Medulloblastomas generally show lower apparent diffusion coefficients (ADC), while pilocytic astrocytomas (PAs) display greater ADC values . There has been some debate on whether PAs may show lower ADC value than the normal brain parenchyma . In clinical practice, the reader generally contrasts the signal intensity of the tumor on diffusion-weighted images or on the ADC map against the normal brain parenchyma to determine the diffusion characteristics of the tumor. The objectives of our retrospective study were to investigate the ADC values and tumor/normal brain ADC ratios of common cerebellar tumors in a larger number of patients than previously published and to identify tumor/normal brain ADC ratio thresholds that may be useful in clinical practice.

Materials and methods

Patient Population

Review of the neuro-oncology database from January 2001 through May 2010 yielded 287 patients with neoplasms in the posterior fossa. Fifty-two patients (18.11%) with brain stem tumors were excluded. Relatively infrequent cerebellar tumors ( n ≤ 5) were excluded. The details of the excluded 20 posterior fossa lesions (8.51%) are shown in Table 1 . There were 95 PAs, 73 medulloblastomas, 30 ependymomas, and 17 atypical teratoid/rhabdoid tumors (AT/RTs). Of these, the 79 patients (age range, 0.25–18.73 years; mean age, 5.90 years; 51 male) who had preoperative magnetic resonance imaging, including a diffusion-weighted imaging sequence not hampered by magnetic susceptibility artifacts generated by dental hardware, and first surgery performed at our institution were included in this study. Pathologic diagnoses were made according to the latest World Health Organization (WHO) classification of tumors of the central nervous system . This study was reviewed and approved for assurances of patient safety and confidentiality by our institutional review board.

Table 1

Histology of the Cerebellar Tumors Excluded from the Study

Histology_n_ Choroid plexus papilloma 5 Ganglioglioma 5 Glioblastoma multiforme 4 Others (eg, immature teratoma, low-grade glial neoplasm, oligodendroglioma) 6

Get Radiology Tree app to read full this article<

Imaging and Measurement of ADC Values

Get Radiology Tree app to read full this article<

Statistical Analysis

Get Radiology Tree app to read full this article<

Get Radiology Tree app to read full this article<

Results

Get Radiology Tree app to read full this article<

Table 2

Patient Demographics and Tumor Types

Tumor Type_n_ Male/Female Age (y), Mean (Range) Pilocytic astrocytoma 31 15/16 7.35 (1.44–18.73) Medulloblastoma 27 19/8 6.16 (1.15–14.18) Ependymoma 14 13/1 4.61 (0.46–17.18) Atypical teratoid/rhabdoid tumor 7 4/3 1.06 (0.25–2.29) Total 79

Table 3

Mean ADC Values (×10 −6 mm 2 /s) Measured by the Two Reviewers

Tumor ADC Value Reviewer 1 Reviewer 2 Pilocytic astrocytoma 1632.22 1631.41 Medulloblastoma 677.67 687.84 Ependymoma 1042.11 1008.78 Atypical teratoid/rhabdoid tumor 606.95 584.62

ADC, apparent diffusion coefficient.

Figure 1, Box-and-whisker plots showing the apparent diffusion coefficient (ADC) values obtained from the tumors and normal brain by the two reviewers. AT/RT, atypical teratoid/rhabdoid tumor; PA, pilocytic astrocytoma by the two reviewers ( a, Reviewer 1; b, Reviewer 2).

Get Radiology Tree app to read full this article<

Get Radiology Tree app to read full this article<

Get Radiology Tree app to read full this article<

Table 4

Tumor/Normal Brain Apparent Diffusion Coefficient Ratios

Tumor Type Reviewer 1 Reviewer 2 Tumor/Cerebellum Tumor/Thalamus Tumor/Cerebellum Tumor/Thalamus Pilocytic astrocytoma 2.30 2.07 2.29 2.06 Medulloblastoma 0.97 0.87 0.99 0.89 Ependymoma 1.58 1.42 1.54 1.39 Atypical teratoid/rhabdoid tumor 0.83 0.73 0.87 0.84

Get Radiology Tree app to read full this article<

Get Radiology Tree app to read full this article<

Figure 2, Pilocytic astrocytoma in a 2.27-year-old male patient. Axial T2-weighted image (a), axial gadolinium-enhanced T1-weighted image (b), and axial apparent diffusion coefficient (ADC) map images (c,d) show a mass arising from the left cerebellar hemisphere. White arrows indicate the tumor which is enhancing, and black arrows indicate the vasogenic edema. (d) Representative sampling of the tumor with an ADC value of 1567.24 × 10 −6 mm 2s, obtained from an area of 1.8793 mm 2 . The solid, enhancing component of the tumor was sampled on the ADC map. For normal brain, the right cerebellar hemisphere was used to avoid vasogenic edema. The tumor/normal brain ADC ratio was 2.35. This ratio was calculated from three different samples of the tumor. sd, standard deviation.

Figure 3, Ependymoma in a 1.92-year-old male patient. Axial T2-weighted image (a) and axial apparent diffusion coefficient (ADC) map image (b) show a mass in the fourth ventricle. The tumor/normal brain ADC ratio was 1.47.

Figure 4, Medulloblastoma in a 2.49-year-old female patient. Axial T2-weighted image (a) and axial apparent diffusion coefficient (ADC) map image (b) display a large fourth ventricular mass. The tumor/normal brain ADC ratio was 0.90.

Figure 5, Atypical teratoid/rhabdoid tumor in a 2.29-year-old female patient. Axial T2-weighted image (a) and axial apparent diffusion coefficient (ADC) map image (b) demonstrate a mass in the fourth ventricle. The tumor/normal brain ADC ratio was 0.90.

Get Radiology Tree app to read full this article<

Get Radiology Tree app to read full this article<

Get Radiology Tree app to read full this article<

Discussion

Get Radiology Tree app to read full this article<

Get Radiology Tree app to read full this article<

Get Radiology Tree app to read full this article<

Get Radiology Tree app to read full this article<

Get Radiology Tree app to read full this article<

Get Radiology Tree app to read full this article<

Get Radiology Tree app to read full this article<

Get Radiology Tree app to read full this article<

Get Radiology Tree app to read full this article<

Get Radiology Tree app to read full this article<

Get Radiology Tree app to read full this article<

Get Radiology Tree app to read full this article<

Get Radiology Tree app to read full this article<

Get Radiology Tree app to read full this article<

Get Radiology Tree app to read full this article<

Conclusions

Get Radiology Tree app to read full this article<

References

  • 1. Meadows A.T., Friedman D.L., Neglia J.P., et. al.: Second neoplasms in survivors of childhood cancer: findings from the Childhood Cancer Survivor Study cohort. J Clin Oncol 2009; 27: pp. 2356-2362.

  • 2. Central Brain Tumor Registry of the United States. CBTRUS statistical report: primary brain and central nervous system tumors diagnosed in the United States in 2004-2007. Available at: http://www.cbtrus.org . Accessed September 15, 2011.

  • 3. Harwood-Nash D.C.: Primary neoplasms of the central nervous system in children. Cancer 1991; 67: pp. 1223-1228.

  • 4. Jaremko J.L., Jans L.B., Coleman L.T., et. al.: Value and limitations of diffusion-weighted imaging in grading and diagnosis of pediatric posterior fossa tumors. AJNR Am J Neuroradiol 2010; 31: pp. 1613-1616.

  • 5. Rumboldt Z., Camacho D.L., Lake D., et. al.: Apparent diffusion coefficients for differentiation of cerebellar tumors in children. AJNR Am J Neuroradiol 2006; 27: pp. 1362-1369.

  • 6. Schneider J.F., Confort-Gouny S., Viola A., et. al.: Multiparametric differentiation of posterior fossa tumors in children using diffusion-weighted imaging and short echo-time 1H-MR spectroscopy. J Magn Reson Imaging 2007; 26: pp. 1390-1398.

  • 7. Tzika A.A., Astrakas L.G., Zarifi M.K., et. al.: Multiparametric MR assessment of pediatric brain tumors. Neuroradiology 2003; 45: pp. 1-10.

  • 8. Tzika A.A., Zarifi M.K., Goumnerova L., et. al.: Neuroimaging in pediatric brain tumors: Gd-DTPA-enhanced, hemodynamic, and diffusion MR imaging compared with MR spectroscopic imaging. AJNR Am J Neuroradiol 2002; 23: pp. 322-333.

  • 9. Rumboldt Z.: The holy grail and the quest for the gold standard. AJNR Am J Neuroradiol 2010; 31: pp. 1617-1618.

  • 10. Scheithauer BW, Hawkins C, Tihan T, et al. Pilocytic astrocytoma. In: Louis DN, Ohgaki H, Wiestler OD, et al., eds. WHO Classification of Tumours of the Central Nervous System. Lyon, France: IACR, 2007:14–21.

  • 11. McLendon R.E., Wiestler O.D., Kros J.M., et. al.: Ependymoma.Louis D.N.Ohgaki H.Wiestler O.D. et. al.WHO Classification of Tumours of the Central Nervous System.2007.IACRLyon, France:pp. 74-78.

  • 12. Giangaspero F., Eberhart C.G., Haapasalo H., et. al.: Medulloblastoma.Louis D.N.Ohgaki H.Wiestler O.D. et. al.WHO Classification of Tumours of the Central Nervous System.2007.IARCLyon, France:pp. 132-140.

  • 13. Judkins A.R., Eberhart C.G., Wesseling P.: Atypical teratoid/rhabdoid tumor.Louis D.N.Ohgaki H.Wiestler O.D. et. al.WHO Classification of Tumours of the Central Nervous System.2007.IARCLyon, France:pp. 147-149.

  • 14. Guo A.C., Cummings T.J., Dash R.C., et. al.: Lymphomas and high-grade astrocytomas: comparison of water diffusibility and histologic characteristics. Radiology 2002; 224: pp. 177-183.

  • 15. Brunberg J.A., Chenevert T.L., McKeever P.E., et. al.: In vivo MR determination of water diffusion coefficients and diffusion anisotropy: correlation with structural alteration in gliomas of the cerebral hemispheres. AJNR Am J Neuroradiol 1995; 16: pp. 361-371.

  • 16. Garcia-Perez A.I., Lopez-Beltran E.A., Kluner P., et. al.: Molecular crowding and viscosity as determinants of translational diffusion of metabolites in subcellular organelles. Arch Biochem Biophys 1999; 362: pp. 329-338.

  • 17. Tanner J.E.: Intracellular diffusion of water. Arch Biochem Biophys 1983; 224: pp. 416-428.

  • 18. Gauvain K.M., McKinstry R.C., Mukherjee P., et. al.: Evaluating pediatric brain tumor cellularity with diffusion-tensor imaging. AJR Am J Roentgenol 2001; 177: 449–354

  • 19. Jenkinson M.D., Smith T.S., Brodbelt A.R., et. al.: Apparent diffusion coefficients in oligodendroglial tumors characterized by genotype. J Magn Reson Imaging 2007; 26: pp. 1405-1412.

  • 20. Yamashita Y., Kumabe T., Higano S., et. al.: Minimum apparent diffusion coefficient is significantly correlated with cellularity in medulloblastomas. Neurol Res 2009; 31: pp. 940-946.

  • 21. Jenkinson M.D., du Plessis D.G., Smith T.S., et. al.: Cellularity and apparent diffusion coefficient in oligodendroglial tumours characterized by genotype. J Neurooncol 2010; 96: pp. 385-392.

  • 22. Schneider J.F., Viola A., Confort-Gouny S., et. al.: Infratentorial pediatric brain tumors: the value of new imaging modalities. J Neuroradiol 2007; 34: pp. 49-58.

  • 23. Koral K., Gargan L., Bowers D.C., et. al.: Imaging characteristics of atypical teratoid-rhabdoid tumor in children compared with medulloblastoma. AJR Am J Roentgenol 2008; 190: pp. 809-814.

  • 24. Northcott P.A., Korshunov A., Witt H., et. al.: Medulloblastoma comprises four distinct molecular variants. J Clin Oncol 2011; 29: pp. 1408-1414.

This post is licensed under CC BY 4.0 by the author.